Welcome
This is the course materials site for Fullstack Academy AI/ML cohort 2605.
Use the Notebooks page to find and download activity and demo notebooks for each lesson. Use the Resources section for reference guides covering tools, commands, and environment setup.
Notebooks
How to download a notebook
- Click download next to a notebook to save the
.ipynbfile directly. - Open the downloaded file in VS Code.
Click view to open the notebook on GitHub first.
Unit 1: Python fundamentals
| Lesson | Topic | Type | Notebook |
|---|---|---|---|
| Bonus session | Introduction to Python | Demo | view · download |
| Lesson 4 | String methods, file I/O, and error handling | Demo | view · download |
| String methods, file I/O, and error handling | Activity | view · download | |
| String methods, file I/O, and error handling | Activity solution | view · download | |
| Lesson 5 | Loops and conditionals | Demo | view · download |
| Loops and conditionals | Activity | view · download | |
| Loops and conditionals | Activity solution | view · download | |
| Lesson 6 | Functions | Demo | view · download |
| Functions | Activity | view · download | |
| Functions | Activity solution | view · download |
Unit 2: Data science fundamentals
| Lesson | Topic | Type | Notebook |
|---|---|---|---|
| Lesson 9 | NumPy | Demo | view · download |
| NumPy | Activity | view · download | |
| NumPy | Activity solution | view · download | |
| Lesson 10 | Pandas | Demo | view · download |
| Pandas | Activity | view · download | |
| Pandas | Activity solution | view · download | |
| Lesson 11 | Data visualization | Demo | view · download |
| Data visualization | Activity | view · download | |
| Data visualization | Activity solution | view · download | |
| Lesson 12 | Linear algebra & basic statistics | Intro | view · download |
| Linear algebra & basic statistics | Demo | view · download | |
| PCA & feature space | Demo | view · download | |
| Linear algebra & basic statistics | Activity | view · download | |
| Linear algebra & basic statistics | Activity solution | view · download | |
| Lesson 13 | Probability distributions | Demo | view · download |
| Probability distributions | Activity | view · download | |
| Probability distributions | Activity solution | view · download | |
| Lesson 14 | Advanced statistics | Demo | view · download |
| Advanced statistics | Activity | view · download | |
| Advanced statistics | Activity solution | view · download | |
| Lesson 15 | Data wrangling | Demo | view · download |
| Data wrangling | Activity | view · download | |
| Data wrangling | Activity solution | view · download | |
| Lesson 16 | Feature engineering | Demo | view · download |
| Dimensionality reduction | Demo | view · download | |
| Explained variance | Demo | view · download | |
| Feature engineering | Activity | view · download | |
| Feature engineering | Data leakage 1 | view · download | |
| Feature engineering | Data leakage 2 | view · download | |
| Feature engineering | GPT 5.5 solution | view · download | |
| Feature engineering | Claude Opus 4.8 solution | view · download | |
| Feature engineering | Gemini 3.1 Pro solution | view · download | |
| Feature engineering | Claude Fable 5 solution | view · download | |
| Feature engineering | Instructor solution | view · download | |
| Feature engineering | zone6a (1st place) | view · download |
Unit 3: Machine learning
| Lesson | Topic | Type | Notebook |
|---|---|---|---|
| Lesson 19 | Regression | Supervised learning demo | view · download |
| Regression | Model comparison demo | view · download | |
| Regression | DIY 'model training' | view · download | |
| Regression | Activity | view · download | |
| Regression | Activity solution | view · download | |
| Lesson 20 | Classification | Demo | view · download |
| Classification | Naive Bayes Demo | view · download | |
| Classification | Activity (Kaggle) | view · download | |
| Lesson 21 | Ensemble learning | Demo | view · download |
| Lesson 22 | Unsupervised learning | Demo | view · download | Unsupervised learning | Activity | view · download | Unsupervised learning | Activity solution | view · download | Unsupervised learning | Full intrusion detection solution | view · download |
| Lesson 23 | Recommendation systems | Anime demo | view · download |
| Recommendation systems | MovieLens demo | view · download |
Unit 4: Deep learning
| Lesson | Topic | Type | Notebook |
|---|---|---|---|
| Lesson 26 | Artificial neural networks | Demo | view · download |
| Artificial neural networks | Activity | view · download | |
| Artificial neural networks | Activity solution | view · download | |
| Lesson 28 | Tensorflow regression | Demo part 1 | view · download |
| Tensorflow regression | Demo part 2 | view · download | |
| Tensorflow classification | Activity | view · download | |
| Tensorflow classification | Activity solution | view · download | |
| Lesson 29 | PyTorch regression | Demo | view · download |
| PyTorch regression | Activity part 1 | view · download | |
| PyTorch regression | Activity part 1 solution | view · download | |
| PyTorch image classification | Activity part 2 | view · download | |
| PyTorch image classification | Activity part 2 solution | view · download | |
| Lesson 32 | PyTorch CNN | Demo | view · download |
| PyTorch CNN | Activity | view · download | |
| PyTorch CNN | Activity solution | view · download | |
| Lesson 30 | Neural net optimizers | Demo | view · download |
| Lesson 31 | Neural net hyperparameter tuning | Demo | view · download |
| Neural net hyperparameter tuning | Activity | view · download | |
| Lesson 33 | Fine tuning | Demo | view · download |
| Lesson 34 | Object detection: YOLO26 | Demo | view · download | RNNs: alphabet model | Demo | view · download | RNNs: Twitter sentiment analysis | Demo | view · download | CNN-RNN hybrid: Twitter sentiment analysis | Activity | view · download | CNN-RNN hybrid: Twitter sentiment analysis | Activity solution | view · download |
| Lesson 36 | Autoencoders: image anomaly detection | Activity | view · download |
| Autoencoders: image anomaly detection | Activity solution | view · download |
Unit 6: NLP
| Lesson | Topic | Type | Notebook |
|---|---|---|---|
| Lesson 43 | Text data analysis | Demo | view · download |
| Text data analysis | Activity | view · download | |
| Text data analysis | Activity solution | view · download | |
| Lesson 44 | Text vectorization | Demo | view · download |
| Text vectorization | Activity | view · download | |
| Text vectorization | Activity solution | view · download | |
| Lesson 45 | Distributed representation | Demo | view · download |
| Distributed representation | Activity | view · download | |
| Distributed representation | Activity solution | view · download |