(in Polish) Komunikacja z AI: Programowanie w Python 1 2600-ZLAIz1KAIPIf

Module 1 – Introduction: Development Environment and Python Basics
Information about the course, grading rules
Introduction to Python and its applications in business
• Why learn Python? Why learn programming if you don’t want to become a programmer?
• Examples: automation, data analysis, decision support
Development environment: Anaconda, Google Colab, Visual Studio Code
• Installing and configuring Anaconda for local work
• Running Python in the console
• Jupyter Notebook – the best invention since sliced bread
• Introduction to Google Colab as a cloud-based alternative: collaboration, leveraging Google’s server resources
• Visual Studio Code – coding like a professional ;)
• Differences, advantages, and limitations of various environments
Python as a smarter calculator
• Basic arithmetic operations
• Printing results
Numbers, text, and logical operations
• Variables, numbers, basic operations, comments, int, float, string, boolean
• Arithmetic and logical operators
Strings and text processing
• Handling client names, product categories, reviews
• String formatting (f-strings)

Module 2 – Control Flow, Loops, and Testing
Conditional statements and business logic
• If/else statements and decision rules
• Exercises: discount calculator, credit approval rules
Functions and reusable logic
• Defining functions
• Splitting code into reusable parts – best practices – “do one thing, but do it well”
Installing external Python libraries
• Using the package manager pip
• Virtual environments (venv)
Testing
• The pytest library
• Best practices
Module 3 – Working with Data Collections and Loops
Data structures – arrays, lists
• Lists: creating, modifying, basic operations
• append(), remove(), len(), indexing
• Iterating over lists
Examples
Loops
• For and while loops
• The range() function, iterating over lists
• Examples
Dictionaries and tuples
• Basics of dictionaries
• Creating, accessing values, methods keys(), values(), items()
• Tuples
Module 4 – Classes and Objects
Object-Oriented Programming – the concept
• Simple introduction (employees, products as objects)
• Classes and objects
• Adding behavior to objects – inheritance and polymorphism
Applications
• Using existing classes
• Creating custom classes and objects, initialization
Code organization and creating custom modules
• Importing built-in and custom modules
• Exercises: splitting business logic across files
• Best practices for structuring code in files/directories
Useful built-in modules
• datetime, math, random, os, pathlib, statistics
Version control (optional topic)

Module 5 – Input/Output Handling
Reading data
• Reading data interactively
Working with files
• Reading and writing files
• Error handling, exceptions
Reading data from the Internet
• Fetching web page content
• Data processing
• Web Services
Reading and writing files (CSV, Excel)
• Import/export of spreadsheet data
• Exercises: sales report analysis, employee attendance list

Module 6 – Using Artificial Intelligence
Introduction to AI – Large Language Models (LLMs)
• AI – an old acquaintance (neural networks, Machine Learning)
• LLMs – the (r)evolution of AI systems’ capabilities
Using AI for code generation
• Popular models
• Examples of usage, how to write effective prompts, context, tokens, cost considerations
Using AI libraries in your own programs
• AI libraries, configuration, API keys
• AI agents
• Do Androids Dream of Electric Sheep? – Model Context Protocol

Module 7 – Review and Final Project
Review of material
• Summary of the most important topics, discussion of the final project
Final project
• Implementation of the final project – all approaches are allowed