I teach hard-core Machine Learning Engineering. Artificial | Artificial Intelligence

I teach hard-core Machine Learning Engineering.

Artificial Intelligence changed my life forever. There has never been a better time to build a career that will set you apart for the next 20-30 years.

I teach a program where I show people how to build Machine Learning systems.

My program is not an online course. It's not a group of videos you watch and a PDF you read.

My program is a 90-hour live class with an additional 13 Assignments and 9 projects material. It's tough.

While everyone wants to know what will happen in the next ten years, we won't waste time trying to predict that. Instead, we focus on what never changes.

The program is about the fundamental principles of building machine learning systems. It's about timeless ideas that will help you understand the future, whatever that is.

My guarantee is simple: you'll learn more than you've ever done before.

• Cohort #1 starts this Saturday on 13th January

You can join here: www.Aiindia.ai/bootcamp.

Some of the most frequently asked questions:

How much do I have to pay?

The cost to join is a one-time payment of ₹30k and for students ₹10k There are no recurrent payments. Once you join, you get lifetime access to all materials and a community of engineers who went through the program.

Is every class live, or can I watch them offline?

Classes are live, but you can watch the recordings at your own pace.

What are the prerequisites to join?

Ideally, you don't need any prerequisite to join our program only required is your dedication and commitment. You don't need a machine learning experience to learn.

What are some of the topics you'll cover?

We cover a lot, but here are 10 of the most important topics we'll discuss in class:

1. Framing machine learning problems
2. How to fine tune models and transfer learning.
3. Processing, training, deploying, inference pipelines
4. Offline evaluation and testing in production
5. Performing error analysis. Where to work next
6. Distributed training. Data and model parallelism
7. Pruning, quantization, and knowledge distillation
8. Model deployment. Online and batch inference
9. LLMs basics with training.
10. Python programming from scratch.

Here is the link to join: www.aiindia.ai/bootcamp