Enrollment and waitlist data for current and upcoming courses refresh every 10 minutes; all other information as of 6:00 AM.
| 01/04 - 01/28 | ||||||
| M | T | W | Th | F | Sa | Su |
| + asynchronous coursework | ||||||
Subject: Computer & Info Sci (UG) (CISC)
CRN: 10168
Online: Asynchronous | Lecture
Online
Requirements Met:
Liberal Arts Bus Minor Appr
This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for non-majors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics. NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
4 Credits
| 01/04 - 01/28 | ||||||
| M | T | W | Th | F | Sa | Su |
| + asynchronous coursework | ||||||
Subject: Computer & Info Sci (UG) (CISC)
CRN: 10169
Online: Asynchronous | Lecture
Online
Requirements Met:
Liberal Arts Bus Minor Appr
This course will prepare students to use computers in a business environment and in daily life. It will provide an introduction to programming and problem solving for non-majors. Spreadsheet and database software will be used to solve problems related to business. The course includes an overview of hardware and software, how computers acquire and process information, and related topics. NOTE: Students who receive credit for CISC 200 may not receive credit for CISC 110 or 216.
4 Credits
| 01/04 - 01/28 | ||||||
| M | T | W | Th | F | Sa | Su |
| + asynchronous coursework | ||||||
Subject: Data Science (DASC)
CRN: 10175
Online: Asynchronous | Lecture
Online
Core Requirements Met:
[Core] Quant Analysis
Other Requirements Met:
Liberal Arts Bus Minor Appr
School of Ed Transfer Course
Instructor: TBD
This course is composed of an in-depth study of the processes through which statistics can be used to learn about environments and events. There will be an intensive focus on the application, analysis, interpretation, and presentation of both descriptive and inferential statistics in a variety of real world contexts. Topics include data collection, research design, data visualization, sampling distributions, confidence intervals and hypothesis testing, inference for one and two samples, chi-square tests for goodness of fit and association, analysis of variance, and simple and multiple linear regression. Extensive data analysis using modern statistical software is an essential component of this course. Prerequisites: Math placement at level of MATH 108 or above; or completion of MATH 006, 007, 100, 101, 103, 104, 105, 107, 108, 111, or 113. NOTE: Students who receive credit for DASC 120 may not receive credit for DASC 111 or DASC 112.
4 Credits
| 01/04 - 01/28 | ||||||
| M | T | W | Th | F | Sa | Su |
| + asynchronous coursework | ||||||
Subject: Data Science (DASC)
CRN: 10176
Online: Asynchronous | Lab
Online
Core Requirements Met:
[Core] Quant Analysis
Other Requirements Met:
Liberal Arts Bus Minor Appr
School of Ed Transfer Course
Instructor: TBD
This course is composed of an in-depth study of the processes through which statistics can be used to learn about environments and events. There will be an intensive focus on the application, analysis, interpretation, and presentation of both descriptive and inferential statistics in a variety of real world contexts. Topics include data collection, research design, data visualization, sampling distributions, confidence intervals and hypothesis testing, inference for one and two samples, chi-square tests for goodness of fit and association, analysis of variance, and simple and multiple linear regression. Extensive data analysis using modern statistical software is an essential component of this course. Prerequisites: Math placement at level of MATH 108 or above; or completion of MATH 006, 007, 100, 101, 103, 104, 105, 107, 108, 111, or 113. NOTE: Students who receive credit for DASC 120 may not receive credit for DASC 111 or DASC 112.
0 Credits