Timeroom: Spring 2022

Displaying 251 - 260 of 1213 Results for: Level = All Graduate

DPP 982 (1ON) - Project Implementation and Monitoring

Proj. Implementation & Monitor

Credits: 3.0
Term: Spring 2022 - E-term III (01/18/2022 - 03/11/2022)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 51737
Students will begin implementation activities in field placement communities. Regular progress reports ad online postings will be required. Prereq: DPP 980.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Only listed majors in section: COM DEV PLC PRT, DEV PLICY PRCT
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/18/2022 3/11/2022 Hours Arranged ONLINE

DPP 983 (1ON) - Project Evaluation

Project Evaluation

Credits: 3.0
Term: Spring 2022 - E-term IV (03/21/2022 - 05/12/2022)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 56811
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. Prereq: DPP 980.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Only listed majors in section: COM DEV PLC PRT, DEV PLICY PRCT
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
3/21/2022 5/12/2022 Hours Arranged ONLINE

DPP 990 (01) - Independent Study

Independent Study

Credits: 1.0 to 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 54508
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.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 6 credits.
Instructors: STAFF
Start Date End Date Days Time Location
1/25/2022 5/9/2022 Hours Arranged TBA
Durham   Paul College of Business&Econ :: Decision Sciences

DS 805 (01) - Statistical Learning

Statistical Learning

Credits: 3.0
Term: Spring 2022 - E-term III (01/18/2022 - 03/11/2022)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 54916
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. Prereq: DS 803.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF
Start Date End Date Days Time Location
1/18/2022 3/11/2022 M 5:40pm - 9:15pm PBLANE 216
Durham   Paul College of Business&Econ :: Decision Sciences

DS 806 (01) - Optimization Methods I

Optimization Methods I

Credits: 3.0
Term: Spring 2022 - E-term III (01/18/2022 - 03/11/2022)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 54917
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.)
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF
Start Date End Date Days Time Location
1/18/2022 3/11/2022 R 5:40pm - 9:15pm PBLANE 216
Durham   Paul College of Business&Econ :: Decision Sciences

DS 807 (01) - Modeling Unstructured Data

Unstructured Data

Credits: 3.0
Term: Spring 2022 - E-term IV (03/21/2022 - 05/12/2022)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 54918
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. Prereq: DS 805.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF
Start Date End Date Days Time Location
3/21/2022 5/12/2022 M 5:40pm - 9:15pm PBLANE 216
Durham   Paul College of Business&Econ :: Decision Sciences

DS 808 (01) - Optimization Methods II

Optimization Methods II

Credits: 3.0
Term: Spring 2022 - E-term IV (03/21/2022 - 05/12/2022)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 54919
This course introduces students to more advanced concepts and modeling techniques in mathematical programming. Topics to be covered include integer programming, nonlinear programming, multi-objective optimization, goal programming, and Monte Carlo simulation. Application areas include Marketing (e.g., pricing and revenue optimization), Finance (capital budgeting and portfolio optimization), and Operations management (e.g., production and inventory planning, shipping and distribution, routing, location selection, etc.). The course delivery will be a mix of lectures, hands-on problem solving, and case discussions. Prereq: DS 806.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF
Start Date End Date Days Time Location
3/21/2022 5/12/2022 R 5:40pm - 9:15pm PBLANE 216
Durham   Paul College of Business&Econ :: Decision Sciences

DS 809 (01) - Time Series Analysis

Time Series Analysis

Credits: 3.0
Term: Spring 2022 - E-term III (01/18/2022 - 03/11/2022)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 54920
The course is designed to introduce analytical techniques needed in the estimation and analysis of temporal (time series) data in various business disciplines. The course focuses on theoretical and application aspects of stationary/non-stationary univariate as well as multivariate time series models. Emphasis will be given to topics such as time series regression, random walks, ARIMA/SARIMA processes, ARCH/GARCH for modeling conditional volatility, Vector ARMA models, and transfer functions. Modern software implementation is fully integrated into the course. Some examples of the business application areas include demand forecasting, financial asset return modeling, stochastic volatility modeling of financial indexes and securities, mortgage default risk assessment, online webpage click-rate modeling, market share modeling. Prereq: DS 803.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF
Start Date End Date Days Time Location
1/18/2022 3/11/2022 W 5:40pm - 9:15pm PCBE 205
Durham   Paul College of Business&Econ :: Decision Sciences

DS 810 (1SY) - Enterprise Level Analytics

Enterprise Analytics

Credits: 3.0
Term: Spring 2022 - E-term IV (03/21/2022 - 05/12/2022)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 54921
This course is designed to be a capstone experience with emphasis on the integration of materials covered in prior courses. In addition, the course provides students with the necessary knowledge and skills to manage vast quantities of business data. By the end of the course students will understand how big data systems are developed and used to support the operations and decision-making functions within a business organization. The course begins with a framework for understanding big data systems are developed and used. It continues with an emphasis on "experiential learning" where students build big data systems using contemporary technologies such as Hadoop, MapReduce, Spark etc. Finally, students learn how to analyze large-scale data sets and reveal valuable business insights. As part of the capstone experience, students develop these systems in groups, make several presentations and discuss cases during the semester. Prereq: DS 801, DS 804, and DS 807.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Attributes: Scheduled meeting time, Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
3/21/2022 5/12/2022 T 5:40pm - 9:15pm ONLINE
Durham   Paul College of Business&Econ :: Decision Sciences

DS 898 (01) - Topics in Business Analytics

Top/Ped Analy: Regress Model

Credits: 3.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 56990
Special Topics; may be repeated. Pre- and co-requisite courses vary. Please consult time and room schedule for the specific 898 topics section you are interested in for details.
Section Comments: Full Title: Top/Predictive Analytics: Regression Model
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 12 credits.
Instructors: STAFF
Start Date End Date Days Time Location
1/25/2022 5/9/2022 W 5:10pm - 8:00pm PBLANE 216