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What advice would you give to an undergraduate attempting to break into ML research right now?

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Jayden S. asked a question to Kelly W.

Category: Career Advice

Date asked: Friday, July 18, 2025

Last reviewed: Monday, July 21, 2025

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Kelly W.

research scientist

Great question! I think the most important thing is to Build a Strong Math and Programming Foundation. This includes:

  • Master the Fundamentals: A solid grasp of linear algebra, calculus, probability, and statistics is crucial. Many online courses (Coursera, edX, Udacity) offer excellent resources.
  • Learn Programming: Python is the dominant language in ML. Become proficient in it, including libraries like NumPy, Pandas, and Scikit-learn.
  • Understand ML Concepts: Take introductory and advanced ML courses.

In addition to that, it is important to Gain Hands-on Experience through

  • Personal Projects: Work on your own ML projects. This demonstrates initiative and allows you to apply your knowledge.
  • Contribute to Open Source: Contributing to open-source ML projects is a fantastic way to learn from experienced developers and build your Github portfolio.
  • Industry Internships: Seek internships at companies or research labs working in ML.
  • Research Opportunities: Leverage resources and network at your school and find opportunities to work with professors or grad students on ML research projects.

Monday, July 21, 2025

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