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Search Results
| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
SYSM 6339 (Overall) | |||||
SYSM 6339 Gaurav Shekhar | |||||
Search Results
| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
SYSM 6339 (Overall) | |||||
SYSM 6339 Gaurav Shekhar | |||||
Robotic Process Automation
SYSM 6339
Naveen Jindal School of Management
This course is intended to provide students with practical literacy on robotic process automation through real-world, relevant data preparation use cases. It will help identify potential uses and the benefits and considerations for robotic process automation. The students will learn the elements of a business process and the basics of developing a BPM application, implementing triggers to automate processes, defining and measuring KPIs. Students will use elements of artificial intelligence (AI) and machine learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform. These tasks can include queries, calculations, and maintenance of records and transactions. Students will be able to use apply analytics to the generated data for a systematic computational analysis of data for the discovery, interpretation, and communication of meaningful patterns in data that will be used towards effective decision making. 3 credit hours.
Offering Frequency: Each semester
This professor/course combination hasn't been taught in the semesters you selected. To see more grade data, try changing your filters.
Grades: 0
Median GPA: None
Mean GPA: None
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Robotic Process Automation
SYSM 6339
Naveen Jindal School of Management
This course is intended to provide students with practical literacy on robotic process automation through real-world, relevant data preparation use cases. It will help identify potential uses and the benefits and considerations for robotic process automation. The students will learn the elements of a business process and the basics of developing a BPM application, implementing triggers to automate processes, defining and measuring KPIs. Students will use elements of artificial intelligence (AI) and machine learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform. These tasks can include queries, calculations, and maintenance of records and transactions. Students will be able to use apply analytics to the generated data for a systematic computational analysis of data for the discovery, interpretation, and communication of meaningful patterns in data that will be used towards effective decision making. 3 credit hours.
Offering Frequency: Each semester
This professor/course combination hasn't been taught in the semesters you selected. To see more grade data, try changing your filters.
Grades: 0
Median GPA: None
Mean GPA: None
Click a checkbox to add something to compare.