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5.0
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5.0
Difficulty
1,000
Ratings given
99%
Would take again
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| Name | Grades | Rating | |||
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Not teaching in Spring 2026 | |||||
BUAN 6385 Gaurav Shekhar | |||||
A | |||||
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| Name | Grades | Rating | |||
|---|---|---|---|---|---|
Not teaching in Spring 2026 | |||||
BUAN 6385 Gaurav Shekhar | |||||
A | |||||
Grades: 1,949
Median GPA: A-
Mean GPA: 3.482
4.4
Professor rating
3.5
Difficulty
56
Ratings given
89%
Would take again
Robotic Process Automation
BUAN 6385
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
Grades: 205
Median GPA: A
Mean GPA: 3.406
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Grades: 1,949
Median GPA: A-
Mean GPA: 3.482
4.4
Professor rating
3.5
Difficulty
56
Ratings given
89%
Would take again
Robotic Process Automation
BUAN 6385
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
Grades: 205
Median GPA: A
Mean GPA: 3.406
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