To be a good data scientist, you need to know how to use data science and machine learning libraries and algorithms, such as NumPy, TensorFlow and PyTorch, to solve whichever problem you have at hand.

To be an excellent data scientist, you need to know how those libraries and algorithms work.

This is where our course "Machine Learning & Data Science Foundations Masterclass" comes in. Led by deep learning guru Dr. Jon Krohn, this first entry in the Machine Learning Foundations series will give you the basics of the mathematics such as linear algebra, matrices and tensor manipulation, that operate behind the most important Python libraries and machine learning and data science algorithms.

The first step in your journey into becoming an excellent data scientist is broken down as follows:

• Section 1: Linear Algebra Data Structures

• Section 2: Tensor Operations

• Section 3: Matrix Properties

We are currently filming the remaining linear algebra content (Section 4 on Eigenvectors and Eigenvalues and Section 5 on Matrix Operations for Machine Learning) and are aiming to have all of it released by the end of 2020. By the end of 2021, we plan to have released all 20 sections of the Machine Learning Foundations series, covering not only linear algebra, but also calculus, probability, statistics, algorithms, data structures, and optimization. Enrollment now includes free access to all of this future content.

Throughout each of the sections, you'll find plenty of hands-on assignments and practical exercises to get your math game up to speed!

Are you ready to become an excellent data scientist? See you in the classroom.