![]() ![]() ![]() These are functions commonly used by many in different scenarios in everyday programming tasks. In fact, my favorite part of creating the course was organizing the rich collection of my most useful Wolfram Language functions according to the MPDS narrative. I have found the power and flexibility of the Wolfram Language extremely helpful in this context. My experience as a programming instructor at Duke University and as a Wolfram certified instructor has given me valuable insights on introducing simple concepts to students with the help of computation and programming. My academic background is in communications engineering and computer science, and I developed a passion for applied data science while studying computational genomics at graduate school. ![]() I work as a training and development specialist with the Wolfram U team at Wolfram Research. In this post, I’ll give insight to the design of the course-the main goals, what topics are included and how to use the built-in interactivity to get the most out of your experience. Beyond doing data science, I’ve found that multiparadigm principles make both teaching and learning more effective. Our goal is to increase your understanding of data science while allowing you to take advantage of multiparadigm insights-whether you’re a newcomer working on a simple problem or an expert using well-established methods.Īs the content creator and instructor, I’d like to provide some background on myself and my approach to the MPDS course. This course gives a hands-on introduction to basic concepts of data science through a multiparadigm approach-using various types of data, modern analytical techniques, automated machine learning and a range of interfaces for communicating your data science results. A few weeks back, we announced Wolfram U’s latest open online course: Multiparadigm Data Science (MPDS).
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