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5.0
Professor rating
5.0
Difficulty
1,000
Ratings given
99%
Would take again
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5.0
Professor rating
5.0
Difficulty
1,000
Ratings given
99%
Would take again
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| Name | Grades | Rating | |||
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ITSS 4383 Judd Bradbury | |||||
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ITSS 4383 Judd Bradbury | |||||
Grades: 2,407
Median GPA: B+
Mean GPA: 3.292
2.5
Professor rating
3.7
Difficulty
100
Ratings given
31%
Would take again
Machine Learning for Business Analytics
Naveen Jindal School of Management
Exploration of advanced applications of artificial intelligence and machine learning in business and analytics using Python. Coverage includes supervised and unsupervised methods, neural networks, deep learning, natural language processing, large language models, and reinforcement learning. Emphasis placed on data preparation, statistical foundations, model building, and evaluation techniques. Case studies and applied exercises highlight the role of AI in strategic decision-making, implementation, and governance. Ethical and regulatory considerations are integrated throughout, examining fairness, bias, and responsible deployment of AI systems. 3 credit hours.
Prerequisites: (ITSS 3312 or BUAN 4381 or ITSS 4381) and (BUAN 4373 or OPRE 4373).
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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Grades: 2,407
Median GPA: B+
Mean GPA: 3.292
2.5
Professor rating
3.7
Difficulty
100
Ratings given
31%
Would take again
Machine Learning for Business Analytics
Naveen Jindal School of Management
Exploration of advanced applications of artificial intelligence and machine learning in business and analytics using Python. Coverage includes supervised and unsupervised methods, neural networks, deep learning, natural language processing, large language models, and reinforcement learning. Emphasis placed on data preparation, statistical foundations, model building, and evaluation techniques. Case studies and applied exercises highlight the role of AI in strategic decision-making, implementation, and governance. Ethical and regulatory considerations are integrated throughout, examining fairness, bias, and responsible deployment of AI systems. 3 credit hours.
Prerequisites: (ITSS 3312 or BUAN 4381 or ITSS 4381) and (BUAN 4373 or OPRE 4373).
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.