DATASCI 415 - Data Mining and Statistical Learning
Winter 2022, Section 001
Instruction Mode: Section 001 is  In Person (see other Sections below)
Subject: Data Science (DATASCI)
Department: LSA Statistics
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Requirements & Distribution:
Enforced Prerequisites:
(MATH 214 or MATH 217) and either (one of STATS 401, STATS 412, STATS 426) or (MATH/STATS 425 and (DATASCI 101 or STATS 206 or STATS 250 or STATS 280)).
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
May not be repeated for credit.
Primary Instructor:


This course covers the principles of data mining, exploratory analysis, and visualization of complex data sets, and predictive modeling. The presentation balances statistical concepts (such as model bias and over-fitting data, and interpreting results) and computational issues (including algorithmic complexity and strategies for efficient implementation). Students are exposed to algorithms, computations, and hands-on data analysis in weekly discussion sessions.


Course Requirements:

The evaluation will be based on weekly problem sets, one midterm exam, and a final project. The final project will be an individual project involving either data analysis using the methods covered in the course, or a simulation-based or analytical investigation of the properties of one of the methods covered in the course. Students will be expected to write a statement of their findings of approximately 3 pages in length, as well as providing clean and documented versions of their computer code,

Intended Audience:

The course can be used as an elective to satisfy the requirements of the statistics concentration, the applied statistics minor, and the statistics minor.

Class Format:

3 hours of lecture and 1 hour GSI-led discussion.


DATASCI 415 - Data Mining and Statistical Learning
Schedule Listing
001 (LEC)
 In Person
TuTh 11:30AM - 1:00PM
002 (DIS)
 In Person
40Enrollment Management
F 8:30AM - 10:00AM
003 (DIS)
 In Person
40Enrollment Management
F 1:00PM - 2:30PM
004 (DIS)
 In Person
40Enrollment Management
F 2:30PM - 4:00PM

Textbooks/Other Materials

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