Review Assessment Report
Part 1: Contact & Program Identification
Report Year and Contact Information | ||
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Academic Year | Modified By | Date Modified |
2020-2021 | [email protected] | 2021-11-30T21:10:58.952Z |
School | Name of Program | Courses |
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BIT | Artificial Intelligence and Machine Learning Certificate | None |
Part 2: Program Summary
Provide a high level review of the program to include highlights, successes, challenges, significant changes, and significant resources needed to support the program |
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This is a new certificate program. Certificate will be assessed during the 2021-2022 academic year. |
Part 3: Data Review
2018-2019 | 2019-2020 | 2020-2021 | |
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Annual number of graduate awards is greater than 10 | 0 | 0 | 0 |
Number of declared majors | 0 | 0 | 0 |
Average Class Size | n/a | n/a | n/a |
Annual Average Class withdrawal rate is 30% or below (SAGE 35%) | n/a | n/a | n/a |
Annual C-Pass rate for coursework is 60% or above | n/a | n/a | n/a |
Average class fill rate at 60% or above capacity within a term or over a year | n/a | n/a | n/a |
Graduate Transfer to 4-year Schools | n/a | n/a | n/a |
Full-time Faculty Coverage by Section | n/a | n/a | n/a |
Summarize how your program met or did not meet the target measures based on the data above |
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New certificate program. No data available. |
Part 4: Program Learning Outcome Analysis
Learning Outcome | Population or Course(s) Assessed | Description | Summary of Assessment Results |
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1. Apply common artificial intelligence (AI) concepts and methodologies, including neural networks/Deep Learning, machine learning, Natural Language Processing, Computer Vision, and data science, for analysis and decision making. | AIML 2010 | Data unavailable. | |
2. Apply artificial intelligence (AI) project development and machine learning life cycle to address social and business issues, opportunities, and problems. | AIML 1010 | Data unavailable. | |
3. Apply statistical analysis and machine learning algorithms to predict usefulness of artificial intelligence (AI) programming solutions. | AIML 2010, BCIS 1330 | Data unavailable. | |
4. Use appropriate programming languages to implement artificial intelligence (AI) solutions. | AIML 2010 | Data unavailable. | |
5. Evaluate issues of bias, culture, environment, ethics, regulations, and professional expectations in the field of artificial intelligence (AI) and machine learning. | AIML 1010 | Data unavailable. |
Interpretation of Assessment findings |
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New certificate program. Program will be assessed for the 2021-2022 academic year. |
Part 5: Additional Action Plan in Support of Student Learning (If Appropriate)
Upcoming Year | Changes Planned for the upcoming year | Data Motivating this change |
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2021-2022 | ||
2021-2022 | ||
2021-2022 |