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