Data Analytics Bootcamp 5.0: Job Placement Support + AI Automation & Data Engineering Basics
Industry Projects-Based Bootcamp Created by Hiring Managers
Prepare for high-demand roles like Data Analyst, Business Analyst, Finance Analyst, & Marketing Analyst with our Data Analytics Bootcamp (trusted by a community of 1M+ learners). Created by industry hiring managers, this hands-on program teaches real-world skills using modern tools and AI concepts for analysts. With practical job support integrated, you'll gain the confidence to successfully launch your analytics career.
50+
Real Scenarios
18
Business Projects
2
Virtual Internships
Free
Portfolio Website
Lifetime
Content Validity
20K+
Enrolled Learners
Join our Bootcamp
Learn In-demand Skills
Get Hired by Top Companies
Get AI Toolkit For Professionals at a 25% subsidy along with your Bootcamp. Click to Benefit
No Questions Asked Refund Policy
Get your money within 30 days of enrollment
Added Benefit
If you have already taken our paid Data Analytics course(s), you will pay only the difference (This Bootcamp Price - Money You Paid for Data Analytics Course(s) Price)
50+
Real Scenarios
18
Business Projects
2
Virtual Internships
Free
Portfolio Website
Lifetime
Content Validity
20K+
Enrolled Learners
Why this is the most effective Data Analytics Bootcamp?
-
Automated Resume Builder, LinkedIn optimizer and Portfolio Website to showcase your work
-
Unlimited daily doubt clearance support via private Discord community
-
Dedicated module to become an AI-enabled Data Analyst ( AI Workflow automation, Effective Prompting, AI/ML Basics)
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Data‑engineering basics module — pipelines, ETL, and data prep every analyst needs
-
Practical job assistance (Resume & Interview Preparation + Interview and Job Application Playbook + Interview Leads + Building Online Credibility + Mock Interview)
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Real-time industry-based projects in FMCG, Hospitality, Insurance, Telecom, Banking & Finance domain, Sales, Marketing, HR & Supply Chain departments
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Complex datasets that have more than 7 Million records like you will get in a company
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Highly engaging content with the cinematic experience, real business practice problems, business meetings, etc.
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Easy explanation of complex topics by Dhaval Patel, a famous Youtuber (1M+ subs) teacher & active data industry expert
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Real-time tasks prepared by Hemanand Vadivel, a data analytics leader with 8+ years of experience in Europe
Key Reasons
Why Should You Enroll in This Data Analytics Bootcamp?
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The Features of DA Bootcamp 5.0
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AI Automation & Data Engineering Basics
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Enhanced Practical Job Assistance
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Interview Support & Guidance
2630 learners have created their portfolio websites
Explore PortfoliosHear It From
Our Happy Learners
Our content is rated 4.9/5 from 52861+ Learners
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DA Bootcamp
Landed a Job
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Landed a Job
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Python
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SQL
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Excel
Landed a Job
I recently completed the Data Analytics bootcamp offered by Codebasics, which included a virtual internship with AtliQ Technologies, and I can confidently say it was one of the best decisions I made for my career.
The course is extremely well-structured and beginner-friendly. It covers everything needed to become a job-ready data analyst—from Excel, SQL, and Power BI to real-world problem-solving and data storytelling. The teaching style of Dhaval Patel is simple, clear, and highly practical, which made even complex concepts easy to understand.
The highlight of the course was the virtual internship with AtliQ Technologies, where I got the chance to apply everything I had learned in a real-world business setting. It gave me hands-on experience with solving data problems from various departments. This was a turning point in my journey.
The best part—this course and internship experience helped me secure a job opportunity! I’ve been selected for a role, and once the formalities are completed, I look forward to sharing the full update on LinkedIn.
I'm truly thankful to Dhaval Patel, Hemanand sir, and the entire Codebasics team for designing such a high-quality, practical learning path. I would highly recommend this course to anyone who wants to build a strong, real-world foundation in data analytics and step confidently into the industry.
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Landed a Job
Being from a non-tech background and I know only economics and statistics, I feel happy because these industry experts made our life so easy. From the bottom of my heart, I congratulate Mr Dhaval Patel for introducing this fantastic course.
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Landed a Job
The best excel course that I had ever taken, The Videos are of optimum length with best information than ever, The Projects are of so good quality and we have worked so smoothly on them that I didn't even realize that I had just worked with data of over 1 million records.
Also making cinematic videos to make us feel like as if we are working as a data analyst in company kudos for that to all the codebasics team.
Also apart from just technical knowledge they taught us Real time Business skills like Project priority Matrix , Scenario planning etc which makes this course best among all.
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Landed a Job
Thank you for well-managed and customized course. Its so nicely explained even a beginner will be hassle-free while learning it. This course is highly recommended to those who either wants to learn data analysis or are on the verge of building a portfolio(like me).
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Power BI
Completing the Advanced Excel course was an absolute game-changer for me! From Power Query to DAX, each module was packed with exciting features that completely transformed the way I work with data. Learning to unleash Excel's full potential has been an exhilarating journey, and I feel equipped to tackle any data challenge with confidence. Highly recommend this course to anyone ready to take their Excel skills to the next level! A heartfelt thanks to Peter Pandey for his enthusiastic learning spirit and to Tony Sharma for his passionate business teachings.
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You Can
Work On Real World Projects
That
Hiring Managers Like
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Executive Insights: Insurance Domain
Use Python, SQL, Excel, and Power BI to provide insights to the executive team in the insurance industry. This is a virtual internship project that simulates working on a client project and involves ad-hoc tasks and final solution implementation.
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Revenue Analytics: Hospitality Domain
You will generate revenue insights in the hospitality domain by performing data cleaning, data transformation, and insights generation using Python and Pandas.
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Business Insights 360: FMCG Domain
You will implement end-to-end data analytics solution (along with deployment) in Power BI to generate insights for finance, sales, marketing, and supply chain departments in an FMCG company.
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Scenario Planning
Tool
Create a scenario planning tool in Excel to meet gross margin target. You will analyze best, realistic, and worst-case scenarios based on various business metrics such as net sales, discount percentage, gross margin, spread between the margin and the target, etc.
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Project Priority
Matrix
A project manager is experiencing difficulties in prioritizing projects. To assist them, you will create an Excel tool for a project priority matrix that utilizes a feasibility/impact analysis to prioritize projects effectively.
Overview
What you'll learn in
this Data Analytics Bootcamp
Welcome to The Bootcamp Experience
00h:45m:43s on-demand video
|
15 Lectures
1:
Welcome to The Bootcamp Experience
15 Lectures
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1.1: Why Should You Become a Data Analyst?
Free -
1.2: How Do I Know If The Data Analyst Role Is Suitable For Me?
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1.3: Is Computer Science Degree / Young Age / Relevant Work Experience Mandatory?
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1.4: What Kind of Job Assistance Do You Provide?
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1.5: How Do I Get Doubt-Clearing Support? (Discord)
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1.6: How Much Time Do I Need to Complete The Bootcamp?
Free -
1.7: Do I get a Real Internship Certificate After Completing a Virtual Internship?
Free -
1.8: Do the Creators of This Bootcamp Have Real Industry Experience?
Free -
1.9: How Many Business Projects Will I Complete in This Bootcamp?
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1.10: How can I Trust That This Bootcamp Has the Best Content on Planet Earth?
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1.11: What Domain and Functional Knowledge Will You Build and How?
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1.12: What are the Soft Skills I Will Acquire By the End of Bootcamp?
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1.13: Bootcamp Syllabus Overview
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1.14: How Will I Be Informed About The Monthly Live Webinars?
Free -
1.15: System Requirements
Excel: Mother of Business Intelligence
09h:05m:26s on-demand video
|
70 Lectures
2:
Excel Basics: Getting Started
13 Lectures
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2.1: Peter Pandey’s Journey and Need to Learn Excel
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2.2: Installing Excel: Windows / Mac
Free -
2.3: Getting Familiar With Excel
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2.4: Getting More Familiar With Excel
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2.5: Introduction to Formulas
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2.6: Formula Behavior
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2.7: Introduction to Tables
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2.8: Introduction to Charts
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2.9: Other Essential Features
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2.10: Peter Gets His First Assignment From His Senior
Free -
2.11: Practice Exercise: Personal Expense Tracker
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2.12: Quiz
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2.13: Chapter Summary
4:
Excel Basics: Applying Business Maths & Statistics
9 Lectures
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4.1: Basic Maths to Business Metrics (Bollywood movies revenue avg)
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4.2: Commonly Used Business Metrics (P&L)
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4.3: Commonly Used Statistic Concepts (Mean, Median, Mode)
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4.4: Commonly Used Statistic Concepts (Variance, Standard Deviation)
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4.5: Commonly Used Statistic Concepts (Correlation)
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4.6: Peter Gets to Solve a Real Time Problem
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4.7: Practice Exercise
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4.8: Quiz
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4.9: Chapter Summary
6:
Excel Basics+: Creating Business Reports Using Pivot Table & Power Pivot
14 Lectures
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6.1: Pivot Table Introduction: Apple Product Sales
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6.2: Pivot Table For Movie Analytics
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6.3: Creating a Report Using Pivot Table
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6.4: Pivot Table Options & Formatting
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6.5: Using Power Pivot & DAX For Powerful Business Reports
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6.6: Adding Targets Using Data Modelling in Power Pivot
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6.7: Breaking Down Complex Problems: Thinking Process of a Highly Paid Data Analyst
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6.8: More Business Metrics and Conditional Formatting
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6.9: VBA Basics & How Much VBA You Should Learn
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6.10: Peter Practices On His Own
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6.11: Practice Exercise
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6.12: Quiz
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6.13: I Need a Favour
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6.14: Chapter Summary
8:
Excel Advanced: Sales Analytics
12 Lectures
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8.1: ETL (Extract, Transform and Load Data) in Excel I
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8.2: ETL (Extract, Transform and Load Data) in Excel II
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8.3: Business Report: Solution Design Thought Process
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8.4: Creating Connections Among Tables Using Data Modelling
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8.5: Adding a Date Table Using Power Query
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8.6: Functional Knowledge: Sales
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8.7: Sales Analytics: Creating Customer Performance Report
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8.8: User Empathetic Report Design
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8.9: Sales Analytics: Creating Market Performance vs Targets Reported
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8.10: Practice Exercise
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8.11: Quiz
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8.12: Chapter Summary
9:
Excel Advanced: Finance Analytics
11 Lectures
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9.1: Understanding P & L
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9.2: Functional Knowledge: Finance
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9.3: Adding the Finance Data to Data Model
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9.4: Finance Analytics: P & L by Year Report
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9.5: Fine Tuning P & L By Year Report
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9.6: Adding Months & Quarters in Data Model
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9.7: Finance Analytics: P & L by Months Report
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9.8: Fine Tuning P & L By Month Report
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9.9: Practice Exercise
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9.10: Quiz
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9.11: Chapter Summary
10:
Excel Advanced: Real-Time Business Applications
9 Lectures
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10.1: Wanda’s Challenge With Prioritizing Projects
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10.2: Peter & Tony Creates a Project Priority Matrix
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10.3: Mentor Talk: Being A Problem Solver
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10.4: Practice Exercise
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10.5: Bruce Haryali Needs Help With Excel
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10.6: Peter & Tony Creates a Scenario Planning Tool
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10.7: Mentor Talk: Growth Zone
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10.8: Practice Exercise
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10.9: Quiz
Start Building Your Online Credibility
00h:26m:24s on-demand video
|
6 Lectures
Get Job Ready: Power BI Data Analytics for All Levels 3.0
19h:10m:41s on-demand video
|
137 Lectures
2:
Power BI Basics: Getting Started
13 Lectures
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2.1: Install Power BI
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2.2: Power BI: Tool Introduction
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2.3: Power Query: Intro & Column Transformations
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2.4: Power Query: Merging and Appending
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2.5: Power Query: Best Practices
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2.6: Introduction to DAX
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2.7: Introduction to DAX - II
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2.8: Introduction to Data Modeling
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2.9: Introduction to Creating Visuals
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2.10: Tony asks Peter to Fix Data Holes
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2.11: Practice Exercise
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2.12: Chapter Summary
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2.13: Quiz
3:
Project Planning and Scoping
9 Lectures
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3.1: Problem Statement
Free -
3.2: The Email that Started this Project
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3.3: Project Kick-off Meeting
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3.4: Learn how a ‘Project Charter’ is Used in Companies
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3.5: Project Kick-off: Session Debrief
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3.6: Senior Data Analyst Sets Up the Next Steps with Junior Data Analyst
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3.7: Simplified: Profit and Loss Statement
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3.8: Chapter Summary
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3.9: Quiz
4:
Power BI Basics: Data collection, Exploration & Validation
10 Lectures
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4.1: Simplified: Data Warehouse, OLTP vs OLAP, Data Catalog
Free -
4.2: Install MySQL and Import Data
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4.3: Simplified: Data Exploration Using SQL, Star Schema, Fact vs Dimension Tables
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4.4: Load and connect data with MySQL
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4.5: Create a Date Dimension Table
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4.6: Validate Data against Benchmark Numbers
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4.7: Tony’s Valuable Advise to Peter
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4.8: Practice Exercise
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4.9: Chapter Summary
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4.10: Quiz
7:
Power BI Advanced: Data Modeling & Calculated Columns
11 Lectures
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7.1: Power Query or DAX for Generating Calculated Columns?
Free -
7.2: Data Modelling: Star and Snowflake Schema
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7.3: Data Modeling: Connect Dimensions with Fact Tables
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7.4: Simplified: Why Do We Need Dimension Tables?
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7.5: Mentor Talk: Congratulations! You are Levelling Up!
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7.6: Create Calculated Columns Using DAX
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7.7: Easy Way to Verify Your Numbers in Power BI
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7.8: Assignment: Optimize Report and Reduce File Size by 25 %
Free -
7.9: I Need a Favour
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7.10: Chapter Summary
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7.11: Quiz
8:
Power BI Advanced: Build Finance View
15 Lectures
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8.1: Finance View: Prepare a List of Metrics
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8.2: Simplified: Calculate Function & Filter Context
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8.3: Finance View: Creating Metrics
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8.4: Finance View: Create P&L Table Structure
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8.5: Finance View: Create Last Year (LY) Column
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8.6: Finance View: Build an Ultimate DAX Measure for P & L Table Structure - I
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8.7: Finance View: Build an Ultimate DAX Measure for P & L Table Structure - II
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8.8: Finance View: Create ‘Quarters’ & ‘YTD/YTG’ Slicers
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8.9: Mentor Talk: Figuring Out Solutions
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8.10: Finance View: Create a Line chart to Show Performance Over Time
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8.11: Finance View: Build Top Product, Market & Region Visuals
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8.12: Intermediate Review: I Met Product Owner Nick and He Gave this Feedback!
Free -
8.13: Finance View: Add Net Profit
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8.14: Chapter Summary
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8.15: Quiz
9:
Power BI Advanced: Build Sales, Marketing & Supply Chain View
10 Lectures
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9.1: Review Sales View Mockup
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9.2: Sales View: Build Top Customers & Performance Matrix Visuals
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9.3: Sales View: Build Product Performance & Unit Economics Visuals
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9.4: Build Marketing View
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9.5: Simplified: Supply Chain Basics
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9.6: Supply Chain View: Review Mock Up
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9.7: Supply Chain View: Build Key Measures
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9.8: Supply Chain View: Build Visuals
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9.9: Chapter Summary
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9.10: Quiz
10:
Power BI Advanced: Designing an Effective Dashboard
9 Lectures
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10.1: Simplified: Dashboard vs Report
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10.2: 15 Design Rules for an Effective Dashboard
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10.3: Finalize Page Layout Design
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10.4: Create Home Page
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10.5: Design Finance Dashboard
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10.6: Add Key Elements to Finance Dashboard
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10.7: Copy the Design to Sales, Marketing & Supply Chain Dashboard
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10.8: Chapter Summary
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10.9: Quiz
12:
Stakeholder review & Feedback implementation
16 Lectures
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12.1: Stakeholder Analysis and its Significance
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12.2: Peter Recalls the Stakeholder Mapping Meeting
Free -
12.3: Stakeholder Review Meeting: How did it Go?
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12.4: This is the secret to be ‘Job Ready’!
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12.5: Practice Exercise: Quick Fixes
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12.6: Quick Fix: Chg% formula
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12.7: Practice Exercise: Implementing Dynamic Benchmark
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12.8: Practice Exercise: Adding Dynamic Slicer to Filter Visual
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12.9: Practice Exercise: Create a Toggle Button to Switch between Two Visuals
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12.10: Practice Exercise: Create a Tool Tip to Show Trend
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12.11: Learn: Adding Market Share Data
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12.12: Practice Exercise: Create an Executive Dashboard
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12.13: Learn: Performance Optimization
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12.14: Learn: Fix Data Quality Issues
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12.15: Chapter Summary
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12.16: Quiz
13:
Deploying the Solution: Power BI Service
7 Lectures
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13.1: Power BI Service Overview, Report Sharing, and Apps
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13.2: How to Set Up Automatic Data Refresh: My SQL
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13.3: How to Set Up Automatic Data Refresh: Excel
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13.4: Simplified: Collaboration, Bookmarks, and Insights in Power BI Service
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13.5: Driving the Extra Mile: Documentation and Maintenance
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13.6: Chapter Summary
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13.7: Quiz
14:
Practice Exercise Solutions
11 Lectures
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14.1: Solution: Quick Fixes
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14.2: Solution: Implementing Dynamic Targets (Add Targets)
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14.3: Solution: Implementing Dynamic Targets (Create a dynamic switch between Targets and LY)
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14.4: Solution: Implementing Dynamic Targets (P & L visuals to compare Target or LY based on selection)
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14.5: Solution: Adding Dynamic Slicer to Filter Visual
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14.6: Solution: Create a Toggle Button to Switch between Two Visuals
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14.7: Solution: Create a Tool Tip to Show Trend
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14.8: Solution: Create an Executive Dashboard (KPI Visuals)
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14.9: Solution: Create an Executive Dashboard (Key Insights by Subzone )
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14.10: Solution: Create an Executive Dashboard (Market Share Visual & Conditional Formatting)
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14.11: Solution: Create an Executive Dashboard (Final Enhancements)
16:
PBI Monthly Update Tasks
16 Lectures
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16.1: Intro
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16.2: Feature Updates Task -1
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16.3: Solution: Task - 1
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16.4: Feature Updates Task- 2
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16.5: Solution: Task - 2
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16.6: Feature Updates Task - 3
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16.7: Solution: Task - 3
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16.8: Feature Updates Task - 4
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16.9: Solution: Task - 4
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16.10: Feature Updates Task - 5
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16.11: Solution: Task - 5
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16.12: Feature Updates Task - 6
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16.13: Solution: Task - 6
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16.14: Feature Updates Task - 7
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16.15: Solution: Task - 7
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16.16: Feature Updates Task - 8
Building Online Credibility, Portfolio Projects & ATS Resume
03h:59m:49s on-demand video
|
23 Lectures
2:
Build Your Resume, Now!
8 Lectures
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2.1: What is ATS and Why it is Important?
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2.2: Follow These Guidelines to Build an Amazing Resume
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2.3: Improve the ATS Score of Your Resume
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2.4: Customize Resume as Per Job Posting
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2.5: Career Transition: Sample Experience Sections
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2.6: Meet Naveen, He is applying for a Job Like You!
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2.7: Knowledge Check
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2.8: Checkpoint
5:
Power BI Project(s) for Your Portfolio!
7 Lectures
-
5.1: Get a Shareable Public Link For Your Power BI Project
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5.2: Share Your Power BI Project with Potential Recruiters
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5.3: Differentiate Your Work with New Design
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5.4: How to differentiate your work - Expert Webinar
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5.5: One More Power BI Project for Your Portfolio
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5.6: Check Your Work With this Guided Project
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5.7: One Step Closer to Your Dream Portfolio
SQL Beginner to Advanced For Data Professionals
11h:15m:16s on-demand video
|
84 Lectures
2:
SQL Basics: Data Retrieval - Single Table
15 Lectures
-
2.1: Install MySQL: Windows
Free -
2.2: Install MySQL: Linux, Mac
Free -
2.3: Import Movies Dataset in MySQL
Free -
2.4: Retrieve Data Using Text Query (SELECT, WHERE, DISTINCT, LIKE)
Free -
2.5: Exercise - Retrieve Data Using Text Query (SELECT, WHERE, DISTINCT, LIKE)
Free -
2.6: Retrieve Data Using Numeric Query (BETWEEN, IN, ORDER BY, LIMIT, OFFSET)
Free -
2.7: Exercise - Retrieve Data Using Numeric Query (BETWEEN, IN, ORDER BY, LIMIT, OFFSET)
Free -
2.8: Summary Analytics (MIN, MAX, AVG, GROUP BY)
Free -
2.9: Exercise - Summary Analytics (MIN, MAX, AVG, GROUP BY)
Free -
2.10: HAVING Clause
Free -
2.11: Calculated Columns (IF, CASE, YEAR, CURYEAR)
Free -
2.12: Exercise - Calculated Columns (IF, CASE, YEAR, CURYEAR)
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2.13: The Data God’s Blessing
Free -
2.14: Quiz
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2.15: Chapter Summary
5:
SQL Basics: Database Creation & Updates
18 Lectures
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5.1: Database Normalization and Data Integrity
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5.2: Entity Relationship Diagram (ERD)
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5.3: Mentor Talk: Art of Googling
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5.4: Data Types: Numeric (INT, DECIMAL, FLOAT, DOUBLE)
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5.5: Data Types: String (VARCHAR, CHAR, ENUM)
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5.6: Data Types: Date, Time (DATETIME, DATE, TIME, YEAR, TIMESTAMP)
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5.7: Data Types: JSON, Spatial (JSON, GEOMETRY)
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5.8: Luck Favors the LinkedIn Post
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5.9: Primary key
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5.10: Foreign Key
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5.11: Create a Database From an Entity Relationship Diagram - ERD
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5.12: Import Data From a CSV File Into a Database
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5.13: Insert Statement
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5.14: Update and Delete
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5.15: I Need a Favour
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5.16: Expect the Unexpected: The Intermission Scene
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5.17: Quiz
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5.18: Chapter Summary
6:
AtliQ Hardware & Problem Statement
9 Lectures
-
6.1: The Rise of Databases at AtliQ
Free -
6.2: Relational vs No-SQL Database
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6.3: AtliQ Hardware’s Business Model
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6.4: Profit & Loss Statement
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6.5: ETL, Data Warehouse, OLAP vs OLTP, Data Catalog
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6.6: Fact vs Dimension Table, Star vs Snowflake Schema, Data Import
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6.7: Simplified: What is Kanban?
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6.8: Quiz
-
6.9: Chapter Summary
7:
SQL Advanced: Finance Analytics
10 Lectures
-
7.1: Backlog Grooming Meeting: Gross Sales Report
-
7.2: User-Defined SQL Functions
-
7.3: Exercise: User-Defined SQL Functions
-
7.4: Gross Sales Report: Monthly Product Transactions
-
7.5: Gross Sales Report: Total Sales Amount
-
7.6: Exercise: Yearly Sales Report
-
7.7: Stored Procedures: Monthly Gross Sales Report
-
7.8: Stored Procedure: Market Badge
-
7.9: Benefits of Stored Procedures
-
7.10: Quiz
8:
SQL Advanced: Top Customers, Products, Markets
16 Lectures
-
8.1: Problem Statement and Pre-Invoice Discount Report
-
8.2: Performance Improvement # 1
-
8.3: Performance Improvement # 2
-
8.4: Database Views: Introduction
-
8.5: Database Views: Post Invoice Discount, Net Sales
-
8.6: Exercise: Database Views
-
8.7: Top Markets and Customers
-
8.8: Exercise: Top Products
-
8.9: The Two Most Important Skills for the Data Analyst
-
8.10: Window Functions: OVER Clause
-
8.11: Window Functions: Using it in a Task
-
8.12: Exercise: Window Functions: OVER Clause
-
8.13: Window Functions: ROW_NUMBER, RANK, DENSE_RANK
-
8.14: Exercise: Window Functions: ROW_NUMBER, RANK, DENSE_RANK
-
8.15: 5 Ways SQL is Used in the Industry
-
8.16: Quiz
9:
SQL Advanced: Supply Chain Analytics
13 Lectures
-
9.1: Supply Chain Basics : Simplified
-
9.2: Problem Statement
-
9.3: Create a Helper Table
-
9.4: Database Triggers
-
9.5: Database Events
-
9.6: Temporary Tables & Forecast Accuracy Report
-
9.7: Exercise: CTE, Temporary Tables
-
9.8: Subquery vs CTE vs Views vs Temporary Table
-
9.9: User Accounts and Privileges
-
9.10: Database Indexes: Overview
-
9.11: Database Indexes: Composite Index
-
9.12: Database Indexes: Index Types
-
9.13: Quiz
Python: Beginner to Advanced For Data Professionals
16h:57m:31s on-demand video
|
108 Lectures
6:
Python Basics: Functions, Dictionaries, Tuples and File Handling
9 Lectures
-
6.1: Functions
-
6.2: Dictionary and Tuples
-
6.3: Modules and Pip
-
6.4: File Handling
-
6.5: Quiz: Functions, Dictionaries, Tuples and File Handling
-
6.6: Peter’s Request to Tony
-
6.7: Exercise: Functions, Dictionaries, Tuples and File Handling
-
6.8: Two Deadly Viruses Infecting Learners
-
6.9: Chapter Summary
15:
Project 2: Expense Tracking System
11 Lectures
-
15.1: Problem Statement & Tech Architecture
-
15.2: Database CRUD Operations
-
15.3: Automated Tests Setup for CRUD
-
15.4: Expense Management: Backend (FastAPI)
-
15.5: Expense Management: Logging
-
15.6: Streamlit Introduction
-
15.7: Expense Management: Frontend (Streamlit)
-
15.8: Analytics: Backend (FastAPI)
-
15.9: Analytics: Frontend (Streamlit)
-
15.10: README and Requirements.txt
-
15.11: Exercise
18:
Bonus Medical Data Extraction Project: Prescription Document
10 Lectures
-
18.1: Technical Architecture of the Project
Free -
18.2: Installation of Necessary Libraries
-
18.3: Extract text from a pdf document
-
18.4: Thresholding in OpenCV
-
18.5: Regular Expressions or Regex
-
18.6: Regex Exercise
-
18.7: Python class for prescription
-
18.8: Code Refactoring
-
18.9: Unit Tests using pytest
-
18.10: I Need a Favour
Start Applying for Jobs
00h:48m:46s on-demand video
|
7 Lectures
Interview Preparation / Job Assistance
05h:06m:32s on-demand video
|
17 Lectures
3:
Data Analyst Mock Interviews
14 Lectures
-
3.1: Naveen gets an Interview call
-
3.2: Think like a Hiring Manager
-
3.3: Introducing Yourself
-
3.4: Answering Questions on projects
-
3.5: SQL Questions
-
3.6: Excel Questions
-
3.7: Power BI Questions
-
3.8: Presenting Insights
-
3.9: Scenario Based Questions
-
3.10: Behavioral Questions
-
3.11: Asking Questions to Hiring Managers
-
3.12: Hiring Managers Discussion
-
3.13: Knowledge Check
-
3.14: Checkpoint
Virtual Internship
00h:13m:46s on-demand video
|
8 Lectures
2:
Week 1
22 Lectures
-
2.1: Welcome Note
-
2.2: Your Onboarding Letter
-
2.3: Welcome Note From Your Manager
-
2.4: Let's dive right into Week 1!
-
2.5: Getting Help From Your Seniors / Fellow Team Members
-
2.6: Your First Task
-
2.7: Incoming Task Email 1
-
2.8: Have you completed this task?
-
2.9: Quality Check 1
-
2.10: Quality Check 2
-
2.11: Quality Check 3
-
2.12: Quality Check 4
-
2.13: Congratulations you have completed the first task of your internship.
-
2.14: Incoming Task Email 2
-
2.15: Have you completed this task?
-
2.16: Quality Check
-
2.17: Congratulations you have completed 2 tasks in a row!
-
2.18: You Need Scrum Training
-
2.19: Incoming Task Email 3
-
2.20: Have you completed the assigned task?
-
2.21: Scrum Knowledge Check
-
2.22: Congratulations you have completed week 1 Successfully.
3:
Week 2
33 Lectures
-
3.1: Let's dive right into Week 2!
-
3.2: Create This Variance Report
-
3.3: Incoming Task Email 1
-
3.4: Have you completed the assigned task?
-
3.5: Quality Check 1
-
3.6: Quality Check 2
-
3.7: Quality Check 3
-
3.8: Congratulations on finishing this task!
-
3.9: Incoming Task Email 2
-
3.10: Have you completed the assigned task?
-
3.11: Quality Check 1
-
3.12: Quality Check 2
-
3.13: Quality Check 3
-
3.14: Quality Check 4
-
3.15: Quality Check 5
-
3.16: Quality Check 6
-
3.17: Quality Check 7
-
3.18: Quality Check 8
-
3.19: Quality Check 9
-
3.20: Congratulations on successfully completing the task!
-
3.21: Incoming Task Email 3
-
3.22: Have you completed the assigned task?
-
3.23: Quality Check 1
-
3.24: Quality Check 2
-
3.25: Quality Check 3
-
3.26: Quality Check 4
-
3.27: Quality Check 5
-
3.28: You did an amazing job completing the task.
-
3.29: Critical Presentation Deck
-
3.30: Incoming Task Email 4
-
3.31: Have you completed the assigned task?
-
3.32: Presentation Submission
-
3.33: Congratulations
4:
Week 3 & 4
19 Lectures
-
4.1: Let's dive right into the Final 2 Weeks !
-
4.2: Can You Handle This Insurance Project?
-
4.3: Incoming Task Email: Feature List
-
4.4: Please don't share datasets
-
4.5: Have you completed the feature list?
-
4.6: Download Benchmark Feature List
-
4.7: Quality Check
-
4.8: Don’t Forget to Send A Mock Up to Client
-
4.9: Have you completed the mock up?
-
4.10: Incoming Task
-
4.11: Response from Client
-
4.12: Quality Check
-
4.13: Incoming Task Email: Dashboard Creation
-
4.14: Have you completed the dashboard?
-
4.15: Submission Checklist
-
4.16: Please don't share Datasets
-
4.17: Dashboard Submission
-
4.18: End Note
-
4.19: Get Your Letter Of Completion
Tableau Mini
04h:34m:44s on-demand video
|
23 Lectures
Microsoft Fabric Mini: For Data Analysts
01h:52m:13s on-demand video
|
14 Lectures
DA 2.0: The AI Enabled Data Analyst
04h:47m:25s on-demand video
|
35 Lectures
3:
Machine Learning/ AI Project Lifecycle
11 Lectures
-
3.1: 10 Stages of AI Project Lifecycle
-
3.2: Requirements and Scope of Work (SOW)
-
3.3: Data Collection
-
3.4: Data Preparation & Exploratory Data Analysis
-
3.5: Feature Engineering
-
3.6: Model Selection & Training
-
3.7: Model Evaluation Metrics (Accuracy, Prediction, Recall & F1 Score)
-
3.8: Model Evaluation Metrics: When to use which Metric?
-
3.9: Model Fine Tuning
-
3.10: Model Deployment
-
3.11: Deployment & Monitoring Using ML Ops
Virtual Internship 2
00h:11m:04s on-demand video
|
9 Lectures
2:
Week 1
27 Lectures
-
2.1: Welcome Note
-
2.2: Your Onboarding Letter
-
2.3: Welcome Note From Your Manager
-
2.4: Let's dive right into Week 1!
-
2.5: Getting Help From Your Seniors / Fellow Team Members
-
2.6: Your First Task
-
2.7: Incoming Task Email 1
-
2.8: Have you completed this task?
-
2.9: Quality Check 1
-
2.10: Quality Check 2
-
2.11: Quality Check 3
-
2.12: Quality Check 4
-
2.13: Congratulations you have completed the first task of your internship.
-
2.14: Python Script Task
-
2.15: Incoming Task Email 2
-
2.16: Have you completed this task?
-
2.17: Quality Check 1
-
2.18: Quality Check 2
-
2.19: Quality Check 3
-
2.20: Quality Check 4
-
2.21: Quality Check 5
-
2.22: Congratulations you have completed 2 tasks in a row!
-
2.23: You need Kanban Training
-
2.24: Incoming Task Email 3
-
2.25: Have you completed the assigned task?
-
2.26: Kanban Knowledge Check
-
2.27: Congratulations you have completed week 1 Successfully.
3:
Week 2
11 Lectures
-
3.1: Let's dive right into Week 2!
-
3.2: Rhonda MVP Project - Your First Power BI Task
-
3.3: Incoming Task Email 1
-
3.4: Have you completed the assigned task?
-
3.5: Quality Check - 1
-
3.6: Quality Check - 2
-
3.7: Designing and Enhancing a Dashboard
-
3.8: Create a Mock-up for the Client
-
3.9: Incoming Task Email: Dashboard Creation
-
3.10: Have you completed the dashboard?
-
3.11: Congratulations
4:
Week 3 & 4
14 Lectures
-
4.1: Let's dive right into the Final 2 Weeks !
-
4.2: Can you help our Marketing Team?
-
4.3: Incoming Task Email: Netflix Analysis
-
4.4: Have you completed the analysis?
-
4.5: Quality Check - 1
-
4.6: Quality Check - 2
-
4.7: Write a mail to the Social Media Analytics Team
-
4.8: Response from the Social Media Analytics Team
-
4.9: Appreciation & New Project Task
-
4.10: Incoming Task Email: Tech Instagram Influencer Analysis
-
4.11: Have you completed the analysis?
-
4.12: Presentation submission
-
4.13: End Note
-
4.14: Get Your Letter Of Completion
Unguided Projects
00h:01m:39s on-demand video
|
1 Lectures
Supplementary Learning
01h:07m:59s on-demand video
|
8 Lectures
5:
Power BI Scenarios
26 Lectures
-
5.1: Scenario - 1
-
5.2: Quality Checks
-
5.3: Scenario - 2
-
5.4: Quality Checks
-
5.5: Scenario - 3
-
5.6: Quality Checks
-
5.7: Scenario - 4
-
5.8: Quality Checks
-
5.9: Scenario - 5
-
5.10: Quality Checks
-
5.11: Scenario - 6
-
5.12: Quality Checks
-
5.13: Scenario - 7
-
5.14: Quality Checks
-
5.15: Scenario - 8
-
5.16: Quality Checks
-
5.17: Scenario - 9
-
5.18: Quality Checks
-
5.19: Scenario - 10
-
5.20: Quality Checks
-
5.21: Scenario - 11
-
5.22: Quality Checks
-
5.23: Scenario - 12
-
5.24: Quality Checks
-
5.25: Scenario - 13
-
5.26: Quality Checks
Live Webinar
30h:18m:35s on-demand video
|
22 Lectures
2:
Career Development Session
5 Lectures
-
2.1: Beginners Guide to Job Seeking - Sep 23
-
2.2: 6 Free Internet Tools to Get an Interview Call - Oct 23
-
2.3: Smart Job Assistance Portal & Expert Resume Insights
-
2.4: The Secret Behind Resumes and Portfolios That Landed Jobs: Decode with your Talent Manager
-
2.5: Strategic Job Search with Google, LinkedIn and Naukri - 22nd November
4:
Expert Webinars
9 Lectures
-
4.1: Transitioning from Non-Tech to Data Analytics - Journey and Tips by Shail Sahu
-
4.2: PL-300 Certification: What You Need to Know & How to Prepare - Anmol Malviya
-
4.3: How to Approach Scenario-Based Questions and Guesstimates in the Interviews - Shashank Singh
-
4.4: Tips and Tricks to Approach Data Analyst Interviews - Gaurav Agrawal
-
4.5: How I would prepare for Data Analyst Interviews If I had to start over - Munna Das
-
4.6: Key Lessons and Interview Tips from My Journey as a Data Analyst - Bharath Kumar G
-
4.7: My Life as a Data Analyst at Ford Motors- Raghavan P
-
4.8: Data Analytics Freelancing Essentials - Santhanalakshmi Ponnurasan
-
4.9: How to differentiate your work - Ashish Babaria
Data Engineering Basics for Data Analysts
04h:26m:45s on-demand video
|
46 Lectures
AI Automation for Data Professionals
03h:48m:37s on-demand video
|
19 Lectures
Practice Arena
1:
Scenario Based - Interview Questions
SQL
29
Questions
-
1.1: Future Purchase Prediction Date
-
1.2: Customer Purchase Behavior Analysis
-
1.3: Travel Booking Analysis
-
1.4: Top 3 Customer Revenue Analysis
-
1.5: Cricket Match Scheduling
-
1.6: Travel Booking and Revenue Analysis
-
1.7: Customer Revenue Analysis
-
1.8: Monthly Transaction Analysis for Fraud Detection
-
1.9: Fitness MemberShip
-
1.10: Travel Pattern Analysis
-
1.11: Customer Loyalty Analysis
-
1.12: Product Sales by Store in Bangalore
-
1.13: Analyzing Revenue from High-Demand, Premium Products
-
1.14: Calculating Total Revenue by Product Category
-
1.15: Identifying Unsold Products in Inventory
-
1.16: Analyzing Above-Average Salaries by Department
-
1.17: Identifying Top Customers by Average Purchase Amount
-
1.18: Analyzing Monthly Customer Retention Rates for Q2 2024
-
1.19: Identifying Store Leaders: Most Popular Products by Sales
-
1.20: Identifying APAC Markets for Atliq Exclusive
-
1.21: Sorting Unique Product Counts by Segment at Atliq Exclusive
-
1.22: Optimizing Costs: High and Low Manufacturing Costs at Atliq Exclusive
-
1.23: 2020 Quarterly Sales Trends at Atliq Exclusive
-
1.24: Top 3 Products by Sold Quantities Across Divisions, FY 2021
-
1.25: 2021 Sales Channel Performance at Atliq Exclusive
-
1.26: Segment Growth in Unique Products: 2020-2021 Analysis
-
1.27: Monthly Gross Sales Analysis for Atliq Exclusive Customer
-
1.28: Yearly Product Diversification Increase: 2020-2021
-
1.29: Top 5 Indian Customers by Pre-Invoice Discounts, 2021
2:
MySQL Course Exercises
SQL
24
Questions
-
2.1: Print All Marvel Studios Movies with Titles and Release Year
-
2.2: Select All THOR Movies by Release Year
-
2.3: Select All Movies Not from Marvel Studios
-
2.4: Retrieving Movies with Their Language Names
-
2.5: Retrieve Hollywood Movies with High Profit After 2000
-
2.6: Count Movies Released Between 2015 and 2022
-
2.7: Determine the Range of Movie Release Years
-
2.8: Count Movies Released Annually in Descending Order
-
2.9: Calculate Profit Percentage for All Movies
-
2.10: Retrieve Telugu Movies
-
2.11: Count Movies by Language
-
2.12: Generate a Report of Hindi Movies Sorted by Revenue
-
2.13: Retrieve Movies with Minimum and Maximum Release Year
-
2.14: Retrieve Movies with IMDb Rating Above Average
-
2.15: Select Movies by Marvel Studios and Hombale Films
-
2.16: List Movies by Latest Release Year
-
2.17: All Movies Released After 2020 with Rating Greater Than 8
-
2.18: All Movies Released After 2020
-
2.19: All Movies Released in 2022
-
2.20: Order Movies by Release Year
-
2.21: List Distinct Bollywood Studios
-
2.22: Release Year of The Godfather
-
2.23: Search for Avengers Movies
-
2.24: List Marvel Studios Movies
Welcome to The Bootcamp Experience
00h:45m:43s on-demand video
|
15
Lectures
00h:45m:43s on-demand video
|
15 Lectures
1:
Welcome to The Bootcamp Experience
15 Lectures
-
1.1: Why Should You Become a Data Analyst?
Free -
1.2: How Do I Know If The Data Analyst Role Is Suitable For Me?
Free -
1.3: Is Computer Science Degree / Young Age / Relevant Work Experience Mandatory?
Free -
1.4: What Kind of Job Assistance Do You Provide?
Free -
1.5: How Do I Get Doubt-Clearing Support? (Discord)
-
1.6: How Much Time Do I Need to Complete The Bootcamp?
Free -
1.7: Do I get a Real Internship Certificate After Completing a Virtual Internship?
Free -
1.8: Do the Creators of This Bootcamp Have Real Industry Experience?
Free -
1.9: How Many Business Projects Will I Complete in This Bootcamp?
Free -
1.10: How can I Trust That This Bootcamp Has the Best Content on Planet Earth?
Free -
1.11: What Domain and Functional Knowledge Will You Build and How?
Free -
1.12: What are the Soft Skills I Will Acquire By the End of Bootcamp?
Free -
1.13: Bootcamp Syllabus Overview
Free -
1.14: How Will I Be Informed About The Monthly Live Webinars?
Free -
1.15: System Requirements
Excel: Mother of Business Intelligence
09h:05m:26s on-demand video
|
70
Lectures
09h:05m:26s on-demand video
|
70 Lectures
2:
Excel Basics: Getting Started
13 Lectures
-
2.1: Peter Pandey’s Journey and Need to Learn Excel
-
2.2: Installing Excel: Windows / Mac
Free -
2.3: Getting Familiar With Excel
Free -
2.4: Getting More Familiar With Excel
Free -
2.5: Introduction to Formulas
Free -
2.6: Formula Behavior
Free -
2.7: Introduction to Tables
Free -
2.8: Introduction to Charts
Free -
2.9: Other Essential Features
Free -
2.10: Peter Gets His First Assignment From His Senior
Free -
2.11: Practice Exercise: Personal Expense Tracker
-
2.12: Quiz
-
2.13: Chapter Summary
4:
Excel Basics: Applying Business Maths & Statistics
9 Lectures
-
4.1: Basic Maths to Business Metrics (Bollywood movies revenue avg)
-
4.2: Commonly Used Business Metrics (P&L)
-
4.3: Commonly Used Statistic Concepts (Mean, Median, Mode)
-
4.4: Commonly Used Statistic Concepts (Variance, Standard Deviation)
-
4.5: Commonly Used Statistic Concepts (Correlation)
-
4.6: Peter Gets to Solve a Real Time Problem
-
4.7: Practice Exercise
-
4.8: Quiz
-
4.9: Chapter Summary
6:
Excel Basics+: Creating Business Reports Using Pivot Table & Power Pivot
14 Lectures
-
6.1: Pivot Table Introduction: Apple Product Sales
-
6.2: Pivot Table For Movie Analytics
-
6.3: Creating a Report Using Pivot Table
-
6.4: Pivot Table Options & Formatting
-
6.5: Using Power Pivot & DAX For Powerful Business Reports
-
6.6: Adding Targets Using Data Modelling in Power Pivot
-
6.7: Breaking Down Complex Problems: Thinking Process of a Highly Paid Data Analyst
-
6.8: More Business Metrics and Conditional Formatting
-
6.9: VBA Basics & How Much VBA You Should Learn
-
6.10: Peter Practices On His Own
-
6.11: Practice Exercise
-
6.12: Quiz
-
6.13: I Need a Favour
-
6.14: Chapter Summary
8:
Excel Advanced: Sales Analytics
12 Lectures
-
8.1: ETL (Extract, Transform and Load Data) in Excel I
-
8.2: ETL (Extract, Transform and Load Data) in Excel II
-
8.3: Business Report: Solution Design Thought Process
-
8.4: Creating Connections Among Tables Using Data Modelling
-
8.5: Adding a Date Table Using Power Query
-
8.6: Functional Knowledge: Sales
-
8.7: Sales Analytics: Creating Customer Performance Report
-
8.8: User Empathetic Report Design
-
8.9: Sales Analytics: Creating Market Performance vs Targets Reported
-
8.10: Practice Exercise
-
8.11: Quiz
-
8.12: Chapter Summary
9:
Excel Advanced: Finance Analytics
11 Lectures
-
9.1: Understanding P & L
-
9.2: Functional Knowledge: Finance
-
9.3: Adding the Finance Data to Data Model
-
9.4: Finance Analytics: P & L by Year Report
-
9.5: Fine Tuning P & L By Year Report
-
9.6: Adding Months & Quarters in Data Model
-
9.7: Finance Analytics: P & L by Months Report
-
9.8: Fine Tuning P & L By Month Report
-
9.9: Practice Exercise
-
9.10: Quiz
-
9.11: Chapter Summary
10:
Excel Advanced: Real-Time Business Applications
9 Lectures
-
10.1: Wanda’s Challenge With Prioritizing Projects
-
10.2: Peter & Tony Creates a Project Priority Matrix
-
10.3: Mentor Talk: Being A Problem Solver
-
10.4: Practice Exercise
-
10.5: Bruce Haryali Needs Help With Excel
-
10.6: Peter & Tony Creates a Scenario Planning Tool
-
10.7: Mentor Talk: Growth Zone
-
10.8: Practice Exercise
-
10.9: Quiz
Start Building Your Online Credibility
00h:26m:24s on-demand video
|
6
Lectures
00h:26m:24s on-demand video
|
6 Lectures
Get Job Ready: Power BI Data Analytics for All Levels 3.0
19h:10m:41s on-demand video
|
137
Lectures
19h:10m:41s on-demand video
|
137 Lectures
2:
Power BI Basics: Getting Started
13 Lectures
-
2.1: Install Power BI
-
2.2: Power BI: Tool Introduction
-
2.3: Power Query: Intro & Column Transformations
-
2.4: Power Query: Merging and Appending
-
2.5: Power Query: Best Practices
-
2.6: Introduction to DAX
-
2.7: Introduction to DAX - II
-
2.8: Introduction to Data Modeling
-
2.9: Introduction to Creating Visuals
-
2.10: Tony asks Peter to Fix Data Holes
-
2.11: Practice Exercise
-
2.12: Chapter Summary
-
2.13: Quiz
3:
Project Planning and Scoping
9 Lectures
-
3.1: Problem Statement
Free -
3.2: The Email that Started this Project
Free -
3.3: Project Kick-off Meeting
Free -
3.4: Learn how a ‘Project Charter’ is Used in Companies
-
3.5: Project Kick-off: Session Debrief
-
3.6: Senior Data Analyst Sets Up the Next Steps with Junior Data Analyst
-
3.7: Simplified: Profit and Loss Statement
-
3.8: Chapter Summary
-
3.9: Quiz
4:
Power BI Basics: Data collection, Exploration & Validation
10 Lectures
-
4.1: Simplified: Data Warehouse, OLTP vs OLAP, Data Catalog
Free -
4.2: Install MySQL and Import Data
-
4.3: Simplified: Data Exploration Using SQL, Star Schema, Fact vs Dimension Tables
Free -
4.4: Load and connect data with MySQL
-
4.5: Create a Date Dimension Table
-
4.6: Validate Data against Benchmark Numbers
-
4.7: Tony’s Valuable Advise to Peter
-
4.8: Practice Exercise
-
4.9: Chapter Summary
-
4.10: Quiz
7:
Power BI Advanced: Data Modeling & Calculated Columns
11 Lectures
-
7.1: Power Query or DAX for Generating Calculated Columns?
Free -
7.2: Data Modelling: Star and Snowflake Schema
Free -
7.3: Data Modeling: Connect Dimensions with Fact Tables
-
7.4: Simplified: Why Do We Need Dimension Tables?
-
7.5: Mentor Talk: Congratulations! You are Levelling Up!
-
7.6: Create Calculated Columns Using DAX
-
7.7: Easy Way to Verify Your Numbers in Power BI
-
7.8: Assignment: Optimize Report and Reduce File Size by 25 %
Free -
7.9: I Need a Favour
-
7.10: Chapter Summary
-
7.11: Quiz
8:
Power BI Advanced: Build Finance View
15 Lectures
-
8.1: Finance View: Prepare a List of Metrics
-
8.2: Simplified: Calculate Function & Filter Context
-
8.3: Finance View: Creating Metrics
-
8.4: Finance View: Create P&L Table Structure
-
8.5: Finance View: Create Last Year (LY) Column
-
8.6: Finance View: Build an Ultimate DAX Measure for P & L Table Structure - I
-
8.7: Finance View: Build an Ultimate DAX Measure for P & L Table Structure - II
-
8.8: Finance View: Create ‘Quarters’ & ‘YTD/YTG’ Slicers
-
8.9: Mentor Talk: Figuring Out Solutions
-
8.10: Finance View: Create a Line chart to Show Performance Over Time
-
8.11: Finance View: Build Top Product, Market & Region Visuals
-
8.12: Intermediate Review: I Met Product Owner Nick and He Gave this Feedback!
Free -
8.13: Finance View: Add Net Profit
-
8.14: Chapter Summary
-
8.15: Quiz
9:
Power BI Advanced: Build Sales, Marketing & Supply Chain View
10 Lectures
-
9.1: Review Sales View Mockup
-
9.2: Sales View: Build Top Customers & Performance Matrix Visuals
-
9.3: Sales View: Build Product Performance & Unit Economics Visuals
-
9.4: Build Marketing View
-
9.5: Simplified: Supply Chain Basics
-
9.6: Supply Chain View: Review Mock Up
-
9.7: Supply Chain View: Build Key Measures
-
9.8: Supply Chain View: Build Visuals
-
9.9: Chapter Summary
-
9.10: Quiz
10:
Power BI Advanced: Designing an Effective Dashboard
9 Lectures
-
10.1: Simplified: Dashboard vs Report
-
10.2: 15 Design Rules for an Effective Dashboard
-
10.3: Finalize Page Layout Design
-
10.4: Create Home Page
-
10.5: Design Finance Dashboard
-
10.6: Add Key Elements to Finance Dashboard
-
10.7: Copy the Design to Sales, Marketing & Supply Chain Dashboard
-
10.8: Chapter Summary
-
10.9: Quiz
12:
Stakeholder review & Feedback implementation
16 Lectures
-
12.1: Stakeholder Analysis and its Significance
-
12.2: Peter Recalls the Stakeholder Mapping Meeting
Free -
12.3: Stakeholder Review Meeting: How did it Go?
Free -
12.4: This is the secret to be ‘Job Ready’!
-
12.5: Practice Exercise: Quick Fixes
-
12.6: Quick Fix: Chg% formula
-
12.7: Practice Exercise: Implementing Dynamic Benchmark
-
12.8: Practice Exercise: Adding Dynamic Slicer to Filter Visual
-
12.9: Practice Exercise: Create a Toggle Button to Switch between Two Visuals
-
12.10: Practice Exercise: Create a Tool Tip to Show Trend
-
12.11: Learn: Adding Market Share Data
-
12.12: Practice Exercise: Create an Executive Dashboard
-
12.13: Learn: Performance Optimization
-
12.14: Learn: Fix Data Quality Issues
-
12.15: Chapter Summary
-
12.16: Quiz
13:
Deploying the Solution: Power BI Service
7 Lectures
-
13.1: Power BI Service Overview, Report Sharing, and Apps
-
13.2: How to Set Up Automatic Data Refresh: My SQL
-
13.3: How to Set Up Automatic Data Refresh: Excel
-
13.4: Simplified: Collaboration, Bookmarks, and Insights in Power BI Service
-
13.5: Driving the Extra Mile: Documentation and Maintenance
-
13.6: Chapter Summary
-
13.7: Quiz
14:
Practice Exercise Solutions
11 Lectures
-
14.1: Solution: Quick Fixes
-
14.2: Solution: Implementing Dynamic Targets (Add Targets)
-
14.3: Solution: Implementing Dynamic Targets (Create a dynamic switch between Targets and LY)
-
14.4: Solution: Implementing Dynamic Targets (P & L visuals to compare Target or LY based on selection)
-
14.5: Solution: Adding Dynamic Slicer to Filter Visual
-
14.6: Solution: Create a Toggle Button to Switch between Two Visuals
-
14.7: Solution: Create a Tool Tip to Show Trend
-
14.8: Solution: Create an Executive Dashboard (KPI Visuals)
-
14.9: Solution: Create an Executive Dashboard (Key Insights by Subzone )
-
14.10: Solution: Create an Executive Dashboard (Market Share Visual & Conditional Formatting)
-
14.11: Solution: Create an Executive Dashboard (Final Enhancements)
16:
PBI Monthly Update Tasks
16 Lectures
-
16.1: Intro
-
16.2: Feature Updates Task -1
-
16.3: Solution: Task - 1
-
16.4: Feature Updates Task- 2
-
16.5: Solution: Task - 2
-
16.6: Feature Updates Task - 3
-
16.7: Solution: Task - 3
-
16.8: Feature Updates Task - 4
-
16.9: Solution: Task - 4
-
16.10: Feature Updates Task - 5
-
16.11: Solution: Task - 5
-
16.12: Feature Updates Task - 6
-
16.13: Solution: Task - 6
-
16.14: Feature Updates Task - 7
-
16.15: Solution: Task - 7
-
16.16: Feature Updates Task - 8
Building Online Credibility, Portfolio Projects & ATS Resume
03h:59m:49s on-demand video
|
23
Lectures
03h:59m:49s on-demand video
|
23 Lectures
2:
Build Your Resume, Now!
8 Lectures
-
2.1: What is ATS and Why it is Important?
-
2.2: Follow These Guidelines to Build an Amazing Resume
-
2.3: Improve the ATS Score of Your Resume
-
2.4: Customize Resume as Per Job Posting
-
2.5: Career Transition: Sample Experience Sections
-
2.6: Meet Naveen, He is applying for a Job Like You!
-
2.7: Knowledge Check
-
2.8: Checkpoint
5:
Power BI Project(s) for Your Portfolio!
7 Lectures
-
5.1: Get a Shareable Public Link For Your Power BI Project
-
5.2: Share Your Power BI Project with Potential Recruiters
-
5.3: Differentiate Your Work with New Design
-
5.4: How to differentiate your work - Expert Webinar
-
5.5: One More Power BI Project for Your Portfolio
-
5.6: Check Your Work With this Guided Project
-
5.7: One Step Closer to Your Dream Portfolio
SQL Beginner to Advanced For Data Professionals
11h:15m:16s on-demand video
|
84
Lectures
11h:15m:16s on-demand video
|
84 Lectures
2:
SQL Basics: Data Retrieval - Single Table
15 Lectures
-
2.1: Install MySQL: Windows
Free -
2.2: Install MySQL: Linux, Mac
Free -
2.3: Import Movies Dataset in MySQL
Free -
2.4: Retrieve Data Using Text Query (SELECT, WHERE, DISTINCT, LIKE)
Free -
2.5: Exercise - Retrieve Data Using Text Query (SELECT, WHERE, DISTINCT, LIKE)
Free -
2.6: Retrieve Data Using Numeric Query (BETWEEN, IN, ORDER BY, LIMIT, OFFSET)
Free -
2.7: Exercise - Retrieve Data Using Numeric Query (BETWEEN, IN, ORDER BY, LIMIT, OFFSET)
Free -
2.8: Summary Analytics (MIN, MAX, AVG, GROUP BY)
Free -
2.9: Exercise - Summary Analytics (MIN, MAX, AVG, GROUP BY)
Free -
2.10: HAVING Clause
Free -
2.11: Calculated Columns (IF, CASE, YEAR, CURYEAR)
Free -
2.12: Exercise - Calculated Columns (IF, CASE, YEAR, CURYEAR)
Free -
2.13: The Data God’s Blessing
Free -
2.14: Quiz
-
2.15: Chapter Summary
5:
SQL Basics: Database Creation & Updates
18 Lectures
-
5.1: Database Normalization and Data Integrity
-
5.2: Entity Relationship Diagram (ERD)
-
5.3: Mentor Talk: Art of Googling
-
5.4: Data Types: Numeric (INT, DECIMAL, FLOAT, DOUBLE)
-
5.5: Data Types: String (VARCHAR, CHAR, ENUM)
-
5.6: Data Types: Date, Time (DATETIME, DATE, TIME, YEAR, TIMESTAMP)
-
5.7: Data Types: JSON, Spatial (JSON, GEOMETRY)
-
5.8: Luck Favors the LinkedIn Post
-
5.9: Primary key
-
5.10: Foreign Key
-
5.11: Create a Database From an Entity Relationship Diagram - ERD
-
5.12: Import Data From a CSV File Into a Database
-
5.13: Insert Statement
-
5.14: Update and Delete
-
5.15: I Need a Favour
-
5.16: Expect the Unexpected: The Intermission Scene
-
5.17: Quiz
-
5.18: Chapter Summary
6:
AtliQ Hardware & Problem Statement
9 Lectures
-
6.1: The Rise of Databases at AtliQ
Free -
6.2: Relational vs No-SQL Database
-
6.3: AtliQ Hardware’s Business Model
-
6.4: Profit & Loss Statement
-
6.5: ETL, Data Warehouse, OLAP vs OLTP, Data Catalog
-
6.6: Fact vs Dimension Table, Star vs Snowflake Schema, Data Import
-
6.7: Simplified: What is Kanban?
-
6.8: Quiz
-
6.9: Chapter Summary
7:
SQL Advanced: Finance Analytics
10 Lectures
-
7.1: Backlog Grooming Meeting: Gross Sales Report
-
7.2: User-Defined SQL Functions
-
7.3: Exercise: User-Defined SQL Functions
-
7.4: Gross Sales Report: Monthly Product Transactions
-
7.5: Gross Sales Report: Total Sales Amount
-
7.6: Exercise: Yearly Sales Report
-
7.7: Stored Procedures: Monthly Gross Sales Report
-
7.8: Stored Procedure: Market Badge
-
7.9: Benefits of Stored Procedures
-
7.10: Quiz
8:
SQL Advanced: Top Customers, Products, Markets
16 Lectures
-
8.1: Problem Statement and Pre-Invoice Discount Report
-
8.2: Performance Improvement # 1
-
8.3: Performance Improvement # 2
-
8.4: Database Views: Introduction
-
8.5: Database Views: Post Invoice Discount, Net Sales
-
8.6: Exercise: Database Views
-
8.7: Top Markets and Customers
-
8.8: Exercise: Top Products
-
8.9: The Two Most Important Skills for the Data Analyst
-
8.10: Window Functions: OVER Clause
-
8.11: Window Functions: Using it in a Task
-
8.12: Exercise: Window Functions: OVER Clause
-
8.13: Window Functions: ROW_NUMBER, RANK, DENSE_RANK
-
8.14: Exercise: Window Functions: ROW_NUMBER, RANK, DENSE_RANK
-
8.15: 5 Ways SQL is Used in the Industry
-
8.16: Quiz
9:
SQL Advanced: Supply Chain Analytics
13 Lectures
-
9.1: Supply Chain Basics : Simplified
-
9.2: Problem Statement
-
9.3: Create a Helper Table
-
9.4: Database Triggers
-
9.5: Database Events
-
9.6: Temporary Tables & Forecast Accuracy Report
-
9.7: Exercise: CTE, Temporary Tables
-
9.8: Subquery vs CTE vs Views vs Temporary Table
-
9.9: User Accounts and Privileges
-
9.10: Database Indexes: Overview
-
9.11: Database Indexes: Composite Index
-
9.12: Database Indexes: Index Types
-
9.13: Quiz
Python: Beginner to Advanced For Data Professionals
16h:57m:31s on-demand video
|
108
Lectures
16h:57m:31s on-demand video
|
108 Lectures
6:
Python Basics: Functions, Dictionaries, Tuples and File Handling
9 Lectures
-
6.1: Functions
-
6.2: Dictionary and Tuples
-
6.3: Modules and Pip
-
6.4: File Handling
-
6.5: Quiz: Functions, Dictionaries, Tuples and File Handling
-
6.6: Peter’s Request to Tony
-
6.7: Exercise: Functions, Dictionaries, Tuples and File Handling
-
6.8: Two Deadly Viruses Infecting Learners
-
6.9: Chapter Summary
15:
Project 2: Expense Tracking System
11 Lectures
-
15.1: Problem Statement & Tech Architecture
-
15.2: Database CRUD Operations
-
15.3: Automated Tests Setup for CRUD
-
15.4: Expense Management: Backend (FastAPI)
-
15.5: Expense Management: Logging
-
15.6: Streamlit Introduction
-
15.7: Expense Management: Frontend (Streamlit)
-
15.8: Analytics: Backend (FastAPI)
-
15.9: Analytics: Frontend (Streamlit)
-
15.10: README and Requirements.txt
-
15.11: Exercise
18:
Bonus Medical Data Extraction Project: Prescription Document
10 Lectures
-
18.1: Technical Architecture of the Project
Free -
18.2: Installation of Necessary Libraries
-
18.3: Extract text from a pdf document
-
18.4: Thresholding in OpenCV
-
18.5: Regular Expressions or Regex
-
18.6: Regex Exercise
-
18.7: Python class for prescription
-
18.8: Code Refactoring
-
18.9: Unit Tests using pytest
-
18.10: I Need a Favour
Start Applying for Jobs
00h:48m:46s on-demand video
|
7
Lectures
00h:48m:46s on-demand video
|
7 Lectures
Interview Preparation / Job Assistance
05h:06m:32s on-demand video
|
17
Lectures
05h:06m:32s on-demand video
|
17 Lectures
3:
Data Analyst Mock Interviews
14 Lectures
-
3.1: Naveen gets an Interview call
-
3.2: Think like a Hiring Manager
-
3.3: Introducing Yourself
-
3.4: Answering Questions on projects
-
3.5: SQL Questions
-
3.6: Excel Questions
-
3.7: Power BI Questions
-
3.8: Presenting Insights
-
3.9: Scenario Based Questions
-
3.10: Behavioral Questions
-
3.11: Asking Questions to Hiring Managers
-
3.12: Hiring Managers Discussion
-
3.13: Knowledge Check
-
3.14: Checkpoint
Virtual Internship
00h:13m:46s on-demand video
|
8
Lectures
00h:13m:46s on-demand video
|
8 Lectures
2:
Week 1
22 Lectures
-
2.1: Welcome Note
-
2.2: Your Onboarding Letter
-
2.3: Welcome Note From Your Manager
-
2.4: Let's dive right into Week 1!
-
2.5: Getting Help From Your Seniors / Fellow Team Members
-
2.6: Your First Task
-
2.7: Incoming Task Email 1
-
2.8: Have you completed this task?
-
2.9: Quality Check 1
-
2.10: Quality Check 2
-
2.11: Quality Check 3
-
2.12: Quality Check 4
-
2.13: Congratulations you have completed the first task of your internship.
-
2.14: Incoming Task Email 2
-
2.15: Have you completed this task?
-
2.16: Quality Check
-
2.17: Congratulations you have completed 2 tasks in a row!
-
2.18: You Need Scrum Training
-
2.19: Incoming Task Email 3
-
2.20: Have you completed the assigned task?
-
2.21: Scrum Knowledge Check
-
2.22: Congratulations you have completed week 1 Successfully.
3:
Week 2
33 Lectures
-
3.1: Let's dive right into Week 2!
-
3.2: Create This Variance Report
-
3.3: Incoming Task Email 1
-
3.4: Have you completed the assigned task?
-
3.5: Quality Check 1
-
3.6: Quality Check 2
-
3.7: Quality Check 3
-
3.8: Congratulations on finishing this task!
-
3.9: Incoming Task Email 2
-
3.10: Have you completed the assigned task?
-
3.11: Quality Check 1
-
3.12: Quality Check 2
-
3.13: Quality Check 3
-
3.14: Quality Check 4
-
3.15: Quality Check 5
-
3.16: Quality Check 6
-
3.17: Quality Check 7
-
3.18: Quality Check 8
-
3.19: Quality Check 9
-
3.20: Congratulations on successfully completing the task!
-
3.21: Incoming Task Email 3
-
3.22: Have you completed the assigned task?
-
3.23: Quality Check 1
-
3.24: Quality Check 2
-
3.25: Quality Check 3
-
3.26: Quality Check 4
-
3.27: Quality Check 5
-
3.28: You did an amazing job completing the task.
-
3.29: Critical Presentation Deck
-
3.30: Incoming Task Email 4
-
3.31: Have you completed the assigned task?
-
3.32: Presentation Submission
-
3.33: Congratulations
4:
Week 3 & 4
19 Lectures
-
4.1: Let's dive right into the Final 2 Weeks !
-
4.2: Can You Handle This Insurance Project?
-
4.3: Incoming Task Email: Feature List
-
4.4: Please don't share datasets
-
4.5: Have you completed the feature list?
-
4.6: Download Benchmark Feature List
-
4.7: Quality Check
-
4.8: Don’t Forget to Send A Mock Up to Client
-
4.9: Have you completed the mock up?
-
4.10: Incoming Task
-
4.11: Response from Client
-
4.12: Quality Check
-
4.13: Incoming Task Email: Dashboard Creation
-
4.14: Have you completed the dashboard?
-
4.15: Submission Checklist
-
4.16: Please don't share Datasets
-
4.17: Dashboard Submission
-
4.18: End Note
-
4.19: Get Your Letter Of Completion
Tableau Mini
04h:34m:44s on-demand video
|
23
Lectures
04h:34m:44s on-demand video
|
23 Lectures
Microsoft Fabric Mini: For Data Analysts
01h:52m:13s on-demand video
|
14
Lectures
01h:52m:13s on-demand video
|
14 Lectures
DA 2.0: The AI Enabled Data Analyst
04h:47m:25s on-demand video
|
35
Lectures
04h:47m:25s on-demand video
|
35 Lectures
3:
Machine Learning/ AI Project Lifecycle
11 Lectures
-
3.1: 10 Stages of AI Project Lifecycle
-
3.2: Requirements and Scope of Work (SOW)
-
3.3: Data Collection
-
3.4: Data Preparation & Exploratory Data Analysis
-
3.5: Feature Engineering
-
3.6: Model Selection & Training
-
3.7: Model Evaluation Metrics (Accuracy, Prediction, Recall & F1 Score)
-
3.8: Model Evaluation Metrics: When to use which Metric?
-
3.9: Model Fine Tuning
-
3.10: Model Deployment
-
3.11: Deployment & Monitoring Using ML Ops
Virtual Internship 2
00h:11m:04s on-demand video
|
9
Lectures
00h:11m:04s on-demand video
|
9 Lectures
2:
Week 1
27 Lectures
-
2.1: Welcome Note
-
2.2: Your Onboarding Letter
-
2.3: Welcome Note From Your Manager
-
2.4: Let's dive right into Week 1!
-
2.5: Getting Help From Your Seniors / Fellow Team Members
-
2.6: Your First Task
-
2.7: Incoming Task Email 1
-
2.8: Have you completed this task?
-
2.9: Quality Check 1
-
2.10: Quality Check 2
-
2.11: Quality Check 3
-
2.12: Quality Check 4
-
2.13: Congratulations you have completed the first task of your internship.
-
2.14: Python Script Task
-
2.15: Incoming Task Email 2
-
2.16: Have you completed this task?
-
2.17: Quality Check 1
-
2.18: Quality Check 2
-
2.19: Quality Check 3
-
2.20: Quality Check 4
-
2.21: Quality Check 5
-
2.22: Congratulations you have completed 2 tasks in a row!
-
2.23: You need Kanban Training
-
2.24: Incoming Task Email 3
-
2.25: Have you completed the assigned task?
-
2.26: Kanban Knowledge Check
-
2.27: Congratulations you have completed week 1 Successfully.
3:
Week 2
11 Lectures
-
3.1: Let's dive right into Week 2!
-
3.2: Rhonda MVP Project - Your First Power BI Task
-
3.3: Incoming Task Email 1
-
3.4: Have you completed the assigned task?
-
3.5: Quality Check - 1
-
3.6: Quality Check - 2
-
3.7: Designing and Enhancing a Dashboard
-
3.8: Create a Mock-up for the Client
-
3.9: Incoming Task Email: Dashboard Creation
-
3.10: Have you completed the dashboard?
-
3.11: Congratulations
4:
Week 3 & 4
14 Lectures
-
4.1: Let's dive right into the Final 2 Weeks !
-
4.2: Can you help our Marketing Team?
-
4.3: Incoming Task Email: Netflix Analysis
-
4.4: Have you completed the analysis?
-
4.5: Quality Check - 1
-
4.6: Quality Check - 2
-
4.7: Write a mail to the Social Media Analytics Team
-
4.8: Response from the Social Media Analytics Team
-
4.9: Appreciation & New Project Task
-
4.10: Incoming Task Email: Tech Instagram Influencer Analysis
-
4.11: Have you completed the analysis?
-
4.12: Presentation submission
-
4.13: End Note
-
4.14: Get Your Letter Of Completion
Unguided Projects
00h:01m:39s on-demand video
|
1
Lectures
00h:01m:39s on-demand video
|
1 Lectures
Supplementary Learning
01h:07m:59s on-demand video
|
8
Lectures
01h:07m:59s on-demand video
|
8 Lectures
5:
Power BI Scenarios
26 Lectures
-
5.1: Scenario - 1
-
5.2: Quality Checks
-
5.3: Scenario - 2
-
5.4: Quality Checks
-
5.5: Scenario - 3
-
5.6: Quality Checks
-
5.7: Scenario - 4
-
5.8: Quality Checks
-
5.9: Scenario - 5
-
5.10: Quality Checks
-
5.11: Scenario - 6
-
5.12: Quality Checks
-
5.13: Scenario - 7
-
5.14: Quality Checks
-
5.15: Scenario - 8
-
5.16: Quality Checks
-
5.17: Scenario - 9
-
5.18: Quality Checks
-
5.19: Scenario - 10
-
5.20: Quality Checks
-
5.21: Scenario - 11
-
5.22: Quality Checks
-
5.23: Scenario - 12
-
5.24: Quality Checks
-
5.25: Scenario - 13
-
5.26: Quality Checks
Live Webinar
30h:18m:35s on-demand video
|
22
Lectures
30h:18m:35s on-demand video
|
22 Lectures
2:
Career Development Session
5 Lectures
-
2.1: Beginners Guide to Job Seeking - Sep 23
-
2.2: 6 Free Internet Tools to Get an Interview Call - Oct 23
-
2.3: Smart Job Assistance Portal & Expert Resume Insights
-
2.4: The Secret Behind Resumes and Portfolios That Landed Jobs: Decode with your Talent Manager
-
2.5: Strategic Job Search with Google, LinkedIn and Naukri - 22nd November
4:
Expert Webinars
9 Lectures
-
4.1: Transitioning from Non-Tech to Data Analytics - Journey and Tips by Shail Sahu
-
4.2: PL-300 Certification: What You Need to Know & How to Prepare - Anmol Malviya
-
4.3: How to Approach Scenario-Based Questions and Guesstimates in the Interviews - Shashank Singh
-
4.4: Tips and Tricks to Approach Data Analyst Interviews - Gaurav Agrawal
-
4.5: How I would prepare for Data Analyst Interviews If I had to start over - Munna Das
-
4.6: Key Lessons and Interview Tips from My Journey as a Data Analyst - Bharath Kumar G
-
4.7: My Life as a Data Analyst at Ford Motors- Raghavan P
-
4.8: Data Analytics Freelancing Essentials - Santhanalakshmi Ponnurasan
-
4.9: How to differentiate your work - Ashish Babaria
Data Engineering Basics for Data Analysts
04h:26m:45s on-demand video
|
46
Lectures
04h:26m:45s on-demand video
|
46 Lectures
AI Automation for Data Professionals
03h:48m:37s on-demand video
|
19
Lectures
03h:48m:37s on-demand video
|
19 Lectures
Practice Arena
1:
Scenario Based - Interview Questions
-
1.1: Future Purchase Prediction Date
-
1.2: Customer Purchase Behavior Analysis
-
1.3: Travel Booking Analysis
-
1.4: Top 3 Customer Revenue Analysis
-
1.5: Cricket Match Scheduling
-
1.6: Travel Booking and Revenue Analysis
-
1.7: Customer Revenue Analysis
-
1.8: Monthly Transaction Analysis for Fraud Detection
-
1.9: Fitness MemberShip
-
1.10: Travel Pattern Analysis
-
1.11: Customer Loyalty Analysis
-
1.12: Product Sales by Store in Bangalore
-
1.13: Analyzing Revenue from High-Demand, Premium Products
-
1.14: Calculating Total Revenue by Product Category
-
1.15: Identifying Unsold Products in Inventory
-
1.16: Analyzing Above-Average Salaries by Department
-
1.17: Identifying Top Customers by Average Purchase Amount
-
1.18: Analyzing Monthly Customer Retention Rates for Q2 2024
-
1.19: Identifying Store Leaders: Most Popular Products by Sales
-
1.20: Identifying APAC Markets for Atliq Exclusive
-
1.21: Sorting Unique Product Counts by Segment at Atliq Exclusive
-
1.22: Optimizing Costs: High and Low Manufacturing Costs at Atliq Exclusive
-
1.23: 2020 Quarterly Sales Trends at Atliq Exclusive
-
1.24: Top 3 Products by Sold Quantities Across Divisions, FY 2021
-
1.25: 2021 Sales Channel Performance at Atliq Exclusive
-
1.26: Segment Growth in Unique Products: 2020-2021 Analysis
-
1.27: Monthly Gross Sales Analysis for Atliq Exclusive Customer
-
1.28: Yearly Product Diversification Increase: 2020-2021
-
1.29: Top 5 Indian Customers by Pre-Invoice Discounts, 2021
2:
MySQL Course Exercises
-
2.1: Print All Marvel Studios Movies with Titles and Release Year
-
2.2: Select All THOR Movies by Release Year
-
2.3: Select All Movies Not from Marvel Studios
-
2.4: Retrieving Movies with Their Language Names
-
2.5: Retrieve Hollywood Movies with High Profit After 2000
-
2.6: Count Movies Released Between 2015 and 2022
-
2.7: Determine the Range of Movie Release Years
-
2.8: Count Movies Released Annually in Descending Order
-
2.9: Calculate Profit Percentage for All Movies
-
2.10: Retrieve Telugu Movies
-
2.11: Count Movies by Language
-
2.12: Generate a Report of Hindi Movies Sorted by Revenue
-
2.13: Retrieve Movies with Minimum and Maximum Release Year
-
2.14: Retrieve Movies with IMDb Rating Above Average
-
2.15: Select Movies by Marvel Studios and Hombale Films
-
2.16: List Movies by Latest Release Year
-
2.17: All Movies Released After 2020 with Rating Greater Than 8
-
2.18: All Movies Released After 2020
-
2.19: All Movies Released in 2022
-
2.20: Order Movies by Release Year
-
2.21: List Distinct Bollywood Studios
-
2.22: Release Year of The Godfather
-
2.23: Search for Avengers Movies
-
2.24: List Marvel Studios Movies
Data Analytics
Market Opportunity
While the market is tough, you need to build the exact skills to launch or accelerate your data analytics career with quality teaching. However, just building skills is not enough. You need to know how to present your skills in order to stand out from the crowd.
We help you in each and every step to achieve that:
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Portfolio Website
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Ace the job interview
-
Create an ATS resume
-
Build online credibility
-
Find the right jobs and companies
-
Network effectively on LinkedIn by showing your work
5,70,000 INR
Average Data Analyst Salary
Based on data from glassdoor.com
3,00,000
Number of Job Openings
Based on data from linkedin.com
23% GROWTH
Projected Demand for Data Analysts
Source: U.S. Bureau of Labor Statistics
Data Analyst with AI Toolkit Bundle
US$292
one-time payment
Includes: DA Bootcamp
+
AI Toolkit For Professionals
Get a 25% subsidy on AI Toolkit For Professionals
Get the BundleDA Bootcamp
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Practice with Complex Datasets of over 7M+ Records
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Practical Job Assistance with Virtual Internships
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10+ Business Projects to add to your Resume
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Job Application and Interview Playbooks
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Access to ATS Resume Builder
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Build a Free Portfolio Website
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Unlimited Chat Support
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Live Monthly Webinars
AI Toolkit For Professionals Course
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8+ Real Business Use Cases & Automations
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Get the complete bundle to learn skills practiced by industry experts. Save US$7 with a 25% subsidy.
Get the Bundle - Save US$7May we help you?
Frequently Asked
Questions
Q.1
Are the lectures going to be LIVE?
Q.4
What datasets are used in this bootcamp? Are they some toy datasets or something that mimics a real-world business problem?
Q.5
What is the duration of this data analytics bootcamp? How long will it last?
Q.6
Can I attend this data analytics bootcamp while working full time?
Q.7
What kind of skills can I expect to learn in this bootcamp?
Q.8
Will I get a recording of Zoom monthly webinars if I can't attend the live session?
Q.1
I am confused about whether to pursue my career as a data analyst. Can you help?
Q.2
Do I need a computer science degree or relevant work experience?
Q.3
I have never done programming in my life. Can I take this data analytics bootcamp?
Q.4
I am 40+ years old, can I enroll in this data analytics bootcamp?
Q.5
Is there any prerequisite for taking this bootcamp?
Q.1
Do you provide any job assistance?
Q.2
Will this data analytics bootcamp guarantee me a job?
Q.3
How can I contact the instructors for any doubts/support?
For any questions, that Google cannot answer or if you hit a wall - we got you covered!
You can join our active discord community, which is a dedicated platform to discuss & clear your doubts with fellow learners & mentors.
Q.1
How do I get the certificate?
Q.2
Is this bootcamp enough for me in Microsoft Power BI and Excel certifications?
In addition to this course, you might need to visit the official learning material designed by Microsoft which is available for free on their website.
Q.1
Do we have an EMI option?
(1) First buy the Excel course.
(2) After you have completed the Excel course, buy Power BI course.
(3) After completing the Power BI course, buy the Bootcamp.
This way you will pay in 3 installments.
Remember that the Bootcamp includes the same content from individual Excel and Power BI courses that you bought previously hence you will not lose anything in terms learning in your Bootcamp curriculum.
Also, all the progress you made in these individual courses will be transferred to Bootcamp automatically.
Note: Data Science courses are not part of the Data Analytics Bootcamp 5.0.
Q.2
I have already purchased other Codebasics courses like Excel and Python? Will I have to pay the full amount to enroll in this bootcamp?
If you have purchased any of our data analytics courses, you can pay the difference amount to enroll in the bootcamp. For example, if you have already bought Power BI and SQL. The amount you paid for these courses will be deducted from the Bootcamp price.
Note: Data Science courses are not part of the Data Analytics Bootcamp 5.0
Q.3
I’m an existing bootcamp learner, do I need to pay to get 5.0?
We are offering FREE upgrades for people who have enrolled in the previous two versions (DA 3.0 & DA 4.0) .
DA 1.0 & DA 2.0 learners require a minimum upgrade to DA 3.0 to access DA 5.0 content.
Note: The upgrade fee is non-refundable.
The upgrade fee is calculated as per the table below
| Version / Price | Price (India) | Price (LER) | Price (HER) | Upgrade Fee |
|---|---|---|---|---|
| DA 1.0 | 4800 | 66$ | 85$ | DA 3.0 price - DA 1.0 Price |
| DA 2.0 | 6300 | 90$ | 150$ | DA 3.0 price - DA 2.0 Price |
| DA 3.0 | 8400 | 100$ | 180$ | FREE Upgrade |
| DA 4.0 | 10800 | 150$ | 225$ | FREE Upgrade |
Q.4
I joined DA Bootcamp 3.0 / 4.0. Do I need to upgrade?
Q.5
Is this DA Bootcamp 5.0 upgrade mandatory?
If you have enrolled in DA 3.0 OR 4.0, you will be automatically upgraded to 5.0.
If you belong to earlier versions check the new features and enroll only if you really need it.
Q.6
Why there is an upgrade fee for DA Bootcamp 1.0 and 2.0 learners?
Q.1
What if I don’t like this data analytics bootcamp? Is there a refund policy?
However, if you’ve chosen the mode of payment as PayPal EMI option, the 30-day refund policy is NOT applicable.
No refunds will be provided for learners already enrolled in Bootcamp and opting for just Bootcamp upgrades.
Q.2
How can I trust Codebasics?
Q.1
I’m not sure if this data analytics bootcamp is good enough for me to invest some money. What can I do?
It is a high-quality material available for free-> If you like it and want to learn further then this bootcamp is the perfect extension.
Q.1
Are the lectures going to be LIVE?
Q.4
What datasets are used in this bootcamp? Are they some toy datasets or something that mimics a real-world business problem?
Q.5
What is the duration of this data analytics bootcamp? How long will it last?
Q.6
Can I attend this data analytics bootcamp while working full time?
Q.7
What kind of skills can I expect to learn in this bootcamp?
Q.8
Will I get a recording of Zoom monthly webinars if I can't attend the live session?
Q.1
I am confused about whether to pursue my career as a data analyst. Can you help?
Q.2
Do I need a computer science degree or relevant work experience?
Q.3
I have never done programming in my life. Can I take this data analytics bootcamp?
Q.4
I am 40+ years old, can I enroll in this data analytics bootcamp?
Q.5
Is there any prerequisite for taking this bootcamp?
Q.1
Do you provide any job assistance?
Q.2
Will this data analytics bootcamp guarantee me a job?
Q.3
How can I contact the instructors for any doubts/support?
For any questions, that Google cannot answer or if you hit a wall - we got you covered!
You can join our active discord community, which is a dedicated platform to discuss & clear your doubts with fellow learners & mentors.
Q.1
How do I get the certificate?
Q.2
Is this bootcamp enough for me in Microsoft Power BI and Excel certifications?
In addition to this course, you might need to visit the official learning material designed by Microsoft which is available for free on their website.
Q.1
Do we have an EMI option?
(1) First buy the Excel course.
(2) After you have completed the Excel course, buy Power BI course.
(3) After completing the Power BI course, buy the Bootcamp.
This way you will pay in 3 installments.
Remember that the Bootcamp includes the same content from individual Excel and Power BI courses that you bought previously hence you will not lose anything in terms learning in your Bootcamp curriculum.
Also, all the progress you made in these individual courses will be transferred to Bootcamp automatically.
Note: Data Science courses are not part of the Data Analytics Bootcamp 5.0.
Q.2
I have already purchased other Codebasics courses like Excel and Python? Will I have to pay the full amount to enroll in this bootcamp?
If you have purchased any of our data analytics courses, you can pay the difference amount to enroll in the bootcamp. For example, if you have already bought Power BI and SQL. The amount you paid for these courses will be deducted from the Bootcamp price.
Note: Data Science courses are not part of the Data Analytics Bootcamp 5.0
Q.3
I’m an existing bootcamp learner, do I need to pay to get 5.0?
We are offering FREE upgrades for people who have enrolled in the previous two versions (DA 3.0 & DA 4.0) .
DA 1.0 & DA 2.0 learners require a minimum upgrade to DA 3.0 to access DA 5.0 content.
Note: The upgrade fee is non-refundable.
The upgrade fee is calculated as per the table below
| Version / Price | Price (India) | Price (LER) | Price (HER) | Upgrade Fee |
|---|---|---|---|---|
| DA 1.0 | 4800 | 66$ | 85$ | DA 3.0 price - DA 1.0 Price |
| DA 2.0 | 6300 | 90$ | 150$ | DA 3.0 price - DA 2.0 Price |
| DA 3.0 | 8400 | 100$ | 180$ | FREE Upgrade |
| DA 4.0 | 10800 | 150$ | 225$ | FREE Upgrade |
Q.4
I joined DA Bootcamp 3.0 / 4.0. Do I need to upgrade?
Q.5
Is this DA Bootcamp 5.0 upgrade mandatory?
If you have enrolled in DA 3.0 OR 4.0, you will be automatically upgraded to 5.0.
If you belong to earlier versions check the new features and enroll only if you really need it.
Q.6
Why there is an upgrade fee for DA Bootcamp 1.0 and 2.0 learners?
Q.1
What if I don’t like this data analytics bootcamp? Is there a refund policy?
However, if you’ve chosen the mode of payment as PayPal EMI option, the 30-day refund policy is NOT applicable.
No refunds will be provided for learners already enrolled in Bootcamp and opting for just Bootcamp upgrades.
Q.2
How can I trust Codebasics?
Q.1
I’m not sure if this data analytics bootcamp is good enough for me to invest some money. What can I do?
It is a high-quality material available for free-> If you like it and want to learn further then this bootcamp is the perfect extension.
The ultimate Bootcamp to become a job-ready, AI-enabled data analyst — with dedicated job placement support.
Learning knows no limits. Here’s to your journey of seamless learning. Pick your preferred course from the list of paid & free resources.
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