Artificial Intelligence (AI)

Unit 1: Revisiting AI Project Cycle & Ethics: Problem scoping, data acquisition, data exploration, modeling, and ethical frameworks (bias and data privacy).

Unit 2: Advanced Concepts of Modeling: Rule-based vs. learning-based approaches, machine learning, and deep learning basics.

Unit 3: Evaluating Models: Measuring performance using metrics like accuracy, precision, recall, and F1-score.

Unit 4: Statistical Data: Basic statistics and data visualization concepts.

Unit 5: Computer Vision: Introduction to pixel processing, image features, and basic computer vision applications.

Unit 6: Natural Language Processing (NLP): Text normalization, Bag-of-Words, and TF-IDF models.