How Math and Physics Majors Can Build Artificial Intelligence Careers

Those eager to learn something, anything new about computer programming, allows programming skill development (it doesn't matter for what purpose – ex: building a platform in Hadoop or working with SQL, Shogun, C#, Scikit, etc. Building some experience in Matlab, Octave, Scilab, etc is another sure way to become better exposed as something as complex as building code for ICA (Independent Component Analysis) can be handled in only a very few lines of code. I have met many very successful ML professionals who have developed their skills by self-learning, studying hard and applying their innate scientific skills to apply ML algorithms. Also, Matlab can get things done very quickly. ICA (ICA is a technique to separate linearly mixed sources) can be accomplished very quickly in spite of the significant work that would go into coding such analysis initially. One person I know who has a strong background in Math and Physics is a team leader at Goldman Sachs, having locked himself away for close to six months only to come out a darn good applied data scientist.