Timeroom: Spring 2021

Displaying 241 - 250 of 1175 Results for: Level = All Graduate
Durham   Engineering&Physical Sciences :: Computer Science

CS 980 (01) - Advanced Topics

Advanced Topics

Online Course Delivery Method: Rotational Attendance
Credits: 3.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 55984
Section Comments: Full Title: Advanced Topics in Distributed Systems
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Aleksey Charapko
Start Date End Date Days Time Location
2/1/2021 5/11/2021 TR 11:10am - 12:30pm KING N233
2/1/2021 5/11/2021 MW Hours Arranged TBA
Durham   Engineering&Physical Sciences :: Computer Science

CS 980 (01R) - Advanced Topics

Advanced Topics

Online Course Delivery Method: Scheduled meeting time, Remote Section, Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 56979
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Aleksey Charapko
Start Date End Date Days Time Location
2/1/2021 5/11/2021 TR 11:10am - 12:30pm ONLINE
2/1/2021 5/11/2021 MW Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 998 (01) - Independent Study

Independent Study

Credits: 1.0 to 6.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
CRN: 50278
See instructor for permission then sign up in the dept office before registering through WEBCAT.
Instructors: STAFF
Start Date End Date Days Time Location
2/1/2021 5/11/2021 Hours Arranged TBA
Durham   Engineering&Physical Sciences :: Computer Science

CS 998 (07) - Independent Study

Independent Study

Credits: 1.0 to 6.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 55549
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Dongpeng Xu
Start Date End Date Days Time Location
2/1/2021 5/11/2021 Hours Arranged TBA
Durham   Engineering&Physical Sciences :: Computer Science

CS 999 (01) - Doctoral Research

Doctoral Research

Credits: 0.0
Term: Spring 2021 - Full Term* (02/01/2021 - 05/11/2021)
Grade Mode: Graduate Credit/Fail grading
CRN: 50303
Cr/F.
See instructor for permission then sign up in the dept office before registering through WEBCAT.
Instructors: STAFF
Start Date End Date Days Time Location
2/1/2021 5/11/2021 Hours Arranged TBA
Durham   Engineering&Physical Sciences :: Computer Science

CS 999 (07) - Doctoral Research

Doctoral Research

Credits: 0.0
Term: Spring 2021 - Full Term* (02/01/2021 - 05/11/2021)
Grade Mode: Graduate Credit/Fail grading
Class Size:   5  
CRN: 55360
Cr/F.
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Dongpeng Xu
Start Date End Date Days Time Location
2/1/2021 5/11/2021 Hours Arranged TBA
Durham   Graduate School :: Analytics

DATA 800 (1ON) - Introduction to Applied Analytic Statistics

Intro: Applied Analytic Stats

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term III (01/19/2021 - 03/12/2021)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 53379
This course is designed to give students a solid understanding of the experience in probability, and inferential statistics. The course provides a foundational understanding of statistical concepts and tools required for decision making in a data science, business, research or policy setting. The course uses case studies and requires extensive use of statistical software.
You must sign up in the Dept Office before registering through WEBCAT.
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
1/19/2021 3/12/2021 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 820 (1ON) - Programming for Data Science

Programming for Data Science

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term III (01/19/2021 - 03/12/2021)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 53376
In this class, students will build their foundational toolbox in data science: upon completion, students will be able to use the computer from the command line; practice version control with GIT & GitHub; gain a mastery of programming in Python; data wrangling with Python and perform an exploratory data analysis (EDA) in Python. All learning objectives are achieved through active application of these techniques to real world datasets. Pre- or Coreq: DATA 800.
You must sign up in the Dept Office before registering through WEBCAT.
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Phani Kidambi
Start Date End Date Days Time Location
1/19/2021 3/12/2021 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 821 (1ON) - Data Architecture

Data Architecture

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term IV (03/22/2021 - 05/13/2021)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 53377
In this class, students will learn the foundations of databases and large datasets: upon completion, students will be able to explore out-of-ram datasets though traditional SQL databases and NoSQL databases. Students will also be introduced to distributed computing. All learning objectives are achieved through active application of these techniques to world datasets. Prereq: DATA 800; DATA 820.
You must sign up in the Dept Office before registering through WEBCAT.
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Timothy Chadwick
Start Date End Date Days Time Location
3/22/2021 5/13/2021 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 822 (1ON) - Data Mining and Predictive Modeling

Data Mining & Pred Modeling

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term IV (03/22/2021 - 05/13/2021)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 53378
In this class, students will learn foundations of practical machine learning: upon completion, students will be able to understand and apply supervised and unsupervised learning in Python to build predictive models on real world datasets. Techniques covered include (but not limited to): preprocessing, dimensionality reduction, clustering, feature engineering and model evaluation. Models covered include: generalized linear models, tree-based models, bayesian models, support vector machines, and neural networks. All learning objectives are achieved through active application of these techniques to real world datasets. Prereq: DATA 800; DATA 820 Pre- or Coreq: DATA 821.
You must sign up in the Dept Office before registering through WEBCAT.
Mutual Exclusion : ADMN 872
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
3/22/2021 5/13/2021 Hours Arranged ONLINE