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Data Science 3 with Python (303-3-21)

Instructors

Arvind Krishna

Meeting Info

Harris Hall 107: Mon, Wed 5:30PM - 6:50PM

Overview of class

Only Statistics majors, Data Science minors, and Statistics Ad Hoc Masters students assigned to take 303-3 in this quarter are able to register for this course.

The course introduces non-linear statistical models such as splines, and tree-based methods such as random forests, and boosting. It also introduces some statistical concepts such as model bias and variance.

Registration Requirements

STAT 303-2 or consent of the instructor

Learning Objectives

1) Translate a problem described in layman terms to a statistical modeling problem.
2) Identify the appropriate statistical modeling method for a given problem.
3) Developing and tuning model parameters of the statistical model.
4) Integrate statistical modeling as a component of the larger data science project.
5) Demonstrate proficiency with coding in the Python programming language, in the context of statistical modeling.
6) Collaborate in a team to develop a complete statistical modeling-based data science solution that answers a question of interest.

Teaching Method

Most of the lecture will be focused on explaining the course material, where conceptual content will be explained with power point presentations, and application of the concepts in solving real data science problems will be demonstrated with code on Jupyter notebook. There will be an in-class quiz in every lecture.

Evaluation Method

Evaluation will consist of weekly or bi-weekly assignments, a mid-term exam, a final exam, prediction problems, and in-class quizzes.

Class Materials (Required)

A laptop that is able to run Anaconda Navigator for Python programming

An Introduction to Statistical Learning with Applications in R' by James, Witten, Hastie, Tibshirani, Second edition, ISBN-13: 978-1461471370 (free e-book)

Class Materials (Suggested)

The Elements of Statistical Learning, by Trevor Hastie, Robert Tibshirani, and Jerome Friedman, Second edition, ISBN-13: 978-0387848570 (free e-book)

Class Attributes

Formal Studies Distro Area

Enrollment Requirements

Enrollment Requirements: Prerequisite: STAT 303-2 or consent of the instructor.
Add Consent: Department Consent Required