The days of learning data science by passively consuming video lectures are over. Real learning takes place when a student’s hands are on the keyboard, writing code, working with data, and solving problems. If you agree, keep reading!
This interactive course dives into the fundamentals of artificial neural networks, from the basic frameworks to more modern techniques like adversarial models.
You’ll answer questions such as how a computer can distinguish between pictures of dogs and cats, and how it can learn to play great chess.
Using inspiration from the human brain and some linear algebra, you’ll gain an intuition for why these models work – not just a collection of formulas.
This course is ideal for students and professionals seeking a fundamental understanding of neural networks, or brushing up on basics.