AEM 2830
Last Updated
- Schedule of Classes - June 2, 2019 7:14PM EDT
- Course Catalog - June 2, 2019 7:15PM EDT
Classes
AEM 2830
Course Description
Course information provided by the Courses of Study 2018-2019.
Data-driven decision making and the use of analytical approaches are critical skills for success in business. Analytics skills are increasing in demand and in many cases, are required for business professionals. The new technologies and development such as personal electrical devices, social media, online shopping, etc., resulted in exponential growth in the amount of data we generate and collect on a daily basis. Companies are highly interested in extracting knowledge from these sources. To be able to manipulate and analyze large structured and unstructured dataset, you need to learn how to code. In this course, by learning VBA (Visual Basic for Applications), you will take your Excel skills to the next level. You will learn how to design and code an algorithm and manipulate datasets. In the second part of the semester, you will learn a more advanced coding language called Python. Python is a very strong language for data analysis.
When Offered Spring.
Permission Note Enrollment preference given to: Dyson students.
Prerequisites/Corequisites Prerequisite: AEM 2010.
Forbidden Overlaps Forbidden Overlap: due to an overlap in content, students will not receive credit for both AEM 2830 and CS 1110.
Outcomes
- Program VBA, a strong tool that adds a great deal of functionality to Excel.
- Execute operations in Python, a strong open source coding language.
- Develop algorithmic thinking.
- Utilize and understand Basic Data Structures.
- Utilize and understand Conditional Branching and Looping.
- Build Procedures and Functions in VBA, and Functions in Python.
- Develop skills in building models to solve real-world business problems.
Regular Academic Session.
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Credits and Grading Basis
3 Credits GradeNoAud(Letter grades only (no audit))
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Class Number & Section Details
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Meeting Pattern
- MW Mann Library B30A
Instructors
Moghimi, R
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Additional Information
Enrollment preference given to Dyson students. Non-Dyson students require permission of instructor.
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