Python for Data Science
This course offers comprehensive training in Python, covering everything from the fundamentals of the language and version control with Git and GitHub to advanced techniques in data analysis and artificial intelligence. Participants will explore data collection and manipulation through web scraping with Selenium and API consumption, complemented by data visualization with Seaborn and geospatial analysis using dynamic maps. Additionally, the course introduces the use of Large Language Models (LLMs) in AI, highlighting their applications and ethical considerations. With a practical approach, this course prepares participants to develop projects in data science, advanced programming, and intelligent data analysis.
Discord Syllabus| Week | Title | Materials | Recordings |
|---|---|---|---|
| 1 | Introduction to Python | Lecture
Lab |
Lecture
Lab |
| 2 | Web Scraping 1: Selenium | Lecture
Lab |
Lecture
Lab |
| 3 | Web Scraping 2: APIs | Lecture
Lab |
Lecture
Lab |
| 4 | Graph Visualization: matplotlib and seaborn | Lecture
Lab |
Lecture
Lab |
| 5 | Dashboards Streamlit | Lecture
Lab |
Lecture
Lab |
| 6 | Geospatial Analysis: Static Maps and Dynamic Maps | Lecture
Lab |
Lecture
Lab |
| 7 | Raster Data | ||
| 8 | MIDTERM EXAM | ||
| 9 | Working with LLMs: Prompt Engineering | ||
| 10 | Working with LLMs: Retrieval-Augmented Generation (RAG) | ||
| 11 | Agents | ||
| 12 | Pararellel Computing - CUDA 1 | ||
| 13 | Pararellel Computing - CUDA 2 | ||
| 14 | FINAL EXAM |
Instructors
Time and location
Course Materials