MMC-DataScience is a mini-project undertaken during AIO 2024, involving nearly 100 members. This project serves as an introduction to basic Data Science concepts, preparing participants for the full course ahead.
As a Teaching Assistant, my role entails preparing course content and delivering lessons for Modules 2, 3, and 4.
- Module 1: Data Science Introduction
- Module 2: Data Analysis with Python
- Module 3: Machine Learning for Data Science
- Module 4: Deep Learning for Data Science
- Module 5: Final Project
- Objective: Learn foundational tools and concepts in Data Science.
- Topics Covered:
- Introduction to Git, Github, Anaconda, and Jupyter Notebook.
- Overview of the Data Science Process.
- Basic Python concepts: Strings, Loops, Functions.
- Python coding exercises: Lottery Game Versions 1, 2, and 3.
- Python data structures: Lists, Sets, Dictionaries, Tuples.
- Handling Files, Error Handling, Regular Expressions, Python modules.
- Introduction to Numpy: Arrays, Basic Calculations, Basic Statistical Functions.
- Status: Completed
- Objective: Learn to analyze data using SQL and Python.
- Topics Covered:
- Overview of the Data Analysis Process.
- Introduction to SQL
- Status: On-going
This repository contains coding materials related to the course, including labs, projects, and mini-games throughout the duration of the course. Each module's materials and projects will be organized within the repository for easy access and reference.
Feel free to explore the repository to review course content, access projects, and further your understanding of Data Science concepts.
This repository is licensed under the MIT License.
Please read the LICENSE file for more details.
Feel free to contact me at [email protected] if you have any questions or concerns.