Timeroom: Spring 2024

Displaying 261 - 270 of 1286 Results for: Level = All Graduate

DPP 905 (01) - Fiscal Management for Development Organizations

Fiscal Management

Online Course Delivery Method: Online Asynchronous
Credits: 3.0
Term: Spring 2024 - Term 4 (03/25/2024 - 05/17/2024)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 52728
Budgeting, goal setting, financial planning and financial analysis for development organizations.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Only listed majors in section: COM DEV PLC PRT, COM DEV PLC PRT, DEV PLICY PRCT, GLB CON HMN SEC, PUBLIC ADMIN, PUBLIC ADMIN EX
Attributes: Online (no campus visits), EUNH
Instructors: Robrecht Vanrijkel, Sanjeev Sharma
Start Date End Date Days Time Location
3/25/2024 5/17/2024 Hours Arranged ONLINE

DPP 982 (01) - Project Implementation and Monitoring

Proj. Implementation & Monitor

Online Course Delivery Method: Online Asynchronous
Credits: 3.0
Term: Spring 2024 - Term 3 (01/23/2024 - 03/15/2024)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 51361
Students will begin implementation activities in field placement communities. Regular progress reports ad online postings will be required.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): DPP 980 and DPP 981
Only listed majors in section: COM DEV PLC PRT, COM DEV PLC PRT, DEV PLICY PRCT, GLB CON HMN SEC, PUBLIC ADMIN, PUBLIC ADMIN EX
Attributes: Online (no campus visits), EUNH
Instructors: Jolan Rivera, Sanjeev Sharma
Start Date End Date Days Time Location
1/23/2024 3/15/2024 Hours Arranged ONLINE

DPP 983 (01) - Project Evaluation

Project Evaluation

Online Course Delivery Method: Online Asynchronous
Credits: 3.0
Term: Spring 2024 - Term 4 (03/25/2024 - 05/17/2024)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 54036
This semester students will conduct an evaluation of their project and manage closure processes. At the end students will submit a final written report and present it to the faculty and peers. This final project and the final report detailing the project will serve as the capstone course of the program.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): DPP 980 and DPP 981 and DPP 982
Only listed majors in section: COM DEV PLC PRT, COM DEV PLC PRT, DEV PLICY PRCT, GLB CON HMN SEC, PUBLIC ADMIN, PUBLIC ADMIN EX
Attributes: Online (no campus visits), EUNH
Instructors: Jolan Rivera, Sanjeev Sharma
Start Date End Date Days Time Location
3/25/2024 5/17/2024 Hours Arranged ONLINE

DPP 990 (01) - Independent Study

Independent Study

Online Course Delivery Method: Online Asynchronous
Credits: 1.0 to 4.0
Term: Spring 2024 - Full Term (01/23/2024 - 05/06/2024)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 53258
Under the guidance of an MCD Faculty member, the Independent Study Course (DPP 990) provides students with the opportunity to study a unique topic in-depth that is not offered as a traditional course. Often this topic is a relevant aspect of their capstone project which they wish to explore in more depth.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 6 credits.
Only listed majors in section: COM DEV PLC PRT, COM DEV PLC PRT
Attributes: Online (no campus visits), EUNH
Instructors: Sanjeev Sharma
Start Date End Date Days Time Location
1/23/2024 5/6/2024 Hours Arranged ONLINE
Durham   Paul College of Business&Econ :: Decision Sciences

DS 805 (01) - Statistical Learning

Statistical Learning

Credits: 3.0
Term: Spring 2024 - Term 3 (01/23/2024 - 03/15/2024)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 53431
This course introduces students to statistical tools for modeling and identifying patterns in complex data sets. The goal of statistical learning is to develop predictions informed by data. Topics to be covered include Gaussian linear models, cross-validation techniques, penalized regression methods such as ridge and LASSO, nonlinear models, logistic regression, tree-based models including random forests, bagging, and boosting, and support vector machines. Application areas include Marketing (e.g., effectiveness of advertising and customer satisfaction), Financial Economics (valuation), and Operations Management (resource allocation). The course delivery will be a mix of lectures, readings/podcasts with discussion, and hands-on data analyses.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): DS 803
Instructors: Burcu Eke Rubini
Start Date End Date Days Time Location
1/23/2024 3/15/2024 R 2:10pm - 5:30pm PBLANE 216
Durham   Paul College of Business&Econ :: Decision Sciences

DS 805 (02) - Statistical Learning

Statistical Learning

Credits: 3.0
Term: Spring 2024 - Term 3 (01/23/2024 - 03/15/2024)
Grade Mode: Letter Grading
Class Size:   16  
CRN: 56832
This course introduces students to statistical tools for modeling and identifying patterns in complex data sets. The goal of statistical learning is to develop predictions informed by data. Topics to be covered include Gaussian linear models, cross-validation techniques, penalized regression methods such as ridge and LASSO, nonlinear models, logistic regression, tree-based models including random forests, bagging, and boosting, and support vector machines. Application areas include Marketing (e.g., effectiveness of advertising and customer satisfaction), Financial Economics (valuation), and Operations Management (resource allocation). The course delivery will be a mix of lectures, readings/podcasts with discussion, and hands-on data analyses.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): DS 803
Instructors: Burcu Eke Rubini
Start Date End Date Days Time Location
1/23/2024 3/15/2024 T 2:10pm - 5:30pm PCBE G45
Durham   Paul College of Business&Econ :: Decision Sciences

DS 806 (01) - Optimization Methods I

Optimization Methods I

Credits: 3.0
Term: Spring 2024 - Term 3 (01/23/2024 - 03/15/2024)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 53432
This course introduces students to fundamental quantitative methods for modeling, analyzing, and determining the best course of action in complex decision-making situations. Topics to be covered include decision trees and tables, price of uncertainty, utility theory, linear programming, LP sensitivity analysis, and network flow optimization. Application areas include Marketing and Operations management (e.g., advertising, production and inventory planning, project or personnel scheduling, shipping and distribution, routing, ride matching, etc.)
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Melda Ormeci Matoglu
Start Date End Date Days Time Location
1/23/2024 3/15/2024 M 2:10pm - 5:30pm NESM 125
Durham   Paul College of Business&Econ :: Decision Sciences

DS 806 (02) - Optimization Methods I

Optimization Methods I

Credits: 3.0
Term: Spring 2024 - Term 3 (01/23/2024 - 03/15/2024)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 56833
This course introduces students to fundamental quantitative methods for modeling, analyzing, and determining the best course of action in complex decision-making situations. Topics to be covered include decision trees and tables, price of uncertainty, utility theory, linear programming, LP sensitivity analysis, and network flow optimization. Application areas include Marketing and Operations management (e.g., advertising, production and inventory planning, project or personnel scheduling, shipping and distribution, routing, ride matching, etc.)
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Melda Ormeci Matoglu
Start Date End Date Days Time Location
1/23/2024 3/15/2024 W 5:40pm - 9:00pm PCBE 235
Durham   Paul College of Business&Econ :: Decision Sciences

DS 807 (01) - Modeling Unstructured Data

Unstructured Data

Credits: 3.0
Term: Spring 2024 - Term 4 (03/25/2024 - 05/17/2024)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 53433
This course introduces students to statistical and machine learning tools for modeling unstructured data; including emails, documents, text messages, and social media data. Topics to be covered include text mining, clustering, mixture models, deep learning, and topic models. The course integrates numerous applications to demonstrate practical approaches to analyzing large unstructured collections of data. Application areas include Marketing (Yelp and Trip Advisor reviews), Human Resources (health care plan analysis), Social Media (Twitter, YouTube, and Instagram). The course delivery will be a mix of lectures, readings/podcasts with discussion, and hands-on data analysis.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): DS 805
Instructors: Courtney Paulson
Start Date End Date Days Time Location
3/25/2024 5/17/2024 R 2:10pm - 5:30pm PBLANE 216
Durham   Paul College of Business&Econ :: Decision Sciences

DS 807 (02) - Modeling Unstructured Data

Unstructured Data

Credits: 3.0
Term: Spring 2024 - Term 4 (03/25/2024 - 05/17/2024)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 56834
This course introduces students to statistical and machine learning tools for modeling unstructured data; including emails, documents, text messages, and social media data. Topics to be covered include text mining, clustering, mixture models, deep learning, and topic models. The course integrates numerous applications to demonstrate practical approaches to analyzing large unstructured collections of data. Application areas include Marketing (Yelp and Trip Advisor reviews), Human Resources (health care plan analysis), Social Media (Twitter, YouTube, and Instagram). The course delivery will be a mix of lectures, readings/podcasts with discussion, and hands-on data analysis.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): DS 805
Instructors: Courtney Paulson
Start Date End Date Days Time Location
3/25/2024 5/17/2024 W 8:10am - 11:30am NESM G13