Ready to turn data into insight? In this hands-on lecture, you’ll learn the essential foundations of Python programming—from variables, functions, control flow, classes, and algorithmic thinking to working with the tools that power modern data science.

We’ll move from core programming concepts to real analytical workflows using NumPy, Pandas, Matplotlib, Seaborn, Plotly, and scikit-learn, giving you everything you need to explore, process, and visualize data with confidence.

You’ll also learn how Large Language Models (LLMs) can support you during coding: generating snippets, debugging, improving code style, and accelerating your learning process.

Along the way, you’ll gain familiarity with
🔥 fundamentals of memory representation, number systems, formal languages & simple algorithms
🔥 Python essentials: loops, conditionals, collections, list comprehensions, functions
🔥 classes, inheritance, modules & imports
🔥 complexity analysis, search & sorting algorithms
🔥 clean coding: PEP 8, docstrings, type annotations
🔥 practical workflows with Git, Conda environments, SQL, UML
🔥 powerful visualization and data tools

By the end, you’ll be able to write clean, structured Python code, analyze datasets, build expressive visualizations, and use AI tools to boost your productivity.

Join us and discover how Python—and a little help from LLMs—can unlock the full potential of your data!