Deep learning (DL) is a family of the most powerful and popular machine learning (ML) methods and has wide real-world applications such as face recognition, machine translation, self-driving cars, recommender systems, and playing the Go game, etc. This course is designed for students either with or without an ML background. The course will cover fundamental ML, computer vision, and natural language problems and DL tools for solving the problems. The students will be able to use DL methods for solving real-world ML problems. The homework is mostly implementation and programming using the Python language and popular DL frameworks such as TensorFlow and Keras. Knowledge and skills in Python programming and linear algebra are strictly required. Probability theory, statistics, and numerical analysis are recommended but not required. Knowledge in machine learning and artificial intelligence is helpful but unnecessary.