Spelman College — Spring 2026
A comprehensive introduction to artificial intelligence, covering classical AI techniques and modern machine learning. Topics include search algorithms, game playing, constraint satisfaction, supervised learning, neural networks, and an introduction to deep learning and generative AI.
| Dates | Topics | AIMA | Materials | Assignment |
|---|---|---|---|---|
| 1/15 | Course Overview & Introduction to AI | Slides | ||
| 1/20–1/22 | Uninformed Search BFS, DFS, iterative deepening (IDDFS), search on maze problems |
Ch. 3.1–3.4 | Slides | HW1: Intro & Search |
| 1/27 | Informed Search Greedy best-first search, A*, admissible & consistent heuristics, IDA*, SMA* |
Ch. 3.5 | Slides | HW2: A* on 8-Puzzle |
| 1/29 | Game Playing & Adversarial Search Game trees, minimax algorithm, alpha-beta pruning |
Ch. 5.1–5.3 | Slides Minimax Viz | HW3: Minimax & Alpha-Beta |
| 2/3–2/5 | Stochastic Games & Monte Carlo Tree Search Probability basics, expectimax, explore/exploit tradeoffs, MCTS |
Ch. 5.5 | Slides 2048 Expectimax Autoplay | |
| 2/10 | Constraint Satisfaction Problems Backtracking, variable & value ordering, constraint propagation, arc consistency (AC-3) |
Ch. 6 | Slides | HW4: CSP Sudoku |
| 2/12–2/19 | Introduction to Machine Learning & Linear Regression ML fundamentals, linear regression, linear algebra review, normal equation |
Ch. 18 | Slides | HW5: Linear Regression |
| 2/24–3/3 | Cross-Validation & Gradient Descent Train-test split, polynomial regression, systems of equations, gradient descent |
Ch. 18 | Slides | |
| 3/17–3/26 | Classification & Logistic Regression Binary classification, logistic regression, decision boundaries |
Ch. 18 | Slides | HW6: Logistic Regression |
| 3/31–4/2 | Logistic Regression Evaluation Maximum likelihood estimation, precision, recall, F1, AUC |
Slides | ||
| 4/7 | Introduction to Neural Networks Perceptrons, activation functions, backpropagation |
Slides | ||
| 4/14–4/28 | Project Presentations | Project Description |
Assignments are Google Colab notebooks. To work on them, open the link and go to File → Save a copy in Drive.