How to Get prepared for Job in Bachelor ? (AI)
For young people, just sorting out their career goals, AI offers a wealth of opportunities. So how do we prepare for jobs that don’t yet exist?
For Student:
Math and physics classes are where one learns the basic methods for AI, machine learning, data science, and many of the jobs of the future. Take all the math class you can possibly take, including Calc I, Calc II, Calc III, Linear Algebra, Probability, and Statistics. Computer science, too, is essential; you’ll need to learn how to program. Engineering, economics, and neuroscience are also helpful. You may also want to consider some areas of philosophy, such as epistemology, which is the study of what is knowledge, what is a scientific theory, and what does it mean to learn.
The goal in these classes is not simple rote memorization. Students must learn how to turn data into knowledge. This includes basic statistics, but also how to collect and analyze data, be aware of possible biases, and to be alert to techniques to prevent self-delusion through biased data manipulation.
Find a professor in your school who can help you make your ideas concrete. If their time is limited, you can also look toward senior PhD students or postdocs to work with.
Apply to PhD programs. Forget about the “ranking” of the school for now. Find a reputable professor who works on topics that you are interested in, or pick a person whose papers you like or admire. Apply to several PhD programs in the schools of these professors and mention in your letter that you’d like to work with that professor, but would be open to work with others.
Engage with an AI-related problem you are passionate about. Start reading the literature on the problem and try to think about it differently than what was done before. Before you graduate, try to write a paper about your research or release a piece of open source code.
#Source: #Facebook AI
For Student:
Math and physics classes are where one learns the basic methods for AI, machine learning, data science, and many of the jobs of the future. Take all the math class you can possibly take, including Calc I, Calc II, Calc III, Linear Algebra, Probability, and Statistics. Computer science, too, is essential; you’ll need to learn how to program. Engineering, economics, and neuroscience are also helpful. You may also want to consider some areas of philosophy, such as epistemology, which is the study of what is knowledge, what is a scientific theory, and what does it mean to learn.
The goal in these classes is not simple rote memorization. Students must learn how to turn data into knowledge. This includes basic statistics, but also how to collect and analyze data, be aware of possible biases, and to be alert to techniques to prevent self-delusion through biased data manipulation.
Find a professor in your school who can help you make your ideas concrete. If their time is limited, you can also look toward senior PhD students or postdocs to work with.
Apply to PhD programs. Forget about the “ranking” of the school for now. Find a reputable professor who works on topics that you are interested in, or pick a person whose papers you like or admire. Apply to several PhD programs in the schools of these professors and mention in your letter that you’d like to work with that professor, but would be open to work with others.
Engage with an AI-related problem you are passionate about. Start reading the literature on the problem and try to think about it differently than what was done before. Before you graduate, try to write a paper about your research or release a piece of open source code.
#Source: #Facebook AI
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