Peter fetches data using APIs | Codebasics

Go to Course Page

Gen AI & DS Bootcamp is Live

0% Completed

- Login
- Register

back

- Login
- Register

0% Completed

Contents

1.1: Course Introduction
1.2: What Benefits You Get By Learning Python?
1.3: Who can Enroll In This Course? Any Prerequisites?
1.4: What Kind Of Computer Do I Need For This Course?
1.5: Course Content Overview

2.1: Join Discord for doubt clearing support & networking
2.2: Setting Video Resolution and Video Speed Globally

3.1: Project 1: Hospitality Domain Data Analysis
3.2: Project 2: Expense Tracking System

4.1: Peter Pandey’s Journey and Need to Learn Python
4.2: Python Installation - Windows
4.3: Python Installation - Linux
4.4: Python Installation - Mac
4.5: How to Download Code and Get Help If I Have a Question?

5.1: Variables
5.2: Numbers
5.3: Strings
5.4: Quiz: Variables, Numbers and Strings
5.5: Peter shares his Coding Fear with Tony
5.6: Exercise: Variables, Numbers and Strings
5.7: Chapter Summary

6.1: Lists
6.2: Install Pycharm
6.3: If Condition
6.4: For Loop
6.5: Quiz: Lists, If Condition and For Loop
6.6: Peter Found Something Interesting to Practice
6.7: Exercise: Lists, If Condition and For Loop
6.8: Chapter Summary

7.1: Functions
7.2: Dictionary and Tuples
7.3: Modules and Pip
7.4: File Handling
7.5: Quiz: Functions, Dictionaries, Tuples and File Handling
7.6: Peter’s Request to Tony
7.7: Exercise: Functions, Dictionaries, Tuples and File Handling
7.8: Two Deadly Viruses Infecting Learners
7.9: Chapter Summary

8.1: Classes and Objects
8.2: Operator Overloading
8.3: Inheritance
8.4: Exception Handling
8.5: __main__ Function
8.6: Quiz: Classes, Exception Handling
8.7: Using Python in a Real Time Problem
8.8: Exercise: Classes and Exception Handling
8.9: Chapter Summary

9.1: Introduction and Benefits
9.2: Basic Operations
9.3: Matrix Operations
9.4: Slicing, Stacking
9.5: Quiz: NumPy
9.6: Peter Solves a Real Time Problem Using NumPy
9.7: Exercise: NumPy
9.8: Chapter Summary

10.1: Pandas Introduction and Installation
10.2: Dataframe Basics
10.3: Read, Write Excel and CSV Files
10.4: Handle NA values - Part 1
10.5: Handle NA values - Part 2
10.6: Group by
10.7: Concat and Merge
10.8: Data Visualization Using Matplotlib and Seaborn
10.9: Quiz: EDA using Python

11.1: Problem Statement, OLTP vs OLAP, ETL, Data Warehouse
11.2: Data Understanding: CSV Files
11.3: Data Understanding: Fact vs Dim table, Star vs Snowflake Schema
11.4: Data Exploration
11.5: Data Cleaning
11.6: Data Transformation
11.7: Insights Generation

12.1: Introduction
12.2: Set and Frozenset
12.3: Lists, Dict and Set Comprehensions
12.4: Quiz: Comprehensions and Sets
12.5: Peter gets Adhoc tasks on Advanced Topics
12.6: Exercise: Comprehensions and Sets
12.7: PEP8 Naming Convention
12.8: Code Debugging Using PyCharm
12.9: Chapter Summary

13.1: Working with JSON
13.2: Generators and Iterators
13.3: Decorators
13.4: Quiz: JSON, Generators and Decorators
13.5: Exercise: JSON, Generators and Decorators
13.6: Chapter Summary

14.1: What is API?
14.2: Calling APIs With requests Package
14.3: Building APIs With FastAPI
14.4: Quiz: APIs
14.5: Peter fetches data using APIs
14.6: Exercise: APIs
14.7: Chapter Summary

15.1: Logging
15.2: Automated Testing with Pytest
15.3: MySQL Setup: Windows
15.4: MySQL Setup: Linux, Mac
15.5: Working with MySQL in Python
15.6: Data Validation with Pydantic
15.7: Quiz: Logging, Pytest, Pydantic and Databases
15.8: Exercise: Pytest, Pydantic
15.9: Chapter Summary

16.1: Problem Statement & Tech Architecture
16.2: Database CRUD Operations
16.3: Automated Tests Setup for CRUD
16.4: Expense Management: Backend (FastAPI)
16.5: Expense Management: Logging
16.6: Streamlit Introduction
16.7: Expense Management: Frontend (Streamlit)
16.8: Analytics: Backend (FastAPI)
16.9: Analytics: Frontend (Streamlit)
16.10: README and Requirements.txt
16.11: Exercise

17.1: 7 Career Options After Learning Python
17.2: Next Steps: Python Backend Engineer, Software Engineer
17.3: Next Steps: Data Analyst, Data Scientist
17.4: Stay Connected And Thank You

18.1: Final Quiz

19.1: Technical Architecture of the Project
19.2: Installation of Necessary Libraries
19.3: Extract text from a pdf document
19.4: Thresholding in OpenCV
19.5: Regular Expressions or Regex
19.6: Regex Exercise
19.7: Python class for prescription
19.8: Code Refactoring
19.9: Unit Tests using pytest
19.10: I Need a Favour

20.1: Write patient details class yourself
20.2: Extract name from a document
20.3: Extract remaining fields from a document
20.4: Write patient details class
20.5: Integrate doc parser classes into an extractor

21.1: FastAPI Basics
21.2: Write FastAPI server for our project
21.3: Integration With Frontend And Deployment

Instructor

Dhaval Patel

Dhaval Patel

Data Entrepreneur | YouTuber | Ex - Bloomberg, Nvidia

I have 17 years of experience in Programming and Data Science working for big tech companies like NVIDIA and Bloomberg. I also run a famous YouTube channel called Codebasics where I pursue my passion for teaching. Codebasics is one of the top channels on YouTube when it comes to data science, machine learning, data structures, etc. I firmly believe that “Anyone can code” and I use analogies, simple explanations, and step-by-step storytelling to explain difficult concepts in such a way that even a high school student can understand them easily.

Peter fetches data using APIs

Prev Next

Lecture content Locked

Enroll in Course to Unlock

Login

Log in with Google

Log in with Linkedin

E-Mail Address

Enter your Password

Forgot Password?

Don't have an account? Register Now!

By signing up, you agree to
our Terms and Conditions and Privacy Policy.