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Python & AI Training: Streamline Your Code with AI Assistants

Module 1 – Introduction to Python and AI Assistants

  • Overview of the language and its scientific applications
  • Installing Python and the code editor (VS Code or Jupyter recommended for AI integration)
  • Introduction to AI Coding Tools: Setting up an assistant (e.g., Gemini, Copilot) and core prompting principles for developers
  • First steps with the Python console, scripts, and generating your initial code using AI

Module 2 – Programming Fundamentals

  • Variables, data types, and type conversion
  • Strings, numbers, and booleans
  • Arithmetic and logical operations
  • AI Practice: Using the assistant to generate examples of data type manipulation and understanding conversion errors (TypeError)

Module 3 – Control Structures and Algorithmic Logic

  • Conditions (if, elif, else)
  • Loops (for, while)
  • Indentation principles and best practices
  • AI Practice: Asking the AI to translate a textual algorithm into Python control structures, and using the assistant to catch indentation errors (IndentationError)

Module 4 – Functions, Modularity, and Documentation

  • Creating and calling a function (passing parameters and returning values)
  • Structuring code into logical blocks
  • AI Practice:
    • Writing prompts to generate reusable functions
    • Using AI to automatically generate comments and documentation (docstrings) compliant with PEP 8 standards

Module 5 – Introduction to Object-Oriented Programming (Optional)

  • Understanding the concept of objects in Python
  • Creating a class and instantiating simple objects
  • AI Practice: Using the assistant to model simple object relationships and generate the structural code for a class

Module 6 – File Manipulation and Data Handling

  • Reading and writing text files (TXT, CSV)
  • Parsing and processing data line by line
  • AI Practice: Asking the assistant to generate quick data cleaning or formatting scripts based on a provided file sample

Module 7 – AI-Augmented Practical Project

  • Creating a complete project combining variables, loops, functions, and file manipulation
  • Prompt Engineering for Debugging: Learning how to submit error codes to the AI to get a diagnosis and refactoring suggestions
  • Corrections, AI-driven automated code reviews, and personalized instructor feedback