A complete beginner-friendly journey into problem solving with Python
This repository contains my completed work from MMDT_T-PY101, a foundational Python programming course offered by Myanmar Data Tech (MMDT).
The course covers core computational thinking, essential Python syntax, and practical programming skills through hands-on exercises and mini-projects.
This repo demonstrates my ability to:
- Write clean, beginner-friendly Python code
- Solve logical and mathematical problems programmatically
- Apply core CS concepts in practice
- Use Python to build small, functional solutions
The main goals of the course—and this repo—include:
- Building strong foundations in Python programming
- Understanding variables, loops, conditions, and functions
- Practicing step-by-step problem solving
- Strengthening logical reasoning and algorithmic thinking
- Gaining confidence in debugging and writing clean code
This repository includes my solutions and notes for topics such as:
- Variables, data types, input/output
- Lists, tuples, dictionaries
- Loops and iterations
- Conditional statements
- Function design
- Decomposition and modular coding
- Simple algorithms
- String manipulation
- Math and logic problems
- File handling
- Algorithmic thinking tasks
- Solid Python fundamentals
- Clear coding structure and readability
- Ability to learn and apply new concepts quickly
- Strong logical and analytical thinking
- Preparedness for advanced CS, algorithms, or ML coursework
I plan to extend this repository with:
- Additional mini-projects using the same foundational skills
- More algorithm practice (sorting, searching, recursion)
- Real-world beginner-level applications
- Notes and examples for students learning Python
This repo serves as:
- A portfolio proof of my foundational Python programming knowledge
- A demonstration of consistent learning and problem-solving skills
- A stepping stone toward advanced CS, AI, and data science projects
This repo includes the assignments and lectures conducted in the Python Programming Course. This Course teaches you programming in general as well as Python fundamentals for data science. This course provides you knowledge and skills to create basic programs to work with real data and solve real-world problems in Python. You will gain a strong foundation for more advanced learning that requires the Python Programming knowledge.
Link for Lecture videos : https://youtube.com/playlist?list=PLVJBFnpmHjrYpoBtrsFCYJ3yoO0ocv1SP
I believe that hands-on learning is crucial for understanding and thus, the explanations in the book are accompanied by detailed ’Python code’ snippets throughout the text. The readers can follow the structions and run the code in this Repo on their own computer or an online platform such as Google Colab.
- Go to the original repository's page: https://github.com/myothida/PythonProgramming.git
- Click on the "Fork" button in the top-right corner. This will create a copy of the repository under your GitHub account
Refer to this Github documents: https://docs.github.com/en/repositories/working-with-files/managing-files/adding-a-file-to-a-repository.
- Go to your forked repository's page on GitHub.
- Click on the "Add file" button, located above the list of files.
- In the dropdown menu, select "Upload files." This will open a file upload dialog.
- You can either click on the area to drag and drop your files or click on the "choose your files" button to browse and select files from your local machine.
- Once you've selected the files you want to upload, click on the "Commit changes" button to upload the files to your repository.
*** Before creating the pull request or clone, it's recommended to sync your forked repository with the latest changes from the original repository. ***