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CS82: Statistical Learning

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Prerequisites: Completion of CS01b or AP CS, or permission of instructor. Also requires Algebra II math experience.

CS82 is the most math heavy course offered at KTBYTE, and require students to have mastered self-guided learning. Students will learn tools to model and understand complex data sets, tools and algorithms that are commonly used for tackling "Big Data" problems. Covered concepts include descriptive statistics, linear/logistic regression, basic probability, clustering, naive bayes, q-learning, sk-learn libraries, and more. Unlike our other courses, this one is taught in Python.

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Course Content

  1. Data Formats
  2. Descriptive Statistics
  3. Plots
  4. Linear Regression
  5. Basis Functions
  6. Common problems with linear models
  7. Shrinkage, Ridge Regression
  8. Cross Validation, Dimensionality Reduction
  9. Classification: Logistic Regression
  10. Old Homework Assignments
Format: Web-conference

We Offer this Course in the below Durations

Meeting Location

Online Live Webconference

We will send you the webconference link once enrolled.

CS82 meets one hour a week over the semester. There are weekly homework assignments as well as a final project.

Wed Sept 06 - Wed Jan 24

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  • 8:40-9:40pm ET
  • Includes VM