This course presents the main techniques used in machine learning and data analysis. It will cover all the necessary steps from handling raw data until having an intelligent system that can learn from experience. The students will be able to design, implement and evaluate computer systems that can learn to recognize patterns from data and make intelligent decisions. Furthermore, they will acquire the necessary skills for data analysis, preprocessing and visualization. The techniques will be explored using real-world data sets and different programming libraries such as Scikit-Learn, TensorFlow and Keras.
At the end of this course, the students will be able to:
Textbooks:
Tools:
Activity | Percent (%) |
---|---|
Midterm exam | 30% |
Activities | 10% |
Project/ HWs | 20% |
Final Exam | 40% |