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CIS461
Preview: CIS461 Data Analytics II :
Course Guide
Prerequisites
Course Description
Instructional Materials
CIS 362
The course provides comprehensive overview a of data mining. Students will learn different
methods, such as data collection and selection, data cleaning and transformation, pattern discovery
and knowledge extraction, including traditional statistical analysis and basic machine learning
techniques. Students will analyze large datasets and learn to develop modeling solutions to support
decision making in a professional domain. In so doing, students will gain insight into how data
analytics is applied in professional fields.
Required Resources
zyBooks. 2020. Applied Regression Analysis (Python). CIS461 zyBooks webtext available at
https://www.strayerbookstore.com
Purchase your activation code at the Strayer University Bookstore.
All course readings are included in your zyBook inside the Blackboard course shell.
Note: It is crucial that you purchase and activate zyBooks and complete the required activities
and labs in order to succeed in this course. You must activate zyBooks through the link in
Blackboard Week (do – 1 not go directly to the zyBooks website).
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Course Learning Outcomes
Weekly Course Schedule
Week 1 - To Do List
zyBooks: Read Chapter in 1 Applied
Regression
Analysis
(Python).
zyBooks: Complete the Chapter 1 Lab Activities.
Discuss: Introduce yourself and complete the discussion, Linear Regression Versus Correlation.
Week 2 - To Do List
zyBooks: Read Chapter in 2 Applied
Regression
Analysis
(Python).
zyBooks: Complete the Chapter 2 Lab Activities.
Discuss: Complete the discussion, Data Analytics and Marketing.
