Timeroom: Spring 2021

Displaying 451 - 460 of 1722 Results for: Attributes = EUNH
Durham   Engineering&Physical Sciences :: Computer Science

CS 750 (01R) - Machine Learning

Machine Learning

Course Delivery Method: Scheduled meeting time, Remote Section, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   26  
CRN: 56972
An introduction to fundamental concepts and common methods in machine learning. In addition to theoretical topics, the course involves hands-on experience in making predictions using synthetic and real-world datasets. Prereq: MATH 539 or MATH 644, and Programming course or Permission of instructor.
You must sign up in the Dept Office before registering through WEBCAT.
Mutual Exclusion : MATH 738
Classes not allowed in section: Freshman, Sophomore
Instructors: Marek Petrik
Start Date End Date Days Time Location
2/1/2021 5/11/2021 MW 11:10am - 12:30pm ONLINE
2/1/2021 5/11/2021 F 1:10pm - 2:00pm ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 750 (1SY) - Machine Learning

Machine Learning

Course Delivery Method: Scheduled meeting time, Rotational Attendance, Online with some campus visits, EUNH
Credits: 4.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 53977
An introduction to fundamental concepts and common methods in machine learning. In addition to theoretical topics, the course involves hands-on experience in making predictions using synthetic and real-world datasets. Prereq: MATH 539 or MATH 644, and Programming course or Permission of instructor.
You must sign up in the Dept Office before registering through WEBCAT.
Mutual Exclusion : MATH 738
Classes not allowed in section: Freshman, Sophomore
Instructors: Marek Petrik
Start Date End Date Days Time Location
2/1/2021 5/11/2021 MW 11:10am - 12:30pm KING N121
2/1/2021 5/11/2021 F 1:10pm - 2:00pm ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 757 (01R) - Mathematical Optimization for Applications

Mathematical Optimization

Course Delivery Method: Scheduled meeting time, Remote Section, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   8  
CRN: 56973
This course introduces the foundations of mathematical optimization and reinforces them via applications. The content includes convex optimization, first and second-order methods, constrained problems, duality, linear and quadratic programming, as well as discrete and non-convex optimization. Applications will focus on machine learning methods but also include problems from engineering and operations research. Prereq: MATH 426; Programming proficiency in MATLAB, R, Java, C, Python, or equivalent.
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): MATH 757
Instructors: Marek Petrik
Start Date End Date Days Time Location
2/1/2021 5/11/2021 MWF 9:40am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 758 (1SY) - Algorithms

Algorithms

Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   50  
CRN: 54684
An introduction to important concepts in the design and analysis of algorithms and data structures, including implementation, complexity analysis, and proofs of correctness. Prereq: CS 515 and CS 659.
Section Comments: Cross-listed with CS 858
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Laura Dietz
Start Date End Date Days Time Location
2/1/2021 5/11/2021 TR 3:40pm - 5:00pm ONLINE
2/1/2021 5/11/2021 F 2:10pm - 3:00pm ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 775 (1SY) - Database Systems

Database Systems

Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 53634
Introduction to database management systems --- design, implementation, and usage --- with focus on the relational model. Data description, manipulation, and query language in the context of MySQL. Schema design and normalization; indexes, transaction processing. Web access of databases (PHP); overview of XML and noSQL systems. Prereq: CS 515.
You must sign up in the Dept Office before registering through WEBCAT.
Mutual Exclusion : IT 775
Instructors: Elizabeth Varki
Start Date End Date Days Time Location
2/1/2021 5/11/2021 MWF 9:10am - 10:00am ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 780 (1SY) - Topics

Topics in Computer Vision

Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 53615
Material not normally covered in regular course offerings. May be repeated for credit.
Section Comments: Full Title: Topics in Computer Vision
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Momotaz Begum
Start Date End Date Days Time Location
2/1/2021 5/11/2021 MW 3:40pm - 5:00pm ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 792 (1SY) - Senior Project II

Senior Project II

Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 2.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   45  
CRN: 51859
Continuation of CS 791: Senior Project I. Students complete the project by implementing their design. Students work in teams. Successful completion of this course fulfills the Capstone Experience requirement for Computer Science majors. Prereq: CS 791. Writing intensive.
You must sign up in the Dept Office before registering through WEBCAT.
Only listed majors in section: ANLYTC&DS:ANLY, ANLYTC&DS:DS, COMPUTER SCIENC, CS: ALGORITHMS, CS: CYBERSECRTY, CS: SYSTEMS, INFO TECH
Attributes: Writing Intensive Course
Instructors: Matthew Plumlee
Start Date End Date Days Time Location
2/1/2021 5/11/2021 MW 2:10pm - 3:30pm ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 827 (1SY) - Computer Security

Computer Security

Course Delivery Method: Scheduled meeting time, 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:   18  
CRN: 54686
Introductory course in the mechanism and implementation of techniques in computer security. Various fundamental security topics include cryptography, passwords, access control, protocols, software vulnerabilities and malware detection. Prereq: CS 520.
Section Comments: Cross-listed with CS 727
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 TR 11:10am - 12:30pm ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 850 (01R) - Machine Learning

Machine Learning

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:   4  
CRN: 56975
An introduction to fundamental concepts and common methods in machine learning. In addition to theoretical topics, the course involves hands-on experience in making predictions using synthetic and real-world datasets. Prereq: Statistics, Programming or permission of instructor.
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Marek Petrik
Start Date End Date Days Time Location
2/1/2021 5/11/2021 MW 11:10am - 12:30pm ONLINE
2/1/2021 5/11/2021 F 1:10pm - 2:00pm ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 850 (1SY) - Machine Learning

Machine Learning

Course Delivery Method: Scheduled meeting time, Rotational Attendance, Online with some campus visits, EUNH
Credits: 3.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 53978
An introduction to fundamental concepts and common methods in machine learning. In addition to theoretical topics, the course involves hands-on experience in making predictions using synthetic and real-world datasets. Prereq: Statistics, Programming or permission of instructor.
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Marek Petrik
Start Date End Date Days Time Location
2/1/2021 5/11/2021 MW 11:10am - 12:30pm KING N121
2/1/2021 5/11/2021 F 1:10pm - 2:00pm ONLINE