4 classes matched your search criteria.

Fall 2022  |  IDSC 4444 Section 001: Descriptive and Predictive Analytics (23223)

Instructor(s)
Class Component:
Lecture
Credits:
2 Credits
Grading Basis:
A-F only
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Times and Locations:
First Half of Term
 
09/06/2022 - 10/24/2022
Tue, Thu 01:45PM - 03:25PM
UMTC, West Bank
Carlson School of Management 2-224
Enrollment Status:
Open (34 of 48 seats filled)
Also Offered:
Course Catalog Description:
Descriptive and Predictive Analytics exposes students to a number of data mining and machine learning methods, including: exploratory methods (such as association rules and cluster analysis), predictive methods (such as K-NN and decision trees), and text mining methods. The course combines theoretical lectures with lab lectures, where the methods are practically implemented using the software R. prereqs: IDSC 3001; non-MIS majors also need IDSC 4110
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/23223/1229

Fall 2022  |  IDSC 4444 Section 002: Descriptive and Predictive Analytics (23307)

Instructor(s)
Class Component:
Lecture
Credits:
2 Credits
Grading Basis:
A-F only
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Times and Locations:
Second Half of Term
 
10/25/2022 - 12/14/2022
Mon, Wed 11:50AM - 01:30PM
UMTC, West Bank
Hanson Hall 1-105
Enrollment Status:
Open (33 of 48 seats filled)
Also Offered:
Course Catalog Description:
Descriptive and Predictive Analytics exposes students to a number of data mining and machine learning methods, including: exploratory methods (such as association rules and cluster analysis), predictive methods (such as K-NN and decision trees), and text mining methods. The course combines theoretical lectures with lab lectures, where the methods are practically implemented using the software R. prereqs: IDSC 3001; non-MIS majors also need IDSC 4110
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/23307/1229

Fall 2022  |  IDSC 4444 Section 003: Descriptive and Predictive Analytics (23419)

Instructor(s)
Class Component:
Lecture
Credits:
2 Credits
Grading Basis:
A-F only
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Times and Locations:
Second Half of Term
 
10/25/2022 - 12/14/2022
Mon, Wed 09:55AM - 11:35AM
UMTC, West Bank
Hanson Hall 1-105
Enrollment Status:
Open (28 of 48 seats filled)
Also Offered:
Course Catalog Description:
Descriptive and Predictive Analytics exposes students to a number of data mining and machine learning methods, including: exploratory methods (such as association rules and cluster analysis), predictive methods (such as K-NN and decision trees), and text mining methods. The course combines theoretical lectures with lab lectures, where the methods are practically implemented using the software R. prereqs: IDSC 3001; non-MIS majors also need IDSC 4110
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/23419/1229

Fall 2022  |  IDSC 4444 Section 004: Descriptive and Predictive Analytics (23420)

Instructor(s)
Class Component:
Lecture
Credits:
2 Credits
Grading Basis:
A-F only
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person
Times and Locations:
Second Half of Term
 
10/25/2022 - 12/14/2022
Tue, Thu 01:45PM - 03:25PM
UMTC, West Bank
Carlson School of Management 1-142
Enrollment Status:
Open (18 of 48 seats filled)
Also Offered:
Course Catalog Description:
Descriptive and Predictive Analytics exposes students to a number of data mining and machine learning methods, including: exploratory methods (such as association rules and cluster analysis), predictive methods (such as K-NN and decision trees), and text mining methods. The course combines theoretical lectures with lab lectures, where the methods are practically implemented using the software R. prereqs: IDSC 3001; non-MIS majors also need IDSC 4110
Class Description:
Student may contact the instructor or department for information.
Textbooks:
https://bookstores.umn.edu/course-lookup/23420/1229

ClassInfo Links - Fall 2022 Information and Decision Sci Classes

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