Our Promise: in 6 weeks, this is who you become
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AI skills. Today you write SQL one question at a time. By week 6: you build a SQL assistant that answers leadership's standing questions, checked against a golden set.
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AI skills. Today you ask AI and hope it's right. By week 6: you catch its confident wrong answers before leadership does.
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AI skills. Today you run reports by hand. By week 6: your AI agents watch the data and flag problems for you.
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People skills. Today someone else scopes the project. By week 6: you write the charter, estimate the work and run the planning meeting.
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People skills. Today you take requests. By week 6: you plan a quarter, delegate and hire with a scorecard.
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Strategy. Today you present numbers. By week 6: you pitch a strategy to a leadership panel that pushes back.
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Strategy. Today your work waits to be noticed. By week 6: you leave with a written promotion case, backed by six weeks of shipped work.
How It Works
Practise the manager's job before you get it.
For six weekends you play the Data Analytics Manager of GreenPlate FoodTech, a profitable food delivery company whose margin is slipping. Its new healthy food launch, Fresh, could fix it or make it worse.
Should Fresh go national? Build AI agents, find the answer and deliver the strategy to the leadership team.
Nick Puri
CEO
Victor von Vashist
CTO, your manager
Stephen Kumar
COO
Natasha Reddy
CMO
Morgan Sharma
CFO
Loki Lal
Data Engineer Overview
What you'll learn in
this Advanced Data Analyst Bootcamp
Week-1: Get started with AI
AI Landscape & SQL
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Session 1 - Day One at GreenPlate FoodTech: Kickoff and the AI Landscape (Sat 21st Nov)
The Day One email from the CEO · Company briefing: 12 cities, the Fresh pilot, five function heads, the warehouse · The analytics manager JD vs the 2026 JD · The AI landscape for analysts: assistants, Copilots, coding agents, automation, MCP · How LLMs work, just enough · What never goes into a prompt · Workspace setup · Scenario: the confident wrong answer
Output: A working AI workspace and your first-week plan as the Data Analytics Manager
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Session 2 - Build Day: Your SQL Assistant Answers Leadership's Ten Questions (Sun 22nd Nov)
Why a bare LLM writes wrong SQL on a real warehouse · Claude Projects with instructions and knowledge files · Loading schema, metric definitions and worked queries · Answering leadership's ten standing questions · The golden question set · Where it fails and how you catch it · Scenario: the forgotten refund filter
Output: Tool 1 of 5. A schema-aware SQL assistant, scored against a golden question set
Week-2: Plan the project
Planning & Claude Code
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Session 3 - Project Planning the Corporate Way: Charter, AIMS Grid, Estimation (Sat 28th Nov)
How a project really starts in a company · The project charter · The AIMS grid meeting, run live in pods as Marketing, Finance, Ops and Supply Chain · Stakeholder mapping and the decision contract · Estimation: work breakdown, three-point estimates, buffers · Personal branding and a 90-day plan · Scenario: the project estimate conundrum
Output: A charter, an AIMS grid and an estimate leadership signs off, plus your 90-day LinkedIn plan
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Session 4 - Claude Code: The Expansion Simulator That Ends the Marketing vs Finance Fight (Sun 29th Nov)
Marketing's model vs finance's model · Claude Cowork turns forty kitchen files into unit economics, with row counts reconciled · Designing the levers: budget by channel, CAC, kitchens, price, delivery fee, churn · Claude Code builds the simulator web app with Excel export · Verifying against one real month · Scenario: the simulator that flattered marketing
Output: Tool 2 of 5. An expansion simulator both teams trust
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Jamming Session 1 (optional) - Office Hours with Hem, Naveen and Aditya (Wed 2nd Dec, 8:00 to 9:30 PM IST)
Questions on the SQL assistant and the simulator · Debugging together · Recorded
Output: Both tool builds unblocked before Week 3 starts
Week-3: Build pipelines and apps
Fabric & Claude Code
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Session 5 - Analytics Pipelines on Fabric: The Payments Feed Finance Could Not Reconcile (Sat 5th Dec)
Fabric workspace, Lakehouse and SQL endpoint · VS Code with Claude Code · The daily orders pipeline: ingest, clean, load, schedule, refresh Power BI · Connecting a payment gateway sandbox API · Reconciling orders to payments · Power BI Copilot writes the DAX, you verify it · Fixing a failed run · Scenario: the 1.8 crore payments gap
Output: Tool 3 of 5. A scheduled payments pipeline finance can reconcile
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Session 6 - Building the Data Genie App with Claude Code (Sun 6th Dec)
Self-serve downloads for marketing and sales · Writing the spec: tables, filters, metrics, guardrails, row limits · Spec to working app with Claude Code · Read-only warehouse connection · Every query and download logged · A natural-language question box with a golden set · Scenario: forty download requests a week
Output: Tool 4 of 5. A guarded self-serve data app with an eval score
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Jamming Session 2 (optional) - On-Call Debrief with Hem, Naveen and Aditya (Wed 9th Dec, 8:00 to 9:30 PM IST)
What broke and how you found it · Pipeline and Data Genie questions · A walkthrough of the churn data · Recorded
Output: Ready for the ML session with the churn data understood
Week-4: Forecast and present
ML & Storytelling
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Session 7 - Machine Learning for Analysts: Predicting Churn by City with Regression (Sat 12th Dec)
When a rule beats a model · Framing churn per zone per week, with two baselines · Regression with scikit-learn: AI writes, you read · Reading coefficients out loud · Residuals by city · Spotting leakage and extrapolation in someone else's model · Reading an A/B test honestly · Scenario: the model that knows the future
Output: Tool 5 of 5. A churn forecast that beats its baselines, with a review memo
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Session 8 - Data Storytelling: Presenting to Stakeholders, and the Capstone Brief (Sun 13th Dec)
Answer first: the pyramid principle and SCQA · One chart, one message · The one-slide recommendation · What a CFO reads first vs a CMO · Executive Q&A and handling disagreement · AI-drafted summaries: keep, check, never send · The quarterly review pre-read, presented in pods · Capstone brief opened
Output: An executive deck and a five-minute readout leadership believes
Week-5: Lead the Team, build agents
Leadership & Agents
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Session 9 - Running an Analytics Team: Cadence, Delegation, Estimation, Hiring (Sat 19th Dec)
Where a manager's week goes · The intake queue and task planning · Estimating a real backlog against a fixed quarter · The weekly cadence: standup, review, retro · Delegation and managing up · Reviewing SQL, dashboards and analysis · Hiring with scorecards · The first 90 days as a manager · Scenario: the over-committed quarter
Output: A quarter plan, a hiring scorecard and your 90-day manager plan
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Session 10 - Building Analytics Agents, and the Command Center They Live In (Sun 20th Dec)
What makes an agent: goal, tools, loop, verification · When an agent beats a flow · A weekly insight report agent · A data-quality watchdog agent · A competitor price watch agent · The Command Center dashboard, built with Claude Code · Evals, guardrails, cost caps and audit logs · Scenario: the agent that lied on Tuesday · The unguided capstone starts here
Output: Scheduled, guarded analytics agents inside a dashboard you built
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Jamming Session 3 (optional) - Capstone Jamming with Hem, Naveen and Aditya (Wed 23rd Dec, 8:00 to 9:30 PM IST)
Implementation questions on your capstone · Design review · Debugging together · Recorded
Output: Your capstone unblocked before the review weekend
Week-6: Pitch on demo day
Capstone & Demo Day
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Session 11 - Capstone Review: Harden It, Test It, Learn to Pitch It (Sat 26th Dec)
Design review of every Command Center · Debugging the failures we see most · Evals against the golden sets · Hardening: guardrails, cost, audit log, handover README · How to pitch to leadership, rehearsed in pods · Packaging your analyst skill library · Your portfolio website, published on GitHub Pages
Output: A demo-ready capstone, 20+ packaged analyst skills and a live portfolio website
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Session 12 - Demo Day: Pitch the Command Center to the Leadership Panel, and Graduate (Sun 27th Dec)
Capstone pitches to the GreenPlate leadership panel · Writing your own promotion case · The analytics manager interview loop · Portfolio, GitHub and LinkedIn as an advanced data analyst · Graduation
Output: A five-minute pitch you have defended, and a promotion case backed by six weeks of shipped work
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Bonus Week · Sat 2nd and Sun 3rd January: Turn the Cohort into Your Next Role
Acting on the panel's feedback · Final capstone resubmission · Resume and LinkedIn built around your five tool builds · Your GreenPlate story in two minutes
Output: A finished capstone, an interview-ready resume and a rehearsed career story
Learn From
The People Who Run Analytics Teams
Hemanand Vadivel
Co-Founder & CEO, Codebasics
Leads most sessions and every leadership and management block.
I was among the top 1% with my amazing data analytics job in the UK. I left the job to stay back in India and pursue something that gives me a better sense of being and more joy - creating a positive impact on society by sharing knowledge.
Naveen S
Head of Data Analytics, Codebasics
Co-teaches every build session.
From a Tamil medium school and a Biomedical degree to Test Engineer at Infosys, I moved into data with no CS degree or connections, just by learning in public. In 4 years at Codebasics, I grew to Head of Content and Analytics. To me, AI has senior-level intelligence and intern-level reliability but it needs a data pro who knows what good looks like.
Aditya Goel
Business Automation Specialist & Learner Experience Lead, Codebasics
Backs the build sessions. Runs the jamming sessions with Hem and Naveen.
I come from a non-tech background and took a different route into data analytics. It has been 3+ years since I started this journey. Coming from a non-tech world gave me a fresh view of data and the stories it tells. Over time I moved into automation too. I started cutting down repetitive steps in my work, which gave me more time to find insights and understand the business. With AI in the picture, it is now about how to keep improving and optimizing the way you work. What I have learned is that anyone can learn the tools if they want to. Problem solving and finding better ways to work is what gives you the edge.
Dhaval Patel
Founder, Codebasics · Ex-NVIDIA
Curriculum advisor. Sets what this cohort teaches and what it refuses to.
I have 17 years of experience in programming and data science at leading tech companies like NVIDIA and Bloomberg. I also run Codebasics, a leading YouTube channel for data science, ML, and data structures. I believe "anyone can code", so I use analogies, simple explanations, and step-by-step storytelling to make complex concepts easy to understand, even for high school students.
The Stack
The tools senior analysts actually use in 2026
Claude
PRD drafting and Projects
Claude Code
Building the five tools
Claude Cowork
Multi-file cleaning
Microsoft Fabric
Lakehouse and pipelines
Power BI · Reporting
Reports and verified DAX
SQL
The warehouse
Python + Scikit-Learn
The churn regression
GitHub + VS Code
Where the work livesHear It From
Our Happy Learners
Our content is rated 4.9/5 from 8698+ Learners
Landed a Job
Landed a Job
Landed a Job
As someone with 3+ years of experience in data analysis, I found this course to be a well-structured and practical learning experience that strengthens core Power BI concepts from a strong business intelligence perspective. What stood out to me was the focus on real-world use cases rather than just tool-based learning.
The course covers essential areas such as data modeling, DAX, Power Query, and dashboard design in a clear and structured manner. Concepts like building relationships, writing efficient DAX measures, and creating interactive reports were explained with a strong emphasis on practical application. The end-to-end project was particularly valuable, as it provided a realistic view of how business problems can be translated into actionable insights using Power BI.
Even with prior experience, the course helped me refine best practices, improve report performance, and approach dashboard development more systematically. The examples and exercises were highly relevant and aligned well with real-world analytics and reporting scenarios.
Overall, this is a valuable course not only for beginners but also for experienced analysts who want to strengthen their Power BI skills and enhance their BI reporting capabilities.
Power BI
I started the Data Analytics Bootcamp 5.0 with a clear goal — to analyze company revenue in my home interior field. The journey so far has exceeded expectations. From Python, Excel & Statistics, Power BI, and SQL to interview preparation, every module has been directly applicable to my work.
As a designer + data analyst in my current firm, these skills have allowed us to track board movement, analyze revenue trends, identify fast-moving finishes, and plan more strategically for business growth. The hands-on, real-world approach of this bootcamp has turned data into a powerful decision-making tool for our team.
Thanks to Hemanand Vadivel, Dhaval Patel, and the Codebasics team for creating a practical and industry-focused program. I’m excited to move into the next phases — Virtual Internship, Data Engineering, and AI Automation — and take our data capabilities to the next level.
I had a great learning experience with Codebasics, especially across SQL, Power BI, and Excel.
What stood out for me was the structured approach and strong focus on business problem-solving, rather than just tool usage. The concepts are explained clearly, making them easy to apply in real-world analytics scenarios.
The hands-on projects and practical examples helped reinforce fundamentals and bridge the gap between learning and implementation. Overall, a solid platform for professionals looking to strengthen their data analytics skill set.
Appreciate the efforts of Dhaval Patel , Hemanand Vadivel and the Codebasics team for building such industry-relevant content.
Highly Recommended the "Excel: Mother of Business Intelligence" course from @Codebasics, and I am pleased to share my thoughts on the program.
1. Content Quality: The course provides an in-depth understanding of Excel, starting from the basics and gradually moving into advanced functionalities that are crucial for business intelligence. It covers a wide range of topics, including data analysis, pivot tables, complex formulas, charts, and macros, making it an excellent resource for both beginners and intermediate users.
2. Practical Applications: What sets this course apart is its strong emphasis on practical application. Each module is designed with real-world business problems in mind, helping learners understand how Excel can be leveraged to analyze data and drive business decisions. The use of case studies, hands-on exercises, and projects allows you to practice and apply what you've learned immediately.
3. Teaching Style: The instructor’s teaching style is clear and engaging. Complex concepts are broken down into simple steps, and the explanations are thorough, making it easy to follow even for those with limited prior experience in Excel. The pace of the course is well-balanced, with each section building upon the previous one.
4. Course Structure and Materials: The course is structured in a logical manner, making it easy to navigate. The video lessons are supplemented with downloadable Excel files, which allow learners to work along with the instructor. Additionally, the quizzes and assignments at the end of each section reinforce learning and ensure a solid grasp of the material.
5. Overall Impact: This course has significantly enhanced my Excel skills and has provided me with tools that I can directly apply in my work. I now feel more confident in handling large data sets, performing data analysis, and creating dynamic dashboards. It’s truly a comprehensive course that lives up to its title as the “Mother of Business Intelligence.”
Recommendation: I highly recommend this course to anyone looking to improve their Excel skills, particularly for business intelligence purposes. Whether you are a beginner or someone with experience, you will find valuable insights that will enhance your productivity and analytical capabilities.
Special thanks to Dhaval Patel sir and Hemanand Vadivel sir for making complex concepts easy to grasp and providing real-world applications for each tool.
Tags : Dhaval Patel | @Hemanand Vadivel | Shashank Singh | Pradeep M | Thodupunuri Bharath | Adilfaizan Razvi
Enrolling in the Code Basics Data Analytics Bootcamp 5.0 has truly been a transformational journey that exceeded my expectations on all fronts. As an accountant with little exposure to coding or data science, I initially worried about whether I could keep up with the curriculum or apply the new skills to my current career. However, from the very first module, it was clear that the course was built for ambitious learners like me who want to transition into analytics with practical support, clear teaching, and genuine community engagement.
What set this bootcamp apart for me were the logical, well-structured lessons taught by Dhaval & Hemanand —a gifted instructor who makes even the most complex topics easy to grasp. The hands-on approach was evident in every module, as we tackled real company datasets and industry-based projects from finance, marketing, HR, and more. The virtual internship with AtliQ Technologies was a true highlight. Getting the opportunity to work through authentic business problems, perform analyses, and present insights in a simulated corporate setting elevated my confidence and gave me a strong sense of what a real data analytics job demands.
The bootcamp didn’t just help me master Excel, Power BI, SQL, and Python—it fundamentally changed how I think about working with data. Assignments like scenario planning in Excel, Revenue Analytics in Python, and full-fledged dashboard creation in Power BI were challenging, but the daily support via private Discord channels meant I was never stuck for long. Every doubt, big or small, was answered patiently, and the peer community helped me stay motivated through dips in confidence.
As an accountant, I particularly valued how the bootcamp’s finance analytics modules directly aligned with my background. Concepts such as P&L statements, variance analysis, and scenario simulation were not only introduced but integrated into practical exercises so I could use my domain knowledge alongside my new technical skills. The resume-building guides, LinkedIn optimization sessions, and mock interview practice gave me a clear roadmap for how to present myself to recruiters. I felt equipped not just with technical skills but also with communication tools and an online portfolio to demonstrate my capabilities.
But what made the biggest difference was the environment. The learning path felt cinematic at times, with engaging videos, storytelling, business meetings, deadlines, and a constant sense that I was moving closer to my professional goals. I am incredibly grateful for the dedication of Dhaval and the Code Basics team, who genuinely care about learner outcomes. I’m proud to say that after completing this bootcamp, I secured an interview and am now moving forward into a data analyst role that uses all the skills I built here.
If you are an accountant or from any non-technical background and wish to become a job-ready data analyst, I cannot recommend this bootcamp enough. It was rigorous, inspiring, and delivered real results—giving me the confidence to step into the world of data with new clarity and purpose.
The Codebasics Promise
Not a tutorial. A career move.
Five working tools, three AI agents and a strategy you pitch to a leadership panel that pushes back.
| What you get | Recorded course | Generic AI bootcamp | This cohort |
|---|---|---|---|
| Live, mentor-led sessions | |||
| Data you work on | Sample files | Toy datasets | 20M order lines |
| The 2026 AI analyst stack | On your own | Often generic | |
| People and management skills | No | Rarely | Planning, stakeholders, running a team |
| Strategy pitch to leadership | No | No | Demo Day panel that pushes back |
| Proof for your career | A certificate | A certificate | 5 tools, 3 agents, promotion case, portfolio |
| Investment | Your time | Usually far higher | US$420 |
May we help you?
Frequently Asked
Questions
Q.1
When does the bootcamp officially start?
Q.2
When do I get access after enrolling as an Inner Circle member?
Q.3
What is the Inner Circle, and how is it different from regular enrollment?
Q.4
What will I build in this bootcamp?
Q.5
When are the live sessions?
Q.6
What if I miss a live session?
Q.7
What happens after the 42 days? Do I lose access?
Q.8
Is the Data Analytics Bootcamp 6.0 included in this cohort?
If you need to brush up, the cohort includes pre-work refreshers and the Data Analytics fundamentals courses to help you prepare.
Q.1
Do I need prior experience?
Q.2
I am a fresher with no work experience. Can I join?
Q.3
Who is this bootcamp designed for?
Q.4
I'm a learner in the Codebasics Data Analytics Bootcamp. Can I join?
Q.1
How do I get help if I am stuck?
Q.2
Is there job assistance?
Q.1
What is the Inner Circle price and when does it close?
Q.2
I already own a Codebasics Data Analytics Bootcamp or some courses from it. What do I pay?
Q.1
I used a subsidy and now want to refund this Bootcamp itself. What happens?
Q.2
I used a subsidy (my existing Data Analytics Bootcamp or individual course purchase). Can I refund my original purchase after enrolling?
Q.3
What is the refund policy?
Please note: The refund window is based on the two live sessions scheduled after your enrollment, not on whether you attended them. If you miss a session, the refund window still moves forward.
To request a refund, email [email protected] before the window closes.
Please read the full refund policy here.
Q.1
When does the bootcamp officially start?
Q.2
When do I get access after enrolling as an Inner Circle member?
Q.3
What is the Inner Circle, and how is it different from regular enrollment?
Q.4
What will I build in this bootcamp?
Q.5
When are the live sessions?
Q.6
What if I miss a live session?
Q.7
What happens after the 42 days? Do I lose access?
Q.8
Is the Data Analytics Bootcamp 6.0 included in this cohort?
If you need to brush up, the cohort includes pre-work refreshers and the Data Analytics fundamentals courses to help you prepare.
Q.1
Do I need prior experience?
Q.2
I am a fresher with no work experience. Can I join?
Q.3
Who is this bootcamp designed for?
Q.4
I'm a learner in the Codebasics Data Analytics Bootcamp. Can I join?
Q.1
How do I get help if I am stuck?
Q.2
Is there job assistance?
Q.1
What is the Inner Circle price and when does it close?
Q.2
I already own a Codebasics Data Analytics Bootcamp or some courses from it. What do I pay?
Q.1
I used a subsidy and now want to refund this Bootcamp itself. What happens?
Q.2
I used a subsidy (my existing Data Analytics Bootcamp or individual course purchase). Can I refund my original purchase after enrolling?
Q.3
What is the refund policy?
Please note: The refund window is based on the two live sessions scheduled after your enrollment, not on whether you attended them. If you miss a session, the refund window still moves forward.
To request a refund, email [email protected] before the window closes.
Please read the full refund policy here.
The career booster for data analysts · Inner Circle US$420 until 17th Nov · Save ₹9,000
Excel