Bloomberg is the latest firm to launch a (free) online course in machine learning. And it’s definitely not meant for folks who aren’t great at math.
Indeed, Bloomberg’s Foundations of Machine Learning is meant for those tech pros with strong experience in machine learning and mathematics, such as financial analysts, senior project managers, and engineers with quite a few years of experience under their (proverbial) belts. It’s an offshoot of an internal “Machine Learning EDU” initiative already taken by 1,000 Bloomberg software engineers.
The course is taught by David Rosenberg, a data scientist in the Office of the CTO at Bloomberg; he’s also an instructor at NYU’s Center for Data Science. “In doing this, our goal is to help make valuable machine learning skills more accessible to people with a strong math background, including experienced software developers, experimental scientists, engineers and financial professionals,” read a new Bloomberg blog posting about the program.
Those taking the course should have solid knowledge of linear algebra, multivariate differential calculus, probability theory, and statistics. Also valuable: a computer-science background that includes understanding of data structures, algorithms, and advanced, proof-based mathematics. (Course assignments feature code in Python.) If you’re wondering whether you have the right background knowledge, consult this handy (and pretty tongue-in-cheek) mathematics assessment (PDF).
Actual lessons include an introduction to statistical learning theory, an examination of stochastic gradient descent and excess risk decomposition, and loss functions for regression and classification. Clearly this is not a course for total newbies, or those who panic when they read terms such as “convex optimization” and “Langrangian duality.” In addition to video, lessons come with slides, notes, concept checks, and references. Here’s the first one in the series:
For those interested in building deep knowledge of machine learning, other prominent companies offer online courses. Google, for example, has a (free) course with 25 lessons and more than 40 exercises, which you can finish in 15 hours or so; it features lots of video of Google engineers describing the nuances of machine learning. Online learning schools such as Udacity also have programs in machine learning, some of which are targeted at beginners. Never fear; everyone needs to start somewhere.