Machine Learning Course Schedule

Week	Learning Activities	Assignment
1	Course Overview Introduction to Python Introduction to Machine Learning Quick Draw TensorFlow Playground	Install Python and Packages Data-Driven Engineering
2	Data Engineering (Part 1) Gather Data Statistics and Math Review Visualize Data Cleanse Data	Data Science with TCLab (1-4) Introduction TCLab Help 1. Overview 2. Import Data 3. Statistics 4. Visualize
3	Data Engineering (Part 2) Feature Engineering Imbalanced Data Scale Data Split Data	Data Science with TCLab (5-8) 5. Prepare Data 6. Regression 7. Features 8. Classification
4	Regression Linear Regression k-Nearest Neighbors Neural Network Regressor Support Vector Regressor XGBoost Regressor Case Study: Steel Plate Faults	k-Nearest Neighbors Regression Case Study Polymer Melt Flow Rate
5	Python Data-Access Text Data Analysis Audio Data Analysis	Automotive Monitoring
6	Classification Case Study: Concrete Strength Convolutional Neural Network	Logistic Regression Classification Case Study Sonar Detection
7	Data for Machine Learning	Data Collection with Sensors
8	Midterm Exam Review	Mid-Term Exam Additive Manufacturing

Week	Learning Activities	Assignment
9	Course Project	Project Proposal Data Visualization, Exploration, and Cleansing
10	Course Project	Progress Report Regression, Classification, Clustering Optimize Hyperparameters, Validation, Deployment Performance
11	Course Project	Final Report Project Report and Presentation

Week	Learning Activities	Assignment
12	Video Data Computer Vision Introduction Cascade Classifier Deep Learning Classification	Road Detection Texture Classification Crack Classification
13	Transformers, LSTMs, and LLMs	Database Access Similarity Search Python LLM with Ollama RAG LLM Integration
14	Deploy Machine Learning Cloud Access	Replace PID with LSTM
15	Final Exam Review	Final Exam Individual: Wind Power Group: Safety Surveillance

Machine Learning for Engineers