Georgia Institute Of Technology - ISYE 6501OMSA_ISYE6501Syllabus-combined-Spring_2021v3

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Course Syllabus ISYE 6501 Introduction to Analytics Modeling Professor: Dr. Joel Sokol Course Description An introduction to important and commonly used models in Analytics, as well as aspects of... the modeling process. Prerequisites • Probability and statistics • Basic programming proficiency • Linear algebra • Basic calculus • A little background in R can be useful, but isn’t necessary if you’re willing to learn on the fly. Course Goals The most important thing you can learn from this course is not the memorization of any specific bit of material. Instead, I would like you to learn these skills: • Given a business (or other) question, select an appropriate analytics model to answer it, specify the data you will need to solve it, and understand what the model’s solution will and will not provide as an answer. • Given someone else’s use of analytics to address a specific business (or other) question, evaluate whether they have used an appropriate model (and appropriate data) and whether their conclusion is reasonable. Another goal of this course is for you to learn how to think though descriptions and usage of new models, so you can continue to learn throughout your career; new techniques will certainly be developed after you graduate, and we want you to be able to pick them up quickly. We will not cover the mathematics and algorithms under the hood, or deeper mastery of the modeling needed to set up the use of the technique. You can acquire those deeper levels of knowledge in elective courses. (In fact, we could spend an entire semester on many of the topics you’ll see in the course.) [Show More]

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