Timeroom: Spring 2023

Displaying 151 - 160 of 379 Results for: Campus = Manchester

COMP 520 (M1) - Database Design and Development

Database Design & Development

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 56509
An introduction to developing database applications with business users. Topics include fundamentals of the relational model, structured query language, data modeling and database design and implementation. Students use a variety of database management system tools to model, code, debug, document, and test database applications. Students complete real-world team projects.
Equivalent(s): CIS 520, IT 505
Instructors: Jonathon Shallow
Start Date End Date Days Time Location
1/24/2023 5/8/2023 T 5:31pm - 8:30pm ONLINE

COMP 525 (M1) - Data Structures Fundamentals

Data Structures Fundamentals

Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 56511
Data structures and algorithms are fundamental to developing solutions for computational problems. In this course students design and implement data and functional abstractions; analyze and select appropriate data structures to solve computational problems; practice programming and software development techniques to implement computational solutions. Prereq: COMP 424 or COMP 425.
Equivalent(s): CS 416, CS 417
Instructors: Mihaela Sabin
Start Date End Date Days Time Location
1/24/2023 5/8/2023 T 1:01pm - 3:50pm PANDRA P132

COMP 560 (M1) - Ethics and the Law in the Digital Age

Ethics & Law in theDigital Age

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 51928
Examines classical and ethical and legal constructs as they pertain to current and topical issues. Students develop and articulate a personal point of view on a broad range of issues based on sound ethical principles and consider the impact of such views on co-workers, employers, and society in general. Topics also include: major social issues involving intellectual property, privacy, current U.S. and international relations relevant to ethical theories. The interplay between ethics and law is explored through current case studies and students formulate and support conclusions based on ethical constructs presented in class. Case study analysis is a major component in course delivery. Writing intensive.
Section Comments: Contact Professor Mike Jonas for permission
Only listed classes in section: Senior
Only listed majors in section: COMPINFOSYS, COMPUTER SCI, ELECENGRTECH, MECHENGRTECH
Attributes: Writing Intensive Course, Humanities(Disc)
Instructors: Benjamin Myler
Start Date End Date Days Time Location
1/24/2023 5/8/2023 R 5:31pm - 8:30pm ONLINE

COMP 570 (M1) - Statistics in Computing and Engineering

Statistics in Comp&Engineering

Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 53768
An introduction to tools from probability and statistics that are needed by computing and engineering professionals. Exploratory data analysis including graphic data analysis. discrete and continuous probability distributions, inference, linear regression, and analysis of variance, with applications from artificial intelligence, machine learning, data mining, and related topics. Project work and use of statistical software are an integral part of the course. Prereq: MATH 425.
Start Date End Date Days Time Location
1/24/2023 5/8/2023 T 5:31pm - 8:30pm PANDRA P126

COMP 690 (M1) - Internship Experience

Internship Experience

Online Course Delivery Method: Online with some campus visits, EUNH
Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 52666
The internship provides field-based learning experience through placement in a computing field. Students gain practical computing experience in a business, non-profit, or government organization. Under the direction of a faculty advisor, the student is expected to contribute to the information technology products, processes, or services of the organization. Majors only. May be repeated but no more than 4 credits may fill major requirements. Prereq: UMST 582.
Section Comments: Cross listed with COMP 891/COMP 892, DATA 690
Instructor Approval Required. Contact Instructor for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 8 credits.
Only listed majors in section: COMPINFOSYS, COMPUTER SCI
Instructors: Karen Jin
Start Date End Date Days Time Location
1/24/2023 5/8/2023 Hours Arranged ONLINE
1/24/2023 5/8/2023 M 9:01am - 11:50am PANDRA P301
Additional Course Details: 

Registering for academic credit does not complete your required internship approval process. Students must register and “request an experience” in the UNH online platform of Handshake once they have their internship. Visit https://app.joinhandshake.com/experiences/new to complete your approval process.

For more information on how to complete the Handshake approval process visit, https://manchester.unh.edu/student-internships or contact the UNH Manchester Career and Professional Success (CaPS) Office with questions.

COMP 705 (M1) - Full Stack Development

Full Stack Development

Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   11  
CRN: 51929
Students work in teams and implement, test, document, demonstrate, and deploy web systems that solve organizational needs expressed by real clients. Emphasis is on advanced server-side and client-side programming and integration of web application with database and web server applications. Free and open source development and communication tools are used to carry out the course project. Prereq: Senior status.
Section Comments: Cross listed with COMP 805
Only listed classes in section: Junior, Senior
Instructors: Raghava Adusumilli
Start Date End Date Days Time Location
1/24/2023 5/8/2023 F 5:31pm - 8:30pm PANDRA P149

COMP 721 (M1) - Big Data for Data Engineers

Big Data for Data Engineers

Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   9  
CRN: 52957
In this course students gain practical experience developing data-oriented applications in modern infrastructure frameworks, also known as the cloud data solutions. Guided by what a data scientist profile is, students become familiar with the use cases of data oriented applications. They will apply key data modeling and data design concepts to meet business requirements. Students will also apply modern software development to iteratively construct solutions using established reference architectures. Project work will be based in Google Cloud Platform and Amazon Web Services. Prereq: Senior Status. Special fee.
Section Comments: Cross listed with COMP 821
Only listed campus in section: Manchester
Only listed classes in section: Junior, Senior
Instructors: Anthony Sulpizio, Timothy Chadwick
Start Date End Date Days Time Location
1/24/2023 5/8/2023 R 5:31pm - 8:30pm PANDRA P149

COMP 725 (M1) - Programming Languages

Programming Languages

Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 51953
Explores the main features of modern, high-level, general purpose programming languages from the user point of view. Provides students with an opportunity to use non-imperative programming paradigms, such as object-oriented, functional, and visual, and to learn how specific features of such languages can be used efficiently in solving problems. The purpose is to gain knowledge regarding the languages studied as well as providing the basis to conduct analysis related to comparisons and divergence in capabilities. Prereq: Senior status.
Section Comments: Cross listed with COMP 825
Equivalent(s): CIS 698, COMP 698, ET 647
Only listed classes in section: Junior, Senior
Instructors: Michael Jonas
Start Date End Date Days Time Location
1/24/2023 5/8/2023 W 5:31pm - 8:30pm PANDRA P142

COMP 730 (M1) - Software Development

Software Development

Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 51930
Presents an iterative methodology for developing software systems. Development activities include requirements elicitation and analysis, system and object design, implementation and testing, project and configuration management, infrastructure maintenance, and system deployment to end user. Students work in teams, assume developer roles, build models of a real-world system, and deliver a proof-of-concept or prototype. Prereq: COMP 525.
Section Comments: Cross listed with COMP 830
Only listed classes in section: Junior, Senior
Attributes: Writing Intensive Course
Instructors: Takahide Ohkami
Start Date End Date Days Time Location
1/24/2023 5/8/2023 W 9:01am - 11:50am PANDRA P132

COMP 780 (M1) - Advanced Topics in Computing

AdvTop/Computer Vision

Credits: 4.0
Term: Spring 2023 - UNHM Credit (15 weeks) (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 56510
The course includes advanced topics and emerging areas in computing. Barring duplication of subject, the course may be repeated for credit. Prereq: Senior status or permission.
Section Comments: Cross listed with COMP 880.M1
Instructors: Richard Greene
Start Date End Date Days Time Location
1/24/2023 5/8/2023 T 9:01am - 11:50am PANDRA P126
Additional Course Details: 

Computer vision is powering technologies ranging from computer graphics to social robotics to autonomous vehicle. The course introduces tools of signal and image processing right up to neural networks. Students will write and debug programs that process images or video streams and construct recognizers to identify objects of interest for various purposes, such as scene understanding, facial recognition, or medical image processing. Students will work on a project of a topic of their choice and apply computer vision concepts, techniques, and tools to build computer vision applications.