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Machine Learning & Artificial Intelligence Principles Overview
From robotics, speech recognition, & analytics, to finance & social network analysis, machine learning comprises one of the most useful scientific toolsets of our age. This course provides an overview of the core principles of machine learning using a hands-on, project-based curriculum. There is an intense focus on implementing popular machine learning algorithms to solve real problems using real data.
Who is this course for?
This is designed for people working in any number of data-intensive fields, including consulting, finance, IT, healthcare, & logistics, as well as for recent college graduates & entrepreneurs interested or specializing in those fields.
Considering the data science immersive bootcamp?
Part-Time Alumni can apply the amount of tuition paid for one part-time professional development course towards enrollment in an upcoming bootcamp upon admittance.
Prerequisites
Firm knowledge of the Python programming environment. There will not be any introductory Python material in this course. Students should not take this course if they are not comfortable coding in Python.
Basic understanding of vector & matrix algebra (how to add & multiply vectors/matrices), as well as basic understanding of the notion of a mathematical function (e.g., understanding what f(x)=x^2 or f(x) = sin(x) means).
Basic calculus & linear algebra is helpful but not required (e.g., how to take derivatives, what a linear system of equations is, etc.). A quick refresher on these topics will be provided. (Note: Knowledge of statistics is not required for this course.)
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