Timeroom: Fall 2024

Durham Paul College of Business&Econ :: Decision Sciences

DS 662 (01) - Programming for Business

Programming for Business

Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading

Class Size: 30
CRN: 12969

Introduces students to programming concepts. Covers fundamentals including functions, variable types, conditionals, and data structures. Students apply these concepts to a variety of business analytics problems including data collection, wrangling, reshaping, summarizing , and visualization.

Prerequisite(s): ADMN 410 with minimum grade of C-

Equivalent(s): DS 562

Only listed colleges in section: Paul College of Business&Econ

Classes not allowed in section: Freshman

Only listed majors in section: BUSADM:INFSYSAN

Instructors: Maryann Clark

Start Date	End Date	Days	Time	Location
8/26/2024	12/9/2024	TR	2:10pm - 3:30pm	PCBE G59

Additional Course Details:

This hands-on course empowers you with essential programming skills needed in today's tech-driven business world. Through interactive coding activities, you'll learn to use the Python programming language to extract, analyze, and visualize data to generate business insights. No coding experience required. You'll gain confidence with core programming concepts through collaborative practice. Join us to learn essential Python coding skills you'll rely on throughout your career.

Click to see: Syllabus

Durham Paul College of Business&Econ :: Decision Sciences

DS 671 (01) - Data Visualization and Prescriptive Analytics

Data Viz & Prescript Analytics

Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading

Class Size: 30
CRN: 12965

The course focuses on Descriptive and Prescriptive Analytics. Students gain modeling and data analysis and visualization skills necessary to address a wide variety of business problems. In Descriptive Analytics, students learn principles of data visualization, data cleanup and wrangling, advanced data analysis and visualization tools, and dashboard design. In Prescriptive Analytics, students learn advanced spreadsheet modeling/programming, formulating and solving a variety of optimization problems, and performing sensitivity analysis.

Prerequisite(s): ADMN 410 with minimum grade of C- and ADMN 510 with minimum grade of C-

Equivalent(s): DS 766

Mutual Exclusion : SC 671

Classes not allowed in section: Freshman

Instructors: Roger Grinde

Start Date	End Date	Days	Time	Location
8/26/2024	12/9/2024	MW	2:10pm - 3:30pm	PCBE 235

Click to see: Booklist

Durham Paul College of Business&Econ :: Decision Sciences

DS 673 (01) - Database Management

Database Management

Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading

Class Size: 30
CRN: 12967

Provides students with the skills necessary to understand the database environment of the firm. Topics include data models, normalization, SQL, data warehouses, and nosQL databases. Students learn to design and implement moderately complex relational databases in multi-user, client/server environments.

Prerequisite(s): ADMN 410 with minimum grade of C-

Equivalent(s): DS 773

Classes not allowed in section: Freshman

Instructors: Ermira Zifla

Start Date	End Date	Days	Time	Location
8/26/2024	12/9/2024	MW	11:10am - 12:30pm	PCBE 235

Click to see: Booklist

Durham Paul College of Business&Econ :: Decision Sciences

DS 741 (01) - Private Equity/Venture Capital

Private Equity/Venture Capital

Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading

Class Size: 40
CRN: 10712

The focus is private equity in the context of financing innovation especially from the investor?s perspective. This course covers screening entrepreneurial ideas and business plans through the spectrum of entrepreneurial financing stages from seed, start-up, later-stage financing, to acquisition/buyouts and IPOs. Students will research, discuss and present state-of-the-art analyses and practices and have exclusive access to PitchBook database that provides users intelligence on the private markets, angels, venture capital, mergers & acquisitions, and private companies.

Prerequisite(s): ADMN 570 with minimum grade of C-

Classes not allowed in section: Sophomore

Only listed majors in section: BUSADM:ES

Instructors: Lisa Keslar

Start Date	End Date	Days	Time	Location
8/26/2024	12/9/2024	TR	11:10am - 12:30pm	PCBE 175

Durham Paul College of Business&Econ :: Decision Sciences

DS 742 (01) - Internship in Entrepreneurial and Management Practice

Internshp Entreprenr &Mgt Prac

Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading

Class Size: 40
CRN: 10828

Involves working for leading companies and dynamic entrepreneurs, as well as classroom instruction. The priority experiential, real-world, and real-time learning in the high-growth environment of entrepreneurial ventures. Focus on several topic areas, including venture capital.

Section Comments: See Laura Hill in Room 236 to get permission for this course.

Department Approval Required. Contact Academic Department for permission then register through Webcat.

Classes not allowed in section: Freshman

Only listed majors in section: BUSADM:ES

Instructors: Lisa Keslar

Start Date	End Date	Days	Time	Location
8/26/2024	12/9/2024	TR	3:40pm - 5:00pm	PCBE 135

Durham Paul College of Business&Econ :: Decision Sciences

DS 774 (01) - E-Business

E-Business

Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading

Class Size: 30
CRN: 10711

This course immerses students in the intersecting realms of technology and business. Students will explore key domains such as Artificial Intelligence, Cybersecurity, Global e-Business, Application Design, and Enterprise Systems, engaging in a hands-on, collaborative curriculum. Students will develop a strategic perspective on using IT innovations to drive business value, tackle real-world challenges, and build in-demand skills for dynamic technology careers.

Prerequisite(s): ADMN 410 with minimum grade of C-

Cross listed with : DS 898.01

Classes not allowed in section: Freshman

Only listed majors in section: BUSADM:INFSYSAN

Instructors: Daniel Silverman

Start Date	End Date	Days	Time	Location
8/26/2024	12/9/2024	T	5:10pm - 8:00pm	PCBE 235

Durham Paul College of Business&Econ :: Decision Sciences

DS 801 (03) - Business Intelligence

Business Intelligence

Credits: 3.0
Term: Fall 2024 - Term 1 (08/26/2024 - 10/18/2024)
Grade Mode: Letter Grading

Class Size: 32
CRN: 15651

This course is designed to introduce students to the skills needed to succeed in today's big data environment through the application of data management techniques, business-oriented hands-on cases and exercises. Students will acquire concepts and application of data management techniques, business-oriented hands-on cases and exercises. Students will acquire concepts and techniques in the theory, design, and implementation of relational databases and Data Warehousing (DW) systems, queries in Structured Query Language (SQL), next generation query language (NoSQL).

Instructors: Jing Wang

Start Date	End Date	Days	Time	Location
8/26/2024	10/18/2024	M	2:10pm - 5:30pm	PCBE G45

Durham Paul College of Business&Econ :: Decision Sciences

DS 802 (02) - Probability and Simulation

Probability and Simulation

Credits: 3.0
Term: Fall 2024 - Term 1 (08/26/2024 - 10/18/2024)
Grade Mode: Letter Grading

Class Size: 40
CRN: 13902

The course is designed to provide an introductory understanding of the fundamentals of uncertainty quantification in business decision making. The course will serve as a building block for subsequent course work in inferential statistics, predictive analytics, and time series analysis. The topics include the axioms of probability theory, random variables, probability distributions, random variable generation using simulation methods, and system simulation for relevant business applications (e.g. inventory management, supply chain management, and staffing in call centers). An introduction to the programming language R will be part of the learning experience.

Only listed majors in section: BUSINESS ANLYT

Instructors: Tevfik Aktekin

Start Date	End Date	Days	Time	Location
8/26/2024	10/18/2024	M	8:10am - 11:30am	PBLANE 216

Durham Paul College of Business&Econ :: Decision Sciences

DS 803 (02) - Fundamentals of Statistical Analysis

Fundamentals of Statistical

Credits: 3.0
Term: Fall 2024 - Term 2 (10/28/2024 - 12/20/2024)
Grade Mode: Letter Grading

Class Size: 40
CRN: 13903

The course is designed to introduce the fundamentals of statistics needed for solving business analytics problems. The course will mainly cover the broadly defined subjects of random sampling, likelihoods, estimation using maximum likelihood, Bayesian inference using priors, computational statistics methods, interval estimation, hypothesis testing for continuous data, Gaussian linear models, and model diagnostics. The course will conclude with a brief introduction to nonparametric analysis.

Prerequisite(s): DS 802 with minimum grade of B-

Only listed majors in section: BUSINESS ANLYT

Instructors: Burcu Eke Rubini

Start Date	End Date	Days	Time	Location
10/28/2024	12/20/2024	W	8:10am - 11:30am	PBLANE 216

Durham Paul College of Business&Econ :: Decision Sciences

DS 804 (03) - Exploration and Communication of Data

Communication of Data

Credits: 3.0
Term: Fall 2024 - Term 2 (10/28/2024 - 12/20/2024)
Grade Mode: Letter Grading

Class Size: 40
CRN: 15654

The goal of this course is to expose students to techniques and technologies that will enable them to collect, harvest and transform unstructured and structured data into useful business insights. The first half of the course deals with data management and provides an introduction to data types and sources, data acquisition and harvesting tools and techniques and effective strategies and methods for data aggregation and analysis. In the second half of the course, students learn about the theoretical underpinnings of data visualization and use a variety of software tools to visualize business data in order to generate insightful information that facilitates effective business decision making.

Instructors: Kholekile Gwebu

Start Date	End Date	Days	Time	Location
10/28/2024	12/20/2024	M	2:10pm - 5:30pm	PBLANE 216