Fall 2025 Applied Data Science with Python
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Lecture 1 - Short History of AI

  • Lecture 1 - A Short History and Current State of Artificial Intelligence

Theme 1 - Python Programming

  • Lecture 2 - Data Types in Python
  • Lecture 3 - Statements, Files
  • Lecture 4 - Functions, Iterators
  • Lecture 5 - Object-Oriented Programming, Modules, Packages

Theme 2 - Data Engineering Pipelines

  • Lecture 6 - NumPy for Array Operations
  • Lecture 7 - Data Manipulation with pandas
  • Lecture 8 - Data Visualization with Matplotlib
  • Lecture 9 - Data Visualization with Seaborn
  • Lecture 10 - Databases and SQL
  • Lecture 11 - Data Exploration and Preprocessing

Theme 3 - Model Engineering Pipelines

  • Lecture 12 - Scikit-Learn Library for Data Science
  • Lecture 13 - Ensemble Methods
  • Lecture 14 - Artificial Neural Networks with Keras-TensorFlow
  • Lecture 15 - Convolutional Neural Networks with Keras-TensorFlow
  • Lecture 16 - Model Selection, Hyperparameter Tuning
  • Lecture 17 - Artificial Neural Networks with PyTorch
  • Lecture 18 - Natural Language Processing
  • Lecture 19 - Transformer Networks
  • Lecture 20 - NLP with Hugging Face
  • Lecture 21 - Large Language Models
  • Lecture 22 - Large Language Models (Part 2)
  • Lecture 23 - Reasoning Models
  • Lecture 24 - Agentic AI

Theme 4 - Model Deployment Pipelines

  • Lecture 25 - Introduction to Data Science Operations (DSOps)
  • Lecture 26 - Deploying Projects as Web Applications

Tutorials

  • Tutorial 1 - Working with Jupyter Notebooks
  • Tutorial 2 - Python IDEs, VS Code
  • Tutorial 3 - Terminal and Command Line
  • Tutorial 4 - Virtual Environments
  • Tutorial 5 - Google Colab
  • Tutorial 6 - Image Processing with Python
  • Tutorial 7 - TensorFlow, TensorFlow DataSets
  • Tutorial 8 - PyTorch
  • Tutorial 9 - GitHub
  • Tutorial 10 - Docker Containers
Fall 2025 Applied Data Science with Python
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© Copyright 2025, Alex Vakanski.

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