Learn Machine Learning in 12 Weeks While Building Your Portfolio

If you’ve ever wanted to learn Machine Learning, ML Deep Dive has designed our program to take people from a range of backgrounds to qualified ML Engineers in under 12 weeks.

When designed the curriculum for Machine Learning Deep Dive, we wanted two things:

  1. Provide you with expertise and confidence in building machine learning solutions to real problems.
  2. Help you start your machine learning career with a significant portfolio of finished products. We believe that a personal brand that shows your growth and possibilities as a professional is the single most decisive ingredient for your future success.

We want to make sure the course fits your current level, while at the same time pushing you to the next level. It’s a delicate equilibrium that we achieve through (1) practical courses, (2) guided projects and (3) lectures that introduce you to cutting edge Machine Learning.

You can see the complete syllabus with a week by week breakdown of what you’ll b working on here.

The Syllabus works in three blocks: :

The first block consists of classes by experienced professionals that will get you up to speed as a ML practitioner. You’ll learn and gain a deep understanding of the essential concepts while working on exciting, real-life tasks.

The second block consists of two projects that will provide you with the experience and confidence necessary to develop whole AI products from scratch. We have chosen the two most foundational and sought-after domains in modern-day machine learning: Computer Vision and Natural Language Processing. Those two projects will make up the first part of your final portfolio.

The Computer Vision project will build on exciting applications and state-of-the-art models that we will be discussing in our lectures while you build a state of the art deep learning network that can locate different objects in a set of images. 

We selected NLP for the second challenge because Deep Learning NLP is currently a less mature field than other domains: whereas there are pretty effective techniques to deal with many problems in areas such as image processing, most of the challenges in NLP are still open to active research.

Precisely for that reason, it is an exciting field that also happens to be of immediate practical importance. We will explore this promising area and discuss a whole array of impressive applications as we build a smart chatbot.

In the third block, the training wheels fall off and you’ll work on your own project. We’ll help you decide on an exciting application that showcases your expertise, and we will guide you through the process so that you end up with an impressive final product that you can show to the world, and that will finish up your personal portfolio.

Your project could range from classifying diseases to using Machine Learning for drug discovery. The reason you should learn Machine Learning isn’t that it’s going to benefit your career, but because you are passionate about solving the world’s hardest problems using one of humanity’s most powerful technologies.

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