3-Day AI/ML Workshop with Python and IoT
Day 1 – Theory & Background of Python in AI/ML
| Time | Session Topics Covered | Method |
|---|---|---|
| Day 1: Theory & Background of Python in AI/ML | ||
| 09:30 – 10:15 (45 min) | Kick-off & Workshop Overview: Introduction to workshop, objectives, real-world impact of AI/ML | Presentation + Q&A |
| 10:15 – 11:15 (1 hr) | Python Basics – Part 1: Python syntax, variables, operators, control flow (if-else, loops) | Live coding |
| 11:15 – 11:30 (15 min) | Break: Tea/coffee break | – |
| 11:30 – 12:30 (1 hr) | Python Basics – Part 2: Functions, data structures (lists, tuples, dictionaries), file handling | Hands-on coding |
| 12:30 – 01:15 (45 min) | Python Libraries for AI/ML: Intro to NumPy, Pandas, Matplotlib, Scikit-learn | Demo + practice |
| 01:15 – 02:00 (45 min) | Lunch Break: Relax & networking | – |
| 02:00 – 03:00 (1 hr) | AI/ML Foundations: AI vs ML vs DL, supervised vs unsupervised vs reinforcement learning, datasets, training/testing, overfitting | Presentation + discussion |
| 03:00 – 03:15 (15 min) | Break: Tea/snacks | – |
| 03:15 – 04:15 (1 hr) | Data Handling with Python: Data preprocessing, cleaning, handling missing values, transformations | Hands-on with Pandas |
| 04:15 – 05:15 (1 hr) | Exploratory Data Analysis (EDA): Data visualization with Matplotlib, patterns & trends | Hands-on mini-project |
| 05:15 – 05:30 (15 min) | Wrap-up & Q&A: Recap of Day 1, clarify doubts, prepare for Day 2 (projects) | Open discussion |
Day 2 – Hands-on ML Projects
| Time | Session Topics Covered | Method |
|---|---|---|
| Day 2: Hands-on ML Projects | ||
| 09:30 – 10:00 (30 min) | Recap & Setup: Quick recap of Day 1, setting up Jupyter/Colab, loading datasets | Discussion + setup |
| 10:00 – 11:15 (1 hr 15 min) | Project 1: Regression: Predict house prices (Linear Regression) → Data prep → Model training + evaluation (MSE, R²) | Guided hands-on |
| 11:15 – 11:30 (15 min) | Break: Tea/coffee | – |
| 11:30 – 12:45 (1 hr 15 min) | Project 2: Classification – Part 1: Spam/sentiment classification → Data preprocessing → Train models (Logistic Regression / Decision Tree) | Hands-on |
| 12:45 – 01:30 (45 min) | Lunch Break: Relax & networking | – |
| 01:30 – 02:45 (1 hr 15 min) | Project 2: Classification – Part 2: Evaluate models (confusion matrix, precision, recall, F1) → Compare results → Visualize performance | Hands-on |
| 02:45 – 03:00 (15 min) | Break: Tea/snacks | – |
| 03:00 – 04:15 (1 hr 15 min) | Project 3: Clustering (Unsupervised): Customer segmentation (K-Means algorithm) → Cluster visualization → Real-world applications | Hands-on |
| 04:15 – 05:00 (45 min) | Mini Challenge & Wrap-up: Teams apply ML workflow to a small dataset (choice of regression/classification) → Present quick results → Q&A, prep for Day 3 | Group activity + discussion |
Day 3 – AI/ML for IoT Applications
| Time | Session Topics Covered | Method |
|---|---|---|
| Day 3: AI/ML for IoT Applications | ||
| 09:30 – 10:00 (30 min) | Recap & Introduction to IoT: Review of Day 2 projects, overview of IoT ecosystem (sensors, devices, gateways, cloud/edge) | Presentation + discussion |
| 10:00 – 11:00 (1 hr) | Session 1: AI + IoT Integration: How AI models can be deployed on IoT devices → Edge AI vs Cloud AI → Data flow in IoT systems | Case study + demo |
| 11:00 – 11:15 (15 min) | Break: Tea/coffee | – |
| 11:15 – 12:30 (1 hr 15 min) | Session 2: Predictive Maintenance: IoT sensor data (temperature, vibration, energy) → Anomaly detection model → Predicting machine failures | Guided hands-on |
| 12:30 – 01:15 (45 min) | Lunch Break: Relax & networking | – |
| 01:15 – 02:30 (1 hr 15 min) | Session 3: Smart Environment Application: Example: Smart home energy prediction / smart health monitoring → Train ML model using IoT dataset → Evaluate performance | Hands-on project |
| 02:30 – 02:45 (15 min) | Break: Tea/snacks | – |
| 02:45 – 04:15 (1 hr 30 min) | Capstone Project (Team Work): Teams choose IoT dataset (smart agriculture, smart health, smart city) → Apply ML workflow (data prep → model → evaluation) → Prepare quick demo/presentation | Team project |
| 04:15 – 05:00 (45 min) | Presentations & Wrap-up: Team presentations of IoT projects → Key takeaways → Future of AI+IoT → Feedback & certification | Group activity + discussion |
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24 October 2025
