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Shadid Haque
Shadid Haque

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Embarking on a Self-Taught Machine Learning Journey: From Software Engineer to ML Engineer

Hello world, I am Shadid. I have been a Software Engineer for the last 8 years. Although I was interested in Machine Learning and AI in college, I never had the opportunity or patience to pursue that passion.

Now, when the ML field grew exponentially in 2023, with the latest innovations in large language models, I have a terrible longing for the road not taken. What if I choose to study Machine learning? What if I decided to pursue my career as an ML engineer? What would have happened if I had gone to graduate school?

Being stupidly optimistic, I decided to learn about Machine learning independently.

Partly this crazy idea was also partly inspired by Scott Young’s ted talk video titled: “Can you get an MIT education for $2,000?”. Scott talks about how he finished a computer science degree just by following MIT curriculums and self studying. After. which he was also able to land a entry level position.

I Googled around for self-taught ML Engineers. I got quite a few mixed reviews from Reddit. At this point, I am not sure whether it is possible to be a self-taught ML engineer. The only way to figure it out was to try to attempt it myself. However, I am optimistic.

I plan on taking courses from open-source courses available online, such as MIT Open Courseware and Coursera. The goal is to teach myself everything I can within the next 6~8 months.

To be clear, my goal here is not to build the next groundbreaking model. I simply want to see if I can get an interview for a junior-level Machine Learning or Data Engineering job after this experiment. This is purely an experiment and I am not trying to transition into a role in ML. So, if you are interested, join me on my journey. I plan on journaling about it weekly and documenting everything that I study.

Another disclaimer: I am not starting from scratch. As I did my undergraduate degree in Computer Engineering, I understand some of the fundamentals needed to pull this off. I have solid background knowledge of single and multivariable calculus, linear algebra, and statistics, as I took these courses in school about a decade ago.

I am going to follow this learning roadmap. However, I am going to omit many of these courses. I am going to focus mainly on Machine Learning, Deep learning, and Transformer Architecture. 

https://roadmap.sh/ai-data-scientist

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For the first 4 weeks I am going to focus on finishing Machine Learning Specialization from Andrew Ng. The goal is to speed run through these first 3 courses and get a solid understanding of the basics.

That is all for today, see you in a week or two.

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