Timeroom: Fall 2023

CPS Online Coll of Professional Studies :: Data Analytics

DAT 510 (01) - Introduction to Data Analytics

Intro Data Analytics

Online Course Delivery Method: Online Asynchronous

Credits: 4.0
Term: Fall 2023 - Term 1 (08/28/2023 - 10/20/2023)
Grade Mode: Letter Grading

Class Size: 30
CRN: 16204

Data analytics is defined as a scientific process that produces actionable insights. Students will be introduced to the concepts of data analysis, what the role of a data analyst will do, and the tools that are used to perform daily functions. This course will cover data analytics and data governance where students will learn about the fundamentals of data gathering, data mining, and how the decision-making process can be affected. This course also addresses the skills that are required to effectively communicate data to co-workers, leadership, and stakeholders. Excel proficiency is expected prior to enrollment in this course. Students should consider completing CMPL 402 Excel if they have not completed an Excel course in transfer.

Advisor Approval Required. Contact your Academic Advisor for approval and registration.

Equivalent(s): DATA 510G

Campuses not allowed in section: Durham

Attributes: Online (no campus visits), EUNH

Instructors: Anthony Sulpizio

Start Date	End Date	Days	Time	Location
8/28/2023	10/20/2023		Hours Arranged	ONLINE

CPS Online Coll of Professional Studies :: Data Analytics

DAT 535 (01) - Data Mining, Cleaning, and Visualization

Data Mining/Clean/Visualiz

Online Course Delivery Method: Online Asynchronous

Credits: 4.0
Term: Fall 2023 - Term 2 (10/30/2023 - 12/22/2023)
Grade Mode: Letter Grading

Class Size: 30
CRN: 16205

This course will cover data mining, cleaning, and visualization preparation, including what data mining is and how it pertains to data analytics. Data cleaning and preparation for data analysis will also be covered. Students will have the opportunity to learn about data visualizations, which includes data modeling, mapping data attributes to graphical attributes, and using data visualization tools.

Advisor Approval Required. Contact your Academic Advisor for approval and registration.

Prerequisite(s): DAT 510 or DATA 510G

Equivalent(s): DATA 520G

Campuses not allowed in section: Durham

Attributes: Online (no campus visits), EUNH

Instructors: Anthony Sulpizio

Start Date	End Date	Days	Time	Location
10/30/2023	12/22/2023		Hours Arranged	ONLINE

CPS Online Coll of Professional Studies :: Data Analytics

DAT 620 (X1) - Data Analytics in Business Intelligence

Data Analytics in Bus Intel

Online Course Delivery Method: Online Asynchronous

Credits: 4.0
Term: Fall 2023 - Term 1 (08/28/2023 - 10/20/2023)
Grade Mode: Letter Grading

Class Size: 10
CRN: 16826

This course will examine the role of data analysis through the lens of multiple business disciplines such as business, health care, and marketing. Students will have the opportunity to explore key areas in the analytical process, including how data are created, stored, and accessed. The course covers how businesses and organizations work with data to create environments in which analytics can drive effective and efficient decision making.

Advisor Approval Required. Contact your Academic Advisor for approval and registration.

Prerequisite(s): DAT 610 or DATA 610G

Equivalent(s): DATA 620G

Campuses not allowed in section: Durham

Attributes: Online (no campus visits), EUNH

Instructors: Anthony Sulpizio

Start Date	End Date	Days	Time	Location
8/28/2023	10/20/2023		Hours Arranged	ONLINE

CPS Online Coll of Professional Studies :: Data Analytics

DAT 670 (01) - Advanced Data Analytics

Advanced Data Analytics

Online Course Delivery Method: Online Asynchronous

Credits: 4.0
Term: Fall 2023 - Term 2 (10/30/2023 - 12/22/2023)
Grade Mode: Letter Grading

Class Size: 30
CRN: 16207

Students will have the opportunity to explore more advanced data analytics methods such as collaborating on hypothesis testing and performing root cause analysis and practice presenting visualizations of data analysis that highlight the insights gained from analysis. The handling of imperfect data will also be covered.

Advisor Approval Required. Contact your Academic Advisor for approval and registration.

Prerequisite(s): (DAT 620 or DATA 620G)

Equivalent(s): DATA 630G

Campuses not allowed in section: Durham

Attributes: Online (no campus visits), EUNH

Instructors: Anthony Sulpizio

Start Date	End Date	Days	Time	Location
10/30/2023	12/22/2023		Hours Arranged	ONLINE

Manchester Coll of Professional Studies :: Analytics

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

Introduction to Analytics

Online Course Delivery Method: Hybrid / Blended

Credits: 4.0
Term: Fall 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Letter Grading

Class Size: 20
CRN: 12096

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: Online with some campus visits, EUNH, Environment,Tech&Society(Disc)

Instructors: Bogdan Gadidov

Start Date	End Date	Days	Time	Location
8/28/2023	12/11/2023	T	6:10pm - 8:00pm	PANDRA P367
8/28/2023	12/11/2023		Hours Arranged	ONLINE

Manchester Coll of Professional Studies :: Analytics

DATA 690 (M1) - Internship Experience

Internship Experience

Online Course Delivery Method: Online Synchronous

Credits: 1.0 to 4.0
Term: Fall 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Credit/Fail Grading

Class Size: 2
CRN: 14009

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.

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

Prerequisite(s): UMST 582

Repeat Rule: May be repeated for a maximum of 8 credits.

Attributes: Scheduled meeting time, Online (no campus visits), EUNH

Instructors: Maggie Wells

Start Date	End Date	Days	Time	Location
8/28/2023	12/11/2023	M	9:10am - 12:00pm	ONLINE

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://unh.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 Coll of Professional Studies :: Analytics

DATA 800 (M1) - Introduction to Applied Analytic Statistics

Intro: Applied Analytic Stats

Online Course Delivery Method: Online Asynchronous

Credits: 3.0
Term: Fall 2023 - Term 1 (08/28/2023 - 10/20/2023)
Grade Mode: Letter Grading

Class Size: 20
CRN: 14288

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.

Only listed majors in section: ANALYT DS CERT, ANALYT DS CERT

Attributes: Online (no campus visits), EUNH

Instructors: Bogdan Gadidov

Start Date	End Date	Days	Time	Location
8/28/2023	10/20/2023		Hours Arranged	ONLINE

Manchester Coll of Professional Studies :: Analytics

DATA 820 (M1) - Programming for Data Science

Programming for Data Science

Online Course Delivery Method: Online Asynchronous

Credits: 3.0
Term: Fall 2023 - Term 1 (08/28/2023 - 10/20/2023)
Grade Mode: Letter Grading

Class Size: 20
CRN: 14289

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.

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

Prerequisite(s): DATA 800 May be taken concurrently

Only listed majors in section: ANALYT DS CERT, ANALYT DS CERT

Attributes: Online (no campus visits), EUNH

Instructors: Phani Kidambi

Start Date	End Date	Days	Time	Location
8/28/2023	10/20/2023		Hours Arranged	ONLINE

Manchester Coll of Professional Studies :: Analytics

DATA 821 (M1) - Data Architecture

Data Architecture

Online Course Delivery Method: Online Asynchronous

Credits: 3.0
Term: Fall 2023 - Term 2 (10/30/2023 - 12/22/2023)
Grade Mode: Letter Grading

Class Size: 20
CRN: 14290

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.

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

Prerequisite(s): DATA 800 and DATA 820

Only listed majors in section: ANALYT DS CERT, ANALYT DS CERT

Attributes: Online (no campus visits), EUNH

Instructors: Timothy Chadwick

Start Date	End Date	Days	Time	Location
10/30/2023	12/22/2023		Hours Arranged	ONLINE

Manchester Coll of Professional Studies :: Analytics

DATA 822 (M1) - Data Mining and Predictive Modeling

Data Mining & Pred Modeling

Online Course Delivery Method: Online Asynchronous

Credits: 3.0
Term: Fall 2023 - Term 2 (10/30/2023 - 12/22/2023)
Grade Mode: Letter Grading

Class Size: 20
CRN: 14291

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.

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

Prerequisite(s): DATA 800 and DATA 820 and DATA 821 May be taken concurrently

Mutual Exclusion : ADMN 872

Only listed majors in section: ANALYT DS CERT, ANALYT DS CERT

Attributes: Online (no campus visits), EUNH

Instructors: Bogdan Gadidov

Start Date	End Date	Days	Time	Location
10/30/2023	12/22/2023		Hours Arranged	ONLINE