Course Code: aibspk
Duration: 3 hours
Course Outline:

1. Introduction to AI

2. The Math behind AI
○ Classification
○ Regression
○ Optimization
○ Predictive modeling

3. AI System Architecture
○ Components of Machine Learning Model

  • Classifiers
  • Regressors
  • Optimizers
  • Simulators
  • Policy Learners
  • Segmenters

○ NLP
○ Vision

4. Working with Data
○ Data requirements
○ How to overcome common implementation hurdles?

5. Accuracy
○ Underfitting
○ Overfitting
○ Evaluation metrics

6. Hands on Lab
○ Use scikit-learn to solve machine learning classification and regression
problems