“Python & AI for Absolute Beginners”
Learn to Code with Google Colab, ChatGPT, and Data Science Tools
Contents
Part 1｜Python for Total Beginners
The Ultimate Beginner’s Guide to Python — Your Fastest Route from Basics to ChatGPT Integration!
| # | Title | Summary |
|---|---|---|
| ① | Setting Up the Environment | No installation needed—set up Python in 5 minutes using Google Colab. |
| ② | Getting Started with Python (Basic Calculations) | Learn your first Python code with simple calculations and print statements. |
| ③ | Variables and Lists | Understand how to store and manage data using variables and lists. |
| ④ | if Statements | Master conditional logic and control the flow of your programs. |
| ⑤ | for Loops | Learn how to repeat tasks efficiently using for loops. |
| ⑥ | while Loops | Use while loops to create flexible, condition-based repetition. |
| ⑦ | Functions | Learn how to organize and reuse your code with custom functions. |
| ⑧ | Libraries: pandas | Work with table-like data using pandas, the essential data analysis library. |
| ⑨ | Libraries: numpy | Perform fast, precise numeric computations with the power of numpy. |
| ⑩ | Libraries: matplotlib | Visualize your data with graphs using matplotlib. |
Part 2｜Python × ChatGPT
Use AI to write better code, faster!
| # | Title | Summary |
|---|---|---|
| ⑪ | What Is ChatGPT? | A beginner-friendly explanation of how ChatGPT works, what it can (and can’t) do, and its role in AI-driven conversations. |
| ⑫ | How to Use ChatGPT | Learn how to create an OpenAI account, start using ChatGPT, and understand the differences between GPT-3.5 and GPT-4 (free vs paid). |
| ⑬ | Applying ChatGPT in Python | Practical examples of how to use ChatGPT for writing code and fixing errors — a hands-on guide to using AI in your coding workflow. |
Part 3｜Data Analysis & Machine Learning for Beginners
Data Analysis & AI Essentials — Learn everything from the basics of data analysis to the fundamentals of machine learning through hands-on practice!
| # | Title | Summary |
|---|---|---|
| ⑭ | Steps in Data Analysis | Learn the full process of data analysis: hypothesis, aggregation, visualization. |
| ⑮ | What Is Machine Learning? | Understand how machine learning works through simple, real-world examples. |
| ⑯ | Supervised vs Unsupervised Learning | Explore the differences and use cases of supervised and unsupervised methods. |
| ⑰ | Regression Analysis | Use Python to make predictions from data using linear regression models. |