| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| This course intends to introduce the concepts of Deep learning (DL) and its implementations. Also, each student should learn how to code and apply the algorithms so as to analyze the real-world problems. |
|
|
| topic Discussion/Production |
| Exercises |
| Discussion |
| Lecturing |
|
| Attendance |
| Oral Presentation |
| Assignment |
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
Introduction to Deep Learning (DL) |
| Week 2 |
Introduction to Deep Learning Type - Regression |
| Week 3 |
Introduction to Deep Learning Type - Classification
|
| Week 4 |
Implementation – Part I (Regression) & (Classification) |
| Week 5 |
Introduction to Ensemble Learning |
| Week 6 |
Implementation – Part I (Ensemble Learning) |
| Week 7 |
Implementation – Part II (Regression) & (Classification) |
| Week 8 |
Midterm-Project Presentation |
| Week 9 |
Implementation – Part II (Ensemble Learning) |
| Week 10 |
Introduction to Data Visualization |
| Week 11 |
Implementation – Data Visualization
|
| Week 12 |
Introduction to Semi-supervised Learning |
| Week 13 |
Implementation – Semi-supervised Learning |
| Week 14 |
Introduction to Transfer Learning |
| Week 15 |
Implementation – Transfer Learning |
| Week 16 |
Final-Project Presentation |
| Week 17 |
Self-directed Learning I - Participate in relevant lectures, workshops, or seminars using materials designated by the instructors. |
| Week 18 |
Self-directed Learning II - Participate in relevant lectures, workshops, or seminars using materials designated by the instructors. |
|
| Evaluation |
| Midterm-Project Presentation (30%), Final-Project Presentation (30%), Participation/Assignment (20%), In Class Presentation (20%) |
| Textbook & other References |
Main Textbook: Handout
● Zhang, A., Lipton, Z. C., Li, M., & Smola, A. J. (2023). Dive into deep learning. Cambridge University Press.
● Gulli, A., & Kapoor, A. (2017). TensorFlow 1. x Deep Learning Cookbook: Over 90 unique recipes to solve artificial-intelligence driven problems with Python. Packt Publishing Ltd. |
| Teaching Aids & Teacher's Website |
| The course materials would be found at ilearn. |
| Office Hours |
Tuesday 10:00-11:00 am or please contact the teacher to arrange a meeting time.
|
| Sustainable Development Goals, SDGs |
| 04.Quality Education | include experience courses：N |
|