Timeroom: Fall 2024

Displaying 1 - 6 of 6 Results for: Subject = DATA
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 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 11765
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.
Attributes: Environment,Tech&Society(Disc)
Instructors: Jeremiah Johnson
Start Date End Date Days Time Location
8/26/2024 12/9/2024 M 1:10pm - 3:00pm PANDRA P367
8/26/2024 12/9/2024 Hours Arranged ONLINE
Durham   Coll of Professional Studies :: Analytics

DATA 674 (01) - Predictive and Prescriptive Analytics I

Predictive Analytics I

Credits: 4.0
Term: Fall 2024 - Full Term (08/26/2024 - 12/09/2024)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 14670
A first course in predictive and prescriptive analytics. Supervised learning models including linear models and CART models. Model assessment and scoring methods, including cross-validation. Regularization and model tuning. Unsupervised learning models including k-means clustering. Project-based, with an emphasis on collaborative, experiential learning. Statistical software will be used and programming required.
Prerequisite(s): MATH 425 and COMP 570 and DATA 557
Instructors: Matthew Magnusson
Start Date End Date Days Time Location
8/26/2024 12/9/2024 MWF 1:10pm - 2:00pm MURK 204
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.
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.
Prerequisite(s): DATA 800 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 and DATA 820
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 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
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
10/28/2024 12/20/2024 Hours Arranged ONLINE