a structured 3-year Applied AI Bachelor degree path involves covering foundational courses, specialized AI topics, practical applications, and supplementary resources. Here's a proposed outline:
| Course Code | Course Title | Duration | Effort | Resources |
|---|---|---|---|---|
| AI101 | Introduction to Artificial Intelligence | 12 weeks | Medium | MIT OpenCourseWare |
| CS101 | Introduction to Computer Science | 10 weeks | Medium | edX |
| MATH101 | Linear Algebra | 8 weeks | Medium | Khan Academy |
Books:
- "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig
- "Pattern Recognition and Machine Learning" by Christopher M. Bishop
| Course Code | Course Title | Duration | Effort | Resources |
|---|---|---|---|---|
| AI201 | Machine Learning | 12 weeks | High | Coursera |
| AI202 | Deep Learning | 10 weeks | High | Deep Learning Specialization |
| STAT201 | Probability and Statistics | 8 weeks | Medium | edX |
Books:
- "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
- "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
| Course Code | Course Title | Duration | Effort | Resources |
|---|---|---|---|---|
| AI301 | Natural Language Processing | 10 weeks | High | Stanford NLP Course |
| AI302 | Computer Vision | 10 weeks | High | CS231n: Convolutional Neural Networks for Visual Recognition |
| AI303 | AI Ethics and Responsible AI | 8 weeks | Medium | AI Ethics |
Books:
- "Speech and Language Processing" by Daniel Jurafsky and James H. Martin
- "Computer Vision: Algorithms and Applications" by Richard Szeliski
- Online Platforms: Kaggle, GitHub, TensorFlow Hub
- Journals and Conferences: IEEE Transactions on Pattern Analysis and Machine Intelligence, NeurIPS, CVPR
- Communities: AI & Ethics Community (IEEE), AI & Society Journal
This structure provides a comprehensive path through foundational principles, advanced techniques, and real-world applications in AI, supplemented by books, online courses, and additional resources to deepen understanding and practical skills development. Adjust the specific courses and resources based on the latest developments and personal interests in AI subfields.