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MIS X72T.3 MIS 372T.3  Fundamentals of Health IT  3 Hours

3 Lecture Hours  0 Lab Hours  
Management Information Systems 372T (Topic 3) and 373 (Topic: Fundamentals of Health IT) may not both be counted.
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T MIS 372T  Topics in Management Information Systems  3 Hours

3 Lecture Hours  0 Lab Hours  
Three lecture hours a week for one semester.
Pre/Corequisites: Additional prerequisites vary with the topic.  
Restrictions: Restricted to students in a business major.  
Grading: Student Option  
Repeatable for credit: May be repeated for credit when the topics vary.  
Academic Level: Upper Division  
Topic 1: Open Innovation. Management Information Systems 372T (Topic 1) and 373 (Topic 21) may not both be counted.

Topic 2: IT Audit and Security. Management Information Systems 372T (Topic 2) and 373 (Topic 22) may not both be counted.

Topic 3: Fundamentals of Health IT. Management Information Systems 372T (Topic 3) and 373 (Topic: Fundamentals of Health IT) may not both be counted.

Topic 4: Mobile Apps and Web Services. Explore mobile and web services technology models and architectures. Management Information Systems 372T (Topic 4) and 373 (Topic 24) may not both be counted. Additional prerequisite: Management Information Systems 333K.

Topic 9: Enterprise Computing. Management Information Systems 372T (Topic 9) and 373 (Topic 19) may not both be counted. Additional prerequisite: Management Information Systems 333K, or equivalent programming experience.

Topic 11: Advanced Analytics Programming. Focus on data analysis using the Python programming language. Explore machine learning tasks such as classification and clustering. Only one of the following may be counted: Business Analytics 372 (Topic 1), 372T (Topic 11), Management Information Systems 372T (Topic 11), 373 (Topic 11). Same as: BAX 372T.11 Additional prerequisite: Business Analytics 304 or Management Information Systems 304. Restrictions: Restricted to students in a business major.

Topic 12: Information Technology for Supply Chains. Learn how information technology is used to coordinate supply chain activities across different industries. Only one of the following may be counted: Management Information Systems 373 (Topic 13), 372T (Topic 12), Operations Management 337 (Topic 4), 372T (Topic 12). Same as: O M 372T.12 Additional prerequisite: Management Information Systems 301, 301H, or 302F.

Topic 17: Health Care Analytics. Explore key management challenges and how data may be leveraged to guide decisions and improve operations, with the unifying theme of providing health care services in a manner that leads to lower cost and higher quality. Only one of the following may be counted: Business Analytics 372 (Topic 17), 372T (Topic 17), Management Information Systems 373 (Topic 26), 372T (Topic 17) Operations Management 337 (Topic 8), 372T (Topic 17). Same as: BAX 372T.17, O M 372T.17

Topic 22: Predictive Analytics and Data Mining. Introduction to data mining problems and tools to enhance managerial decision making at all levels of the organization. Discuss scenarios, including the use of data mining to support customer relationship management (CRM) decisions, decisions in the entertainment industry, financial trading, and even professional sports teams. Only one of the following may be counted: Business Analytics 372 (Topic 2), 372T (Topic 22), Management Information Systems 373 (Topic 17), 372T (Topic 22), Marketing 372 (Topic 22), 372T (Topic 22). Same as: BAX 372T.22, MKT 372T.22 Additional prerequisite: Statistics 301 or 301H.

Topic 23: Social Media Analytics. Introduction to social network analysis for business value using statistical optimization and decision theory. Analyze online search and conversation data for market sensing, sentiments, product quality, reputation, recommendations, and brand awareness. Only one of the following may be counted: Business Analytics 372 (Topic 23), 372T (Topic 23), Management Information Systems 372T (Topic 23), 373 (Topic 23). Same as: BAX 372T.23 Restrictions: Restricted to students in a business major.

Topic 24: Data-Driven Revenue Management. Use data-driven tactics and strategies to predict consumer demand and optimize price and capacity/inventory availability to maximize revenue or profit. Explore demand analytics and revenue management techniques, produce rigorous and practical insights, and develop data analysis and optimization skills, based on business cases, datasets, and exercises. Examine diverse contexts and industries, such as conventional retailing, e-commerce, airline/hotel, and contemporary platform and cloud services (e.g., Uber, Dropbox, Netflix, AWS), by utilizing software (Excel, R, or Python) to build models, conduct optimization, and develop insights for a variety of revenue management examples. Only one of the following may be counted: Business Analytics 372T (Topic 24), Management Information Systems 372T (Topic 24), Operations Management 372T (Topic 24). Same as: BAX 372T.24, O M 372T.24

Topic 25: User Generated Content Analytics. Focus on a gamut of questions ranging from strategic to operational matters pertaining to a firm's social media initiatives, metrics to capture relevant outcomes, and predictive analysis to link social media chatter to business performance. Only one of the following may be counted: Business Analytics 372 (Topic 4), 372T (Topic 25), Management Information Systems 372T (Topic 25), 373 (Topic 25). Same as: BAX 372T.25
  

MIS X72T.1 MIS 372T.1  Open Innovation  3 Hours

3 Lecture Hours  0 Lab Hours  
Management Information Systems 372T (Topic 1) and 373 (Topic 21) may not both be counted.
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.2 MIS 372T.2  IT Audit and Security  3 Hours

3 Lecture Hours  0 Lab Hours  
Management Information Systems 372T (Topic 2) and 373 (Topic 22) may not both be counted.
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.4 MIS 372T.4  Mobile Apps and Web Services  3 Hours

3 Lecture Hours  0 Lab Hours  
Explore mobile and web services technology models and architectures. Management Information Systems 372T (Topic 4) and 373 (Topic 24) may not both be counted.
Pre/Corequisites: Management Information Systems 333K.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.9 MIS 372T.9  Enterprise Computing  3 Hours

3 Lecture Hours  0 Lab Hours  
Management Information Systems 372T (Topic 9) and 373 (Topic 19) may not both be counted.
Pre/Corequisites: Management Information Systems 333K, or equivalent programming experience.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.11 MIS 372T.11  Advanced Analytics Programming  3 Hours

3 Lecture Hours  0 Lab Hours  
Focus on data analysis using the Python programming language. Explore machine learning tasks such as classification and clustering. Only one of the following may be counted: Business Analytics 372 (Topic 1), 372T (Topic 11), Management Information Systems 372T (Topic 11), 373 (Topic 11).
Same as: BAX 372T.11  
Pre/Corequisites: Business Analytics 304 or Management Information Systems 304.  
Restrictions: Restricted to students in a business major.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.12 MIS 372T.12  Information Technology for Supply Chains  3 Hours

3 Lecture Hours  0 Lab Hours  
Learn how information technology is used to coordinate supply chain activities across different industries. Only one of the following may be counted: Management Information Systems 373 (Topic 13), 372T (Topic 12), Operations Management 337 (Topic 4), 372T (Topic 12).
Same as: O M 372T.12  
Pre/Corequisites: Management Information Systems 301, 301H, or 302F.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.17 MIS 372T.17  Health Care Analytics  3 Hours

3 Lecture Hours  0 Lab Hours  
Explore key management challenges and how data may be leveraged to guide decisions and improve operations, with the unifying theme of providing health care services in a manner that leads to lower cost and higher quality. Only one of the following may be counted: Business Analytics 372 (Topic 17), 372T (Topic 17), Management Information Systems 373 (Topic 26), 372T (Topic 17) Operations Management 337 (Topic 8), 372T (Topic 17).
Same as: BAX 372T.17, O M 372T.17  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.22 MIS 372T.22  Predictive Analytics and Data Mining  3 Hours

3 Lecture Hours  0 Lab Hours  
Introduction to data mining problems and tools to enhance managerial decision making at all levels of the organization. Discuss scenarios, including the use of data mining to support customer relationship management (CRM) decisions, decisions in the entertainment industry, financial trading, and even professional sports teams. Only one of the following may be counted: Business Analytics 372 (Topic 2), 372T (Topic 22), Management Information Systems 373 (Topic 17), 372T (Topic 22), Marketing 372 (Topic 22), 372T (Topic 22).
Same as: BAX 372T.22, MKT 372T.22  
Pre/Corequisites: Statistics 301 or 301H.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.23 MIS 372T.23  Social Media Analytics  3 Hours

3 Lecture Hours  0 Lab Hours  
Introduction to social network analysis for business value using statistical optimization and decision theory. Analyze online search and conversation data for market sensing, sentiments, product quality, reputation, recommendations, and brand awareness. Only one of the following may be counted: Business Analytics 372 (Topic 23), 372T (Topic 23), Management Information Systems 372T (Topic 23), 373 (Topic 23).
Same as: BAX 372T.23  
Restrictions: Restricted to students in a business major.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.25 MIS 372T.25  User Generated Content Analytics  3 Hours

3 Lecture Hours  0 Lab Hours  
Focus on a gamut of questions ranging from strategic to operational matters pertaining to a firm's social media initiatives, metrics to capture relevant outcomes, and predictive analysis to link social media chatter to business performance. Only one of the following may be counted: Business Analytics 372 (Topic 4), 372T (Topic 25), Management Information Systems 372T (Topic 25), 373 (Topic 25).
Same as: BAX 372T.25  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

MIS X72T.24 MIS 372T.24  Data-Driven Revenue Management  3 Hours

3 Lecture Hours  0 Lab Hours  
Use data-driven tactics and strategies to predict consumer demand and optimize price and capacity/inventory availability to maximize revenue or profit. Explore demand analytics and revenue management techniques, produce rigorous and practical insights, and develop data analysis and optimization skills, based on business cases, datasets, and exercises. Examine diverse contexts and industries, such as conventional retailing, e-commerce, airline/hotel, and contemporary platform and cloud services (e.g., Uber, Dropbox, Netflix, AWS), by utilizing software (Excel, R, or Python) to build models, conduct optimization, and develop insights for a variety of revenue management examples. Only one of the following may be counted: Business Analytics 372T (Topic 24), Management Information Systems 372T (Topic 24), Operations Management 372T (Topic 24).
Same as: BAX 372T.24, O M 372T.24  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division