Automated Machine Learning and Deep Learning with Python

Machine learning (ML) and deep learning (DL) have taken the world by storm. Organizations understand better than ever that they have a lot of data and can use it for their benefit. ML and DL algorithms can predict sales numbers, fight customer churn, create client profiles, predict the weather, uncover fraud, and so much more. Professionals who are able to help organizations achieve these goals are in great demand, but the field requires a very specific set of skills, and acquiring them can take time. The rise of automated libraries, however, has provided new opportunities for people without advanced training to become masters of their own machine learning projects.

Join expert Stijn Van Hijfte to learn the basics of machine and deep learning techniques and their implementations in Python. You’ll explore automated libraries and learn to implement fast solutions for the best possible model in a structured manner. At the same time, you’ll gain insights into the winning model (type, structure, and more).

Hands-on learning with Jupyter notebooks

All exercises and labs are provided as Jupyter notebooks—interactive documents that combine live code, equations, visualizations, and narrative text. There's nothing to install or configure; just click a link and get started! And you can revisit them anytime after class ends to practice and refine your skills.