Timeroom: Spring 2021

Displaying 1 - 7 of 7 Results for: Subject = DATA
Manchester   UNH-Manchester :: Analytics

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

Introduction to Analytics

Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2021 - UNHM Credit (15 weeks) (02/01/2021 - 05/11/2021)
Class Size:   20  
CRN: 52973
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.
You must sign up in the Dept Office before registering through WEBCAT.
Attributes: Environment,Tech&Society(Disc)
Instructors: Jeremiah Johnson
Start Date End Date Days Time Location
2/1/2021 5/11/2021 M 1:01pm - 2:50pm ONLINE
Manchester   UNH-Manchester :: Analytics

DATA 750 (M1) - Neural Networks

Neural Networks

Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2021 - UNHM Credit (15 weeks) (02/01/2021 - 05/11/2021)
Class Size:   4  
CRN: 55157
Artificial neural networks power the recent advances in computer vision, speech recognition, and machine translation. This is a first course on neural networks with a focus on applications in computer vision and natural language processing. Topics will include generic feedforward neural networks, convolutional neural networks for computer vision tasks, and recurrent neural networks with application to natural language processing, with other topics to be selected based on the interests of the instructor and the class. Prereq: Senior status.
Section Comments: Cross listed with COMP 750, COMP 850
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): COMP 750
Instructors: Jeremiah Johnson
Start Date End Date Days Time Location
2/1/2021 5/11/2021 M 9:01am - 10:50am ONLINE
Durham   Graduate School :: Analytics

DATA 800 (1ON) - Introduction to Applied Analytic Statistics

Intro: Applied Analytic Stats

Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term III (01/19/2021 - 03/12/2021)
Class Size:   15  
CRN: 53379
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.
You must sign up in the Dept Office before registering through WEBCAT.
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
1/19/2021 3/12/2021 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 820 (1ON) - Programming for Data Science

Programming for Data Science

Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term III (01/19/2021 - 03/12/2021)
Class Size:   15  
CRN: 53376
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.
You must sign up in the Dept Office before registering through WEBCAT.
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Phani Kidambi
Start Date End Date Days Time Location
1/19/2021 3/12/2021 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 821 (1ON) - Data Architecture

Data Architecture

Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term IV (03/22/2021 - 05/13/2021)
Class Size:   30  
CRN: 53377
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.
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Timothy Chadwick
Start Date End Date Days Time Location
3/22/2021 5/13/2021 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 822 (1ON) - Data Mining and Predictive Modeling

Data Mining & Pred Modeling

Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2021 - E-term IV (03/22/2021 - 05/13/2021)
Class Size:   30  
CRN: 53378
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.
Mutual Exclusion : ADMN 872
Only listed majors in section: ANALYT DS CERT, ANALYTICS CERT
Instructors: Bogdan Gadidov
Start Date End Date Days Time Location
3/22/2021 5/13/2021 Hours Arranged ONLINE
Durham   Graduate School :: Analytics

DATA 897 (01) - Self Designed Analytics Thesis Lab II

Self-Designed Analytics Lab II

Credits: 3.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Class Size:   10  
CRN: 53073
This is the second of a two course self-designed thesis sequence offered under the master's of science degree in analytics. The nature of the class is applied learning directly around a student directed analytic thesis project. The class requires competency in two areas for the successful completion of the course. Students will have completed the data collection, cleaning and management and created readable analytic files for the project of their choice in the first of the two course sequence. Students are primarily responsible to apply modern analytical tools and techniques like predictive modeling, segmentation, and network analysis etc. They are also required to write a formal 2000+ word report on the findings of the project. The report is expected to include modern data visualization synthesized with analysis results. Prereq: DATA 803.
You must sign up in the Dept Office before registering through WEBCAT.
Only listed majors in section: ANALYTICS, ANALYTICS CERT, ANALYTICS PP
Instructors: Joanna Gyory
Start Date End Date Days Time Location
2/1/2021 5/11/2021 Hours Arranged PBLANE 216