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
See additional student enrollment and course instructor information to guide you in your decision making.

Details

Credits:
4
Requirements & Distribution:
BS
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)).
BS:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
Repeatability:
May not be repeated for credit.
Primary Instructor:

Description

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.

Schedule

DATASCI 415 - Data Mining and Statistical Learning
Schedule Listing
001 (LEC)
 In Person
30262
Open
7
 
-
TuTh 11:30AM - 1:00PM
002 (DIS)
 In Person
30263
Open
2
40Enrollment Management
-
F 8:30AM - 10:00AM
003 (DIS)
 In Person
30264
Open
2
40Enrollment Management
-
F 1:00PM - 2:30PM
004 (DIS)
 In Person
30265
Open
3
40Enrollment Management
-
F 2:30PM - 4:00PM

Textbooks/Other Materials

The partner U-M / Barnes & Noble Education textbook website is the official way for U-M students to view their upcoming textbook or course material needs, whether they choose to buy from Barnes & Noble Education or not. Students also can view a customized list of their specific textbook needs by clicking a "View/Buy Textbooks" link in their course schedule in Wolverine Access.

Click the button below to view and buy textbooks for DATASCI 415.001

View/Buy Textbooks

Syllabi

Syllabi are available to current LSA students. IMPORTANT: These syllabi are provided to give students a general idea about the courses, as offered by LSA departments and programs in prior academic terms. The syllabi do not necessarily reflect the assignments, sequence of course materials, and/or course expectations that the faculty and departments/programs have for these same courses in the current and/or future terms.

No Syllabi are on file for DATASCI 415. Click the button below to search for a different syllabus (UM login required)

Search for Syllabus

CourseProfile (Atlas)

The Atlas system, developed by the Center for Academic Innovation, provides additional information about: course enrollments; academic terms and instructors; student academic profiles (school/college, majors), and previous, concurrent, and subsequent course enrollments.

CourseProfile (Atlas)