Machine Learning Engineer Masterclass

Get hands-on experience of an ML Engineer in a 6-week Online program led by ML Tech Leads from top companies like Google and Meta. From learning generative AI, designing scalable ML systems to productionizing models, solve real-world problems that you can showcase on your career portfolio. Certification of course completion will be provided once you complete your capstone project.

Next Kick Off: July 29

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Our 6-Week Curriculum

Our class is 2 hours on Zoom from 9:00 to 11:00 A.M. PST / 12:00 to 2:00 P.M. EST every Saturday and Sunday for the first 5 weeks. On week 6, we have one 1-hour class where you showcase your capstone project.

Build a Recommender System

2 weeks - 4 classes

We will give you a real-world business case that requires a scalable recommender system. We will then teach you the math on the state-of-the-art ranking and retrieval models and how to address scaling challenges for large serving systems. Then we will teach you how to code, build and deploy the model using Tensorflow and Google’s Vertex AI.

Build large language models (LLM) and applications.

2 weeks - 4 classes

We will teach you the basics of language modeling, and a theoretical as well as practical understanding of generative AI. You will learn foundational concepts such as the attention mechanism and the transformer architecture, and build a language model like chatGPT from scratch. You will also get hands-on with emerging techniques such as prompt engineering, and build a question-answering chat assistant for your web pages on the internet (retrieval-augmented QA). Finally, we will show you how to build and deploy an LLM app to the cloud.

Build computer vision models and applications - face recognition system.

1 weeks - 2 classes

We will teach you the basics of computer vision, and an understanding of deep convolutional neural networks. You will learn the various CNN architectures and how to interpret what the model is doing and why. We will also teach you foundational generative AI concepts such as neural style transfer, stable diffusion and text-to-image generation. You will then build a face recognition system incorporating concepts such as face detection, representation and classification. Finally, you will learn how to design scalable, reliable and production-ready ML systems.

Complete a Capstone Project

1 week - 1 class

The final week is the capstone project week where you and peer group will choose an end-to-end ML project to build. You will present your solution in the final class and receive the AI Edge Certification upon delivery.

Our instructors

Damien Benveniste

After a PhD in theoretical physics, I started my Machine Learning career 10 years ago. I have been a Data Scientist, Machine Learning Engineer and Software Engineer. Until recently, I was a Machine Learning Tech Lead at Meta on the automation at scale of model optimization for Ads ranking.

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Abhishek Kumar

Former Software Engineer at Google, Research Scientist at Facebook and Technical Lead/engineering manager at Meta. I enjoy helping businesses make the best out of their data and have been an ML practitioner for over 10 years. I look forward to helping you all on your ML journey!

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Dan Lee

For the past 7 years, I have been an ML practitioner with experiences in leading ML projects at a startup and Google. I am now an ML instructor who will teach you the ins-and-outs of model development and deployment scalable ML systems. I look forward to working with you all!

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Enroll Now

Upskill in ML Engineering:

Enroll now

Our first class starts at 9:00 to 11:00 A.M. PST / 12:00 to 2:00 P.M. EST on July 29, 2023 (Saturday). We will meet at the same time every Saturday and Sunday for the first 5 weeks. Then, we will have our final week (week 6) with one class of capstone presentations on a Saturday.

What's included:

  • 21 hours of live classes

  • 4 end-to-end ML projects

  • 2 MLE instructors

  • Certification

  • Best practices in ML engineering

  • Cohort-based learning

  • Slack community access

  • Alumni community

Frequently asked questions

Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email at and we'll get back to you as soon as we can.

Am I ready for the masterclass?

This course is an advanced course in ML. We expect that you have had 1-year of professional experience in ML or completed a university degree in machine learning and/or data science.

What is the pre-requisite knowledge for the masterclass?

We expect that you already grasp ML fundamentals (e.g. the variance and bias trade-off), Python coding and neural network basics (e.g. back propagation).

How advanced in this course?

We will teach best practices in ML engineering in three major problem areas - recommender system, large language model, computer vision - and teach you ML system design and productionization.

How much math do I need to know?

The portion of the course will be dedicated on deconstructing the mathematics of SOTAs like Two-Tower Model, Transformer, and Reinforcement Learning. We expect that you have a base knowledge on how a neural network model works.

How much coding do I need to know?

We expect that you have at least 1-year experience in Python programming. Having a basic knowledge in TensorFlow is a plus as we will use this to develop and productionize models.

What is the tech stack covered in the course?

We will use Python, TensorFlow, Colab, Docker, Cloud (e.g. AWS), FastAPI.

I won't be able to attend some of the class, will the class be recorded? And, how long is the access?

Yes, the class will be recorded, and you will have access to it for a year.

What goes on in the Slack group?

You will gain access to community of instructors, your peers in current masterclass and alumni to exchange ideas and upskill in ML engineering together.

What happens after I purchase?

You will receive an onboarding content, including Slack group access and Zoom invites to your classes.

Can I get a company reimbursement?

Yes, we will send you an invoice that enables you to reimburse the purchase.

Is it possible to pay in installments?

Absolutely, we provide a payment plan that allows you to pay in 3 monthly installments.

How do I get the AiEdge certification?

After completion of the Capstone project on week 6, you will receive the AiEdge Certification which you can display on your professional portfolio (e.g. resume, LinkedIn).