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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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Search Results
| Name | Grades | Rating | |||
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BUAN 4382 Lidong Wu | |||||
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| Name | Grades | Rating | |||
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BUAN 4382 Lidong Wu | |||||
Lidong Wu
[email protected]Grades: 1,077
Median GPA: A-
Mean GPA: 3.661
1.9
Professor rating
3.5
Difficulty
15
Ratings given
20%
Would take again
Applied Artificial Intelligence/Machine Learning
Naveen Jindal School of Management
Broad exploration of machine learning, data mining, and pattern recognition in business contexts. Coverage of supervised and unsupervised learning methods, text analytics, and applications of AI techniques for business decision-making. Attention to data preparation, model selection, and evaluation. Emphasis on business framing, strategy, and return on investment, along with ethical and regulatory considerations in AI. Content delivered through lectures, discussions, labs, and case studies, focusing on practical methods and conceptual understanding across real-world applications. 3 credit hours.
Prerequisite: ITSS 3312 or BUAN 4381 or ITSS 4381.
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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Lidong Wu
[email protected]Grades: 1,077
Median GPA: A-
Mean GPA: 3.661
1.9
Professor rating
3.5
Difficulty
15
Ratings given
20%
Would take again
Applied Artificial Intelligence/Machine Learning
Naveen Jindal School of Management
Broad exploration of machine learning, data mining, and pattern recognition in business contexts. Coverage of supervised and unsupervised learning methods, text analytics, and applications of AI techniques for business decision-making. Attention to data preparation, model selection, and evaluation. Emphasis on business framing, strategy, and return on investment, along with ethical and regulatory considerations in AI. Content delivered through lectures, discussions, labs, and case studies, focusing on practical methods and conceptual understanding across real-world applications. 3 credit hours.
Prerequisite: ITSS 3312 or BUAN 4381 or ITSS 4381.
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.