Timeroom: Spring 2023

Displaying 101 - 110 of 394 Results for: Attributes = EUNH

CPRM 899 (M1) - Capstone: Thesis Option

Capstone: Thesis Option

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term IV (03/20/2023 - 05/11/2023)
Grade Mode: Letter Grading
Class Size:   2  
CRN: 57107
Students synthesize, evaluate, and integrate past experiences, new research, and the cross-disciplinary knowledge constructed during this degree program to create a publishable quality, graduate-level thesis. In continuation with an advisor, each student develops a project plan; establishes goals and objectives; collects and analyzes information; and prepares and delivers a final product agreed upon by the student and advisor. Prereq: CPRM 720 / CPRM 820, CPRM 870 & (CPRM 879 or EDUC 882). Pre- or Co-req: CPRM 790 / CPRM 890.
Section Comments: Tech requirement: microphone & webcam
Instructor Approval Required. Contact Instructor for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 6 credits.
Only listed majors in section: CYBR SEC PRM
Instructors: Maeve Dion
Start Date End Date Days Time Location
3/20/2023 5/11/2023 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 408 (1SY) - Living in a Networked World: The Good, the Bad, and the Ugly

Living in a Networked World

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2023 - Full Term (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 52721
The objective of this course is to explore the implications of living in a networked world. The course surveys the fundamental technologies and practices that make up the Internet and then ask the student to examine the ramifications of using the technologies. Users of the technologies should understand the technology in order to make educated decisions about how to use it safely and effectively. Students have the opportunity to self-publish by using various current technologies including blogs, discussion boards, email and creating web pages using xhtml.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Attributes: Environment,Tech&Society(Disc)
Instructors: Sindhu Chellappa
Start Date End Date Days Time Location
1/24/2023 5/8/2023 TR 9:40am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 501 (1SY) - Professional Ethics and Communication in Technology-related Fields

Professional Ethics & Comm

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2023 - Full Term (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 51843
A mixed lecture/seminar course intended to improve both reasoning and ability to communicate effectively in front of an audience. Students learn basic forms of ethical argument, they read about ethical situations in which technology and technology professions play a key role, and they participate in student-led discussions about the reading. Students also make oral presentations about both ethical and technical topics, and evaluate each other's presentations in order to improve their sense for what makes a good presentation. Prereq: ENGL 401.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Only listed majors in section: ANLYTC&DS:ANLY, ANLYTC&DS:DS, COMPUTER SCIENC, CS: ALGORITHMS, CS: CYBERSECRTY, CS: SYSTEMS, INFO TECH
Attributes: Inquiry (Discovery), Environment,Tech&Society(Disc)
Instructors: Rita MacAuslan
Start Date End Date Days Time Location
1/24/2023 5/8/2023 MW 9:10am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Computer Science

CS 501 (2SY) - Professional Ethics and Communication in Technology-related Fields

Professional Ethics & Comm

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2023 - Full Term (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:   16  
CRN: 52045
A mixed lecture/seminar course intended to improve both reasoning and ability to communicate effectively in front of an audience. Students learn basic forms of ethical argument, they read about ethical situations in which technology and technology professions play a key role, and they participate in student-led discussions about the reading. Students also make oral presentations about both ethical and technical topics, and evaluate each other's presentations in order to improve their sense for what makes a good presentation. Prereq: ENGL 401.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Only listed majors in section: ANLYTC&DS:ANLY, ANLYTC&DS:DS, COMPUTER SCIENC, CS: ALGORITHMS, CS: CYBERSECRTY, CS: SYSTEMS, INFO TECH
Attributes: Inquiry (Discovery), Environment,Tech&Society(Disc)
Instructors: Rita MacAuslan
Start Date End Date Days Time Location
1/24/2023 5/8/2023 MW 11:10am - 1:00pm ONLINE
Manchester   UNH-Manchester :: Analytics

DATA 557 (M1) - Introduction to Data Science and Analytics

Introduction to Analytics

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:   20  
CRN: 52408
An introduction to data science and analytics. The landscape of analytics, including an overview of industries and sectors using analytics or expected to use analytics in the near future. Data generation, data management, data cleaning, and data preparation. Ethical use of data. Focus on visual and exploratory analysis. Project-based, with an emphasis on collaborative, experiential learning. Programming and statistical software will be used, but previous experience is not required.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Attributes: Environment,Tech&Society(Disc)
Instructors: Jeremiah Johnson
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 - 10:50am PANDRA P367
Manchester   UNH-Manchester :: Analytics

DATA 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: Credit/Fail Grading
Class Size:   5  
CRN: 55610
A field-based learning experience via placement in a business, non-profit, or government organization using analytics. Under the guidance of a faculty advisor and workplace supervisor, students gain practical experience solving problems and improving operational processes using analytics. May be repeated but no more than 4 credits may fill major requirements. Prereq: UMST 582.
Section Comments: Cross listed with COMP 690, COMP 891, COMP 892
Instructor Approval Required. Contact Instructor for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 8 credits.
Cross listed with : COMP 690.M1, COMP 891.M1, COMP 892.M1
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.

Manchester   UNH-Manchester :: Analytics

DATA 800 (M1) - Introduction to Applied Analytic Statistics

Intro: Applied Analytic Stats

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term III (01/17/2023 - 03/10/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55161
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
1/17/2023 3/10/2023 Hours Arranged ONLINE
Manchester   UNH-Manchester :: Analytics

DATA 820 (M1) - Programming for Data Science

Programming for Data Science

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term III (01/17/2023 - 03/10/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55162
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Phani Kidambi
Start Date End Date Days Time Location
1/17/2023 3/10/2023 Hours Arranged ONLINE
Manchester   UNH-Manchester :: Analytics

DATA 821 (M1) - Data Architecture

Data Architecture

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term IV (03/20/2023 - 05/11/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55163
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Timothy Chadwick
Start Date End Date Days Time Location
3/20/2023 5/11/2023 Hours Arranged ONLINE
Manchester   UNH-Manchester :: Analytics

DATA 822 (M1) - Data Mining and Predictive Modeling

Data Mining & Pred Modeling

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2023 - E-term IV (03/20/2023 - 05/11/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 55164
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Mutual Exclusion : ADMN 872
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
3/20/2023 5/11/2023 Hours Arranged ONLINE