2 classes matched your search criteria.
IDSC 6444 is also offered in Spring 2025
IDSC 6444 is also offered in Fall 2024
IDSC 6444 is also offered in Spring 2024
IDSC 6444 is also offered in Fall 2023
IDSC 6444 is also offered in Spring 2023
IDSC 6444 is also offered in Fall 2022
IDSC 6444 is also offered in Spring 2022
IDSC 6444 is also offered in Fall 2021
Spring 2023 | IDSC 6444 Section 001: Business Analytics for Managers I (57271)
- Instructor(s)
- Class Component:
- Lecture
- Credits:
- 2 Credits
- Grading Basis:
- A-F only
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Class Attributes:
- Online Course
- Enrollment Requirements:
- MBA or Mgmt Science MBA
- Times and Locations:
- First Half of Term01/17/2023 - 03/13/2023Tue, Thu 09:55AM - 11:35AMUMTC, West BankCarlson School of Management 1-142
- Enrollment Status:
- Open (28 of 48 seats filled)
- Also Offered:
- Course Catalog Description:
- Use of information technologies to organize and analyze data to help managers make decisions about their business and the way they serve customers. Focused on data mining, the course also provides an orientation to statistical modeling, programming, and the design and testing of prototype systems and evaluation models, and an introduction to basic techniques in visualization, association rules, clustering, classification, regression, and elementary natural language processing. prereq: [IDSC 6041 or IDSC 6051 or MBA 6241], MBA student
- Class Description:
- The interaction between companies and their customers has changed dramatically in recent years. Customers and prospective customers want to interact with companies on their own terms, and even the business of loyal customers is no longer guaranteed. As a result, companies have realized that they need to understand their customers better and to be able to respond to various customer needs in a timely fashion. Business intelligence is the use of information technologies for gathering, storing, analyzing, and providing access to data to help managers make better decisions about their business and the way they serve customers. The innovative use of business intelligence technologies forms a powerful basis for competitive advantage in today's networked economy. The purpose of this course is to explain how technologies such as data mining, personalization, and recommender systems can help in many important business applications, such as new customer acquisition, developing customized product and service offerings, customer relationship management, fraud detection, and credit analysis. This course begins by covering these topics at a basic fundamental level for those who have little or no experience with these technologies, and builds on this foundation to provide a comprehensive exploration of a variety of business intelligence technologies.
- Who Should Take This Class?:
- Students seeking to develop a basic understanding of exploratory and predictive data mining techniques, and the appropriate application of each in real-world business settings. Students will learn the conceptual underpinnings of a variety of data mining algorithms. Students will also receive hands on experience applying these algorithms via lab sessions and homework assignments, employing contemporary industry tools. IDSC 6444 is reserved for MBA students. If you are a non-MBA student seeking to take this course, fill out the petition form found at goo.gl/9Y9PR5. Additional information, including petition deadlines, can be found at http://carlsonschool.umn.edu/degrees/master-business-administration/part-time-mba/admissions/mba-course-petition-form
- Learning Objectives:
- 1. Students will understand the process of introducing data mining and personalization technologies into the business processes which includes:Learning Outcomes• Building the business case for data mining and personalization• Deploying and managing business intelligence applications• Collecting relevant data• Applying data mining models to various business problems2. Students will learn about various data mining and personalization techniques, including decision trees, clustering, and business rule induction.3. Students will learn how the above techniques are applied in a variety of business applications and organizational settings.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/57271/1233
- Instructor Supplied Information Last Updated:
- 15 March 2017
Spring 2023 | IDSC 6444 Section 060: Business Analytics for Managers I (57083)
- Instructor(s)
- Class Component:
- Lecture
- Credits:
- 2 Credits
- Grading Basis:
- A-F only
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Class Attributes:
- Online Course
- Enrollment Requirements:
- MBA or Mgmt Science MBA
- Times and Locations:
- First Half of Term01/17/2023 - 03/13/2023Mon 05:45PM - 09:05PMUMTC, West BankCarlson School of Management 1-132
- Enrollment Status:
- Open (10 of 48 seats filled)
- Also Offered:
- Course Catalog Description:
- Use of information technologies to organize and analyze data to help managers make decisions about their business and the way they serve customers. Focused on data mining, the course also provides an orientation to statistical modeling, programming, and the design and testing of prototype systems and evaluation models, and an introduction to basic techniques in visualization, association rules, clustering, classification, regression, and elementary natural language processing. prereq: [IDSC 6041 or IDSC 6051 or MBA 6241], MBA student
- Class Description:
- The interaction between companies and their customers has changed dramatically in recent years. Customers and prospective customers want to interact with companies on their own terms, and even the business of loyal customers is no longer guaranteed. As a result, companies have realized that they need to understand their customers better and to be able to respond to various customer needs in a timely fashion. Business intelligence is the use of information technologies for gathering, storing, analyzing, and providing access to data to help managers make better decisions about their business and the way they serve customers. The innovative use of business intelligence technologies forms a powerful basis for competitive advantage in today's networked economy. The purpose of this course is to explain how technologies such as data mining, personalization, and recommender systems can help in many important business applications, such as new customer acquisition, developing customized product and service offerings, customer relationship management, fraud detection, and credit analysis. This course begins by covering these topics at a basic fundamental level for those who have little or no experience with these technologies, and builds on this foundation to provide a comprehensive exploration of a variety of business intelligence technologies.
- Who Should Take This Class?:
- Students seeking to develop a basic understanding of exploratory and predictive data mining techniques, and the appropriate application of each in real-world business settings. Students will learn the conceptual underpinnings of a variety of data mining algorithms. Students will also receive hands on experience applying these algorithms via lab sessions and homework assignments, employing contemporary industry tools. IDSC 6444 is reserved for MBA students. If you are a non-MBA student seeking to take this course, fill out the petition form found at goo.gl/9Y9PR5. Additional information, including petition deadlines, can be found at http://carlsonschool.umn.edu/degrees/master-business-administration/part-time-mba/admissions/mba-course-petition-form
- Learning Objectives:
- 1. Students will understand the process of introducing data mining and personalization technologies into the business processes which includes:Learning Outcomes• Building the business case for data mining and personalization• Deploying and managing business intelligence applications• Collecting relevant data• Applying data mining models to various business problems2. Students will learn about various data mining and personalization techniques, including decision trees, clustering, and business rule induction.3. Students will learn how the above techniques are applied in a variety of business applications and organizational settings.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/57083/1233
- Instructor Supplied Information Last Updated:
- 15 March 2017
ClassInfo Links - Spring 2023 Information and Decision Sci Classes
- To link directly to this ClassInfo page from your website or to save it as a bookmark, use:
- http://classinfo.umn.edu/?subject=IDSC&catalog_nbr=6444&term=1233
- To see a URL-only list for use in the Faculty Center URL fields, use:
- http://classinfo.umn.edu/?subject=IDSC&catalog_nbr=6444&term=1233&url=1
- To see this page output as XML, use:
- http://classinfo.umn.edu/?subject=IDSC&catalog_nbr=6444&term=1233&xml=1
- To see this page output as JSON, use:
- http://classinfo.umn.edu/?subject=IDSC&catalog_nbr=6444&term=1233&json=1
- To see this page output as CSV, use:
- http://classinfo.umn.edu/?subject=IDSC&catalog_nbr=6444&term=1233&csv=1
ClassInfo created and maintained by the Humphrey School of Public Affairs.
If you have questions about specific courses, we strongly encourage you to contact the department where the course resides.