Review Assessment Report

Part 1: Contact & Program Identification

Report Year and Contact Information
Academic YearModified ByDate Modified
2022-2023[email protected]2023-10-23T19:56:27.129Z
SchoolName of ProgramCourses
BITArtificial Intelligence and Machine Learning CertificateNone

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
This is a new program. We have no graduates as of yet. We have multiple sections of the introductory course. Some students continue with AIML 2010. We are introducing two follow on classes: AIML 2110 and AIML2120. We anticipate our first graduates in Spring term 2024.

Part 3: Data Review

2020-20212021-20222022-2023
Annual number of graduate awards is greater than 10023
Number of declared majors02221
Average Class Sizen/an/an/a
Annual Average Class withdrawal rate is 30% or below (SAGE 35%)n/an/an/a
Annual C-Pass rate for coursework is 60% or aboven/an/an/a
Average class fill rate at 60% or above capacity within a term or over a yearn/an/an/a
Graduate Transfer to 4-year Schoolsn/an/an/a
Full-time Faculty Coverage by Sectionn/an/an/a
Summarize how your program met or did not meet the target measures based on the data above
There are 21 students in the progam There is no other data to compare yet. Data will be evaluted in the next cycle.

Part 4: Program Learning Outcome Analysis

Learning OutcomePopulation or Course(s) AssessedDescriptionSummary of Assessment Results
1. Apply common artificial intelligence (AI) concepts and methodologies for analysis and decision making.
AIML 2010
    2. Apply artificial intelligence (AI) project development and machine learning life cycle to address social and business issues, opportunities, and problems.
    AIML 1010
      4. Use appropriate programming languages to implement artificial intelligence (AI) solutions.
      AIML 1010, AIML 2010
        5. Evaluate issues of bias, culture, environment, ethics, regulations, and professional expectations in the field of artificial intelligence (AI) and machine learning.
        AIML 1010
          1. Apply common artificial intelligence (AI) concepts and methodologies for analysis and decision making.
          AIML 2010
            Interpretation of Assessment findings
            This is brand new program. There are no findings to interpret because there were only 2 courses were offered over the past year therefore there are no assesment values.

            Part 5: Additional Action Plan in Support of Student Learning (If Appropriate)

            Upcoming YearChanges Planned for the upcoming yearData Motivating this change
            2022-2023
            Two new courses will be added to the program - Natural Language Processing and Deep Learning AIML 2010 and AIML 2020
            There was a revision this cycle.
            2022-2023
            2022-2023
            Please select all of the following that characterize the types of changes described in the above action plan
            2021-2024 CNM - Digital Services
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