![]() Grad school is no longer a necessity to work on machine learning during your career. However, machine learning is a specialization that has started to move from research into engineering. At first, I thought that the only way to work on machine learning during your career is to do research and or grad school. ![]() I became interested in machine learning as a sophomore. If you are more interested in one, learn what it takes to make a career of it. Have different versions of your resume for different specializations. Employers looking for specific roles such as these will prefer to see a related internship, course, or personal project on your resume. Your university may have elective courses to prepare you for networking, systems, web development, front end design, and graphics. Software engineering is not the only career path available to computer science majors. Use these to explore areas that you are interested in. You probably have more room in your schedule to take electives that interest you than you did before. Not all career specializations have the same prerequisites. You’ll have a much less stressful Senior year if you go into it with a job lined up for after you graduate. Companies would much rather hire a past intern than an entirely new applicant. Work experience doesn’t just make you a more attractive applicant. ![]() If not, this is the year to make that happen. If you were lucky, you had the chance to gain some work experience in a lab or during an internship. You’ve had two years to become a decent programmer and be exposed to a few different areas of computing. Your Junior year is the year to start making decisions.
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