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What do I need to do to become a machine learning engineer

I'm going into my first year of college, and I know I want something in computer science for my career, and machine learning really interests me.
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Ethan’s Answer

First, I would like to preface that I am not a ML engineer/scientist. But I believe the fundamental components to understanding the theories and practices of ML and AI will be gained by 1) Studying computer science and 2) Statistics. You'll definitely need a strong foundation in computer systems and writing code. In my experience there are some upper-level courses in many CS departments that can introduce you to ML. But also having a statistics/math background will help you truly understand the models that you'll deploy and when they are appropriate to use given the data you're working with and problem you're trying to solve. You may not necessarily need to understand the models as well as a statistician/researcher might if you're more interested in solving for how something works, as opposed to why it does. But it will be helpful nonetheless and make you a well-rounded engineer.

Of course, much knowledge will be gained by working in an ML team within a company/organization as an intern and after graduating. Some individuals will often opt for a masters as well to specialize even more, but this isn't essential.
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Leo’s Answer

I agree with Ethan: Computer Science and Statistics are usually general pre-requisites of Machine Learning. Your college should also offer some courses (usually advanced courses) to start you on the Artificial Intelligence path. After those courses, you might want to consider doing a Master's or even a PhD in one of the multiple fields in AI/ML.

Also try doing an internship somewhere where you'll be exposed to AI/ML, that also helps a lot in your career path.
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Alex’s Answer

Machine Learning is a hot topic these days. Along with a general computer science background, I have a few recommendations for those wanting to succeed in the AI space.

#1: Learn the tools of the trade - These include industry-leading tools and platforms. Python is a language you should learn. Learn and experiment with platforms like Apache Data Bricks. Create some ML models.

#2: Learn to work with data. Lots of data. There are lots of sample data sets you can use to experiment with - sets like taxi cab ride data in NYC and COVID data in the US. Learn how to make data models that work well for machine learning.

Machine learning, like anything else in the computer science field, requires a foundation, so take programming other CS classes, or get a good book on foundational subjects.

Alex recommends the following next steps:

Create an Azure or AWS account and experiment with open data sets using Azure Data Bricks
Follow sample machine learning modeling using Azure Data Bricks
Create your own machine learning models in Azure Data Bricks
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Mickael’s Answer

Hi Joshua,

Machine Learning is all about statistics, matrices modeling ... So it is maths (statistics) and maths(linear algebra) mostly. Then of course, there is the computer science part and how to use the right Machine Learning model based on what you want to do with it.
Any Computer Science school that teaches Machine Learning and Artificial Intelligence will also teaches the require mathematics topics.
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