Timeroom: Fall 2024

Displaying 141 - 150 of 714 Results for: Delivery = Unknown Attribute
Durham   Engineering&Physical Sciences :: Computer Science

CS 501 (03) - Professional Ethics and Communication in Technology-related Fields

Professional Ethics & Comm

Online Course Delivery Method: Online Asynchronous
Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading
Class Size:   16  
CRN: 12892
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): ENGL 401
Attributes: Inquiry (Discovery), Environment,Tech&Society(Disc)
Instructors: Rita MacAuslan
Start Date End Date Days Time Location
8/26/2024 12/9/2024 Hours Arranged ONLINE
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 2024 - Term 1 (08/26/2024 - 10/18/2024)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 14850
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
Instructors: Alison Russo
Start Date End Date Days Time Location
8/26/2024 10/18/2024 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 2024 - Term 2 (10/28/2024 - 12/20/2024)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 14851
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.
Prerequisite(s): DAT 510 or DATA 510G
Equivalent(s): DATA 520G
Campuses not allowed in section: Durham
Instructors: Alison Russo
Start Date End Date Days Time Location
10/28/2024 12/20/2024 Hours Arranged ONLINE
CPS Online   Coll of Professional Studies :: Data Analytics

DAT 610 (X1-) - Data Analytics and Technologies

Data Analytics and Tech

Online Course Delivery Method: Online Asynchronous
Credits: 4.0
Term: Fall 2024 - Term 1 (08/26/2024 - 10/18/2024)
Grade Mode: Letter Grading
Class Size:   1  
CRN: 16934
Students will have the opportunity to explore contemporary systems and technologies impacting the field of data analytics, including the cloud, AI, and machine learning. This course will also explore areas of technology that provide opportunities for future professional specialization, such as emerging Big Data technologies that support the work of data analysts, and the role of Information Technology (IT).
Advisor Approval Required. Contact your Academic Advisor for approval and registration.
Prerequisite(s): DAT 535 or DATA 520G
Equivalent(s): DATA 610G
Campuses not allowed in section: Durham
Instructors: Anthony Sulpizio
Start Date End Date Days Time Location
8/26/2024 10/18/2024 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 2024 - Term 1 (08/26/2024 - 10/18/2024)
Grade Mode: Letter Grading
Class Size:   1  
CRN: 16911
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
Instructors: Anthony Sulpizio
Start Date End Date Days Time Location
8/26/2024 10/18/2024 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 2024 - Term 2 (10/28/2024 - 12/20/2024)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 14853
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.
Prerequisite(s): (DAT 620 or DATA 620G)
Equivalent(s): DATA 630G
Campuses not allowed in section: Durham
Instructors: Anthony Sulpizio
Start Date End Date Days Time Location
10/28/2024 12/20/2024 Hours Arranged ONLINE
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 2024 - Term 1 (08/26/2024 - 10/18/2024)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 13440
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
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
8/26/2024 10/18/2024 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 2024 - Term 1 (08/26/2024 - 10/18/2024)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 13441
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 with minimum grade of B- May be taken concurrently
Only listed majors in section: ANALYT DS CERT, ANALYT DS CERT
Instructors: Phani Kidambi
Start Date End Date Days Time Location
8/26/2024 10/18/2024 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 2024 - Term 2 (10/28/2024 - 12/20/2024)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 13442
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.
Prerequisite(s): DATA 800 with minimum grade of B- and DATA 820 with minimum grade of B-
Only listed majors in section: ANALYT DS CERT, ANALYT DS CERT
Instructors: Timothy Chadwick
Start Date End Date Days Time Location
10/28/2024 12/20/2024 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 2024 - Term 2 (10/28/2024 - 12/20/2024)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 13443
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.
Prerequisite(s): DATA 800 with minimum grade of B- and DATA 820 with minimum grade of B- and DATA 821 with minimum grade of B- May be taken concurrently
Mutual Exclusion : ADMN 872
Only listed majors in section: ANALYT DS CERT, ANALYT DS CERT
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
10/28/2024 12/20/2024 Hours Arranged ONLINE