Python for Data Analysis (my learning journey)

I’m currently taking the Complete Data Analyst Bootcamp course offered by 365 Careers on Udemy and using it as the core structure for my Python learning. But I’m not stopping there. I’m also diving deeper into individual topics from other online sources (tutorial sites, blogs, articles, etc and of course… a fair bit of help from OpenAI's ChatGPT) through my self-exploration.

This space documents my personal journey of mastering Python for Data Analytics. The goal is not only to learn and practice coding but to:

• Build a solid foundation in Python for Data Analysis
• Organize and document my diversified learning in one place
• Create a personal reference hub for easy access in future

I am sharing this here because I’m excited to see and share how my learning process, which includes a mix of structured lessons and curious explorations, evolves over time. This is a work in progress repository and I’ll keep adding new notebooks as I learn more.

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Topics Covered (so far)

1. Python Programming Basics - Print statement, Comments, Variables, Data Types, Operators, Conditional Statements, Functions, Built-In Python Functions, Sequences, Iteration, etc.

2. All about Strings - Intro, Multi-line Strings, Escape chars, Funtion Parameters, Raw strings, Comparison, String Methods, Indexing & Slicing, Membership, Immutability, Formatting Strings, etc.

3. Sequences

   • List - Creating List, Indexing & Slicing, Modifying elements, List Methods, etc.

   • Tuple - Creating Tuple, List to Tuple, Tuple methods, Immutability, Unpacking, Concatenation, Multiplying Tuples, Deleting tuples, etc.

. (…more to come!)

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Tools I’m Using

• Language: Python 3.x
• Environment: Jupyter Notebook
• Libraries: NumPy, Pandas, Matplotlib, Seaborn

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Learning Sources

A mix of everything that’s helped me grow so far:

• Udemy Bootcamp course (most parts)
• GeeksforGeeks, W3Schools
• YouTube tutorials & blog articles
• AI integrated learning with the help of OpenAI's ChatGPT

This is mainly my personal learning log, but suggestions and improvements are always welcome!

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How to Use

1. Clone or download this repository.
2. Open the .ipynb notebooks in Jupyter Notebook / JupyterLab / VS Code.
3. Run the cells step by step to follow along the practice.

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Feel free to Connect!

Aliya Fanaskar - LinkedIn
Thanks for stopping by!