{"id":21513816,"url":"https://github.com/n-sapkota/dsma-113-python-programming","last_synced_at":"2026-02-21T20:05:00.729Z","repository":{"id":262845111,"uuid":"888537037","full_name":"n-sapkota/DSMA-113-Python-Programming","owner":"n-sapkota","description":"This repository is for DSMA 113: Introduction to Python Programming at Kathmandu University. The course introduces foundational Python concepts, including syntax, data structures, object-oriented programming, and essential libraries like NumPy, Pandas, and Matplotlib. 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This course provides a comprehensive foundation in Python, covering fundamental programming concepts, data structures, object-oriented principles, and essential libraries for data science.\n\n---\n\n## Course Information\n\n- **Course Code:** DSMA 113  \n- **Credits:** 3  \n- **Lecture Hours:** 45  \n- **Institution:** Kathmandu University  \n- **Program:** Bachelor in Data Science\n\n---\n\n## Course Objectives\n\nBy the end of this course, students will be able to:\n\n- Understand essential programming concepts: syntax, data types, variables, operators.\n- Develop efficient algorithms and apply computational thinking.\n- Utilize Python’s built-in data structures (lists, tuples, dictionaries, sets).\n- Implement object-oriented programming (OOP) concepts.\n- Handle files for reading/writing operations.\n- Utilize popular Python libraries like **NumPy**, **Pandas**, and **Matplotlib** for data manipulation and visualization.\n\n---\n\n## Course Outline\n\n### Unit 1: Introduction\n- Overview of Python, installation, using IDLE and Jupyter Notebook\n- Virtual environments, comments, indentation, tokens, operators\n\n### Unit 2: Decision and Loops\n- **Conditional Statements:** `if`, `if-else`, `if-elif-else`\n- **Looping Statements:** `for`, `while`\n- **Exception Handling**\n\n### Unit 3: Built-In Data Types\n- **Numerics, Strings, Lists, Tuples, Sets, Dictionaries**\n\n### Unit 4: Functions\n- Benefits, creation, argument handling, lambda and recursive functions\n\n### Unit 5: Object-Oriented Programming (OOP)\n- Classes, encapsulation, inheritance, polymorphism, data hiding\n\n### Unit 6: File Handling\n- File modes, reading/writing, `os` module\n\n### Unit 7: Common Python Libraries\n- **NumPy:** Arrays, indexing, broadcasting, statistical functions\n- **Pandas:** DataFrames, indexing, missing data, merging, CSVs\n- **Matplotlib:** Plotting and visualization (scatter, bar, histogram, etc.)\n\n### Unit 8: Developing a Project\n- Project design, module decomposition, data flow diagrams\n\n---\n\n## Laboratory Work and Final Project\n\nThis repository contains lab exercises for each course unit. The final project will apply skills learned throughout the course. Project ideas include:\n\n1. **Exploratory Data Analysis (EDA):** Analyzing datasets to uncover patterns.\n2. **Regression Analysis:** Implementing regression models for predicting outcomes.\n\n---\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fn-sapkota%2Fdsma-113-python-programming","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fn-sapkota%2Fdsma-113-python-programming","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fn-sapkota%2Fdsma-113-python-programming/lists"}