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Python Course

This course is designed to introduce participants to the foundational concepts of text-based Python programming. It covers essential features, programming constructs, and advanced techniques to prepare learners for real-world applications. The course also provides an introduction to data analysis, enabling participants to develop skills that are in high demand across industries.

  • Online
  • 20 hours
  • Certificate of completion
  • Target Audience: Python beginners, students and professionals, and future data analysts or developers.
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Course Content

Understand the basics of Python programming

 including syntax, features, and key functions such as print and input.

Use an IDE to write code and run it with Python’s interpreter; compilers are optional.

Know keywords, identifiers, literals; use clear, valid variable names.

  1. Arithmetic operators: for basic math operations like addition, subtraction, multiplication, and division.

  2. Comparison operators: to compare values (e.g., equal to, greater than, less than).

  3. Logical operators: for combining conditions (and, or, not).

  4. Membership operators: to check if a value exists in a sequence (in, not in).

  5. Bitwise operators: for operations on binary numbers (AND, OR, XOR, shifts).

  6. Identity operators: to check if two objects share the same memory location (is, is not).

  • float
  • complex
  • tuple
  • dict
  • Learn data type conversion techniques.
  • if, elif, else
  • Nested if statements
  • Proper indentation in Python.

Use loops to repeat tasks and create patterns; apply nested loops for more complex logic like grids or structured designs.

  • Dictionary, List, and String
  • Utilize functions, loops, and nested dictionaries.
  • Parameters and arguments
  • Default values
  • Lambda functions.

Extend Python’s functionality by organizing code into modules, using built-in and external libraries, and managing collections of tools with packages.

  • Creating, reading, writing, and deleting text and CSV files
  • Managing and manipulating data.

Build a strong foundation in data analysis by learning core concepts and techniques, such as handling datasets, cleaning data, and drawing insights using Python tools and libraries.