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 Github and Introduction to Python Lecture
Lab 		Lecture
Lab
2 Web Scraping 1: Selenium
3 Web Scraping 2: APIs
4 Graph Visualization: matplotlib and seaborn
5 Dashboards Streamlit
6 Geospatial Analysis: Static Maps and Dynamic Maps
7 Raster Data
8 MIDTERM EXAM
9 Working with LLMs
10 Advanced Prompt Engineering
11 Agents
12 Hugging Face
13 Fine Tuning model of Hugging Face
14 Pararellel Computing - CUDA
14 Final Class: Recommendations and Projects
Instructors
Alex Quispe

Alexander Quispe

Paul Melo

Paul Melo

Jean Pool Nieto

Jean Pool Nieto

Time and location
Second Semester (August - December) 2025
Tuesday and Wednesday 7:30 - 9:20 AM
Class Meeting: JOIN
Laboratory Meeting: JOIN
Microsoft Teams
Course Materials
Links of Material
Course Lecture
Laboratoy Material