Schedule & Course Structure
Week 1
Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11 Week 12 Week 13 Week 14 Week 15 Optional |
Unit 01 | Introduction & Essentials
Unit 02 | Data Mining and CRISP-DM Unit 03 | Introduction to Descriptive & Predictive Analytics Unit 04 | Classification through Lazy Learning with k-NN Practicum 01 | Review Exam 01 Unit 05 | Classification through Naive Bayes Unit 06 | Classification through Decision Trees & Rules Unit 07 | Multiple & Logistic Regression Models Practicum 02 | Review Exam 02 Unit 08 | Neural Networks & Support Vector Machines Unit 09 | Finding Patterns & Groups of Data Practicum 03 | Review Exam 03 Unit 10 | Evaluating & Improving Model Performance Project (Signature Assignment) Final Exam Unit 11 | Analyzing Sentiments in Text |