Introduction to Computer Science and Programming

Description

Key Topics Covered:

1. Introduction to Computer Science Concepts
   • Basic principles of computer science, including algorithms, data structures, and problem-solving.
   • Understanding how computers work and the role of programming in solving computational problems.
2. Python Programming Basics
   • Introduction to Python, a beginner-friendly programming language.
   • Key concepts such as variables, data types, operators, and control structures (if statements, loops).
   • Writing and running basic Python programs.
3. Functions and Recursion
   • Understanding how to define and use functions in Python.
   • The concept of recursion and how it is used to solve problems by breaking them down into smaller subproblems.
4. Data Structures and Algorithms
   • Introduction to fundamental data structures, including lists, dictionaries, tuples, and sets.
   • Basic algorithms for sorting, searching, and processing data.
5. Object-Oriented Programming (OOP)
   • Introduction to object-oriented programming concepts, including classes, objects, inheritance, and polymorphism.
   • Understanding how to structure programs using OOP principles for cleaner, reusable code.
6. File Handling
   • Reading from and writing to files using Python.
   • Working with text files and managing data input/output efficiently.
7. Debugging and Problem Solving
   • Techniques for troubleshooting and debugging Python programs.
   • Approaches to breaking down complex problems into manageable steps to find solutions.
8. Computational Thinking
   • Applying computational thinking strategies to solve problems logically and efficiently.
   • Emphasizing abstraction, pattern recognition, decomposition, and algorithm design.
9. Basic Web Programming and APIs
   • Introduction to web programming concepts, including web servers, HTML, and interacting with web APIs using Python.
   • Learning to fetch data from web APIs and process it within Python programs.
10. Introduction to Computational Complexity
    • Basic concepts of computational complexity and big-O notation to understand the efficiency of algorithms.

Course Objectives:

• Understand Computer Science Fundamentals: Gain a broad understanding of core computer science concepts such as algorithms, data structures, and problem-solving techniques.
• Learn Python Programming: Master the Python programming language, focusing on the basics and how to apply it to write programs and solve problems.
• Master Basic Algorithms and Data Structures: Learn how to organize and manipulate data effectively using Python, as well as applying basic algorithms for sorting and searching.
• Develop Problem-Solving Skills: Build the ability to break down complex problems into smaller, more manageable parts and solve them using code.
• Understand Object-Oriented Programming (OOP): Learn the principles of OOP and how to design software systems using classes and objects for more structured and maintainable code.
• Learn File Handling: Develop the skills to interact with files, reading from and writing to them in Python for data storage and retrieval.
• Apply Computational Thinking: Develop logical thinking skills and computational approaches to solve real-world problems efficiently and effectively.
• Get Started with Web Programming: Learn the basics of interacting with web data, including working with APIs and understanding basic web programming principles.
• Evaluate Algorithm Efficiency: Understand how to evaluate the efficiency of algorithms and programs, learning to optimize code performance using big-O notation.