Artificial Intelligence and Machine Learning

The Artificial Intelligence and Machine Learning program provides students with foundational and applied knowledge in artificial intelligence, including machine learning, deep learning, generative AI, and natural language processing. The program emphasizes hands-on learning using real-world datasets and industry-relevant tools to design, implement, and evaluate AI-driven systems.

Students will develop skills in programming, data analysis, and model development using modern AI techniques. Coursework covers core topics such as supervised and unsupervised machine learning, neural networks, language models, generative modeling, and ethical considerations in artificial intelligence.

This program prepares students for entry-level positions such as AI/ML technician, data analyst, data engineer, AI application developer, or software developer with AI-related responsibilities. It also supports upskilling and reskilling for current workers seeking to advance or transition into AI-related roles. 

Because many careers in artificial intelligence and machine learning require advanced degrees, this program is designed to provide a strong foundation for continued education and career advancement.

Prior programming experience is not required; foundational programming skills are developed within the program.

A Certificate of Achievement is awarded upon completion of all required courses with a grade of C or better.

Projected Annual Program Completers: 15 -20

These projections reflect anticipated enrollment patterns in Pasadena City College’s Computer Science and Data Science programs, as well as expected demand for AI/ML coursework. As a new program, completer numbers are expected to grow over time as students progress through the full course sequence. Certificate completion is projected to be slightly higher than degree completion due to the shorter unit requirement and accessibility for part-time students and working professionals seeking upskilling or reskilling.

Program Learning Outcomes (SLOs)

Upon completion of this program, students will be able to:

1. Apply artificial intelligence and machine learning concepts to analyze data and develop computational solutions to real-world problems.
2. Develop and evaluate artificial intelligence and machine learning models using appropriate algorithms, datasets, and performance metrics.
3. Implement artificial intelligence and machine learning solutions using industry-standard programming tools, libraries, and development environments.
4. Evaluate the ethical, societal, and security implications and impacts of artificial intelligence and machine learning technologies.

Occupational Preparation (CTE Alignment)

This program prepares students for entry-level roles in artificial intelligence and data-driven computing, including:

Artificial Intelligence / Machine Learning (AI/ML) Technician

Junior Data Analyst (AI-focused roles)

Machine Learning Support Specialist

Entry-Level Software Developer (AI-related applications)

Students completing the program will develop the following core competencies:

Proficiency in Python programming for AI/ML applications

Ability to preprocess, analyze, and interpret structured and unstructured datasets

Development, training, and evaluation of machine learning and deep learning models

Use of industry-standard tools and libraries for model development and analysis

Understanding of modern AI systems, including generative AI and language models

Application of ethical and responsible AI principles

These competencies align with employer expectations and regional labor market demand.

Program Design and Community College Mission

This program fulfills the mission of the California Community Colleges by:

Providing career technical education leading to high-demand, high-wage careers

Expanding access to emerging technology fields for a diverse student population

Offering lifelong learning and upskilling opportunities for working professionals

Including courses designated for transfer

The program is designed at the appropriate level for a community college, focusing on foundational competencies rather than advanced specialization. The curriculum includes transferable lower-division coursework in programming and data science, that may be of interest to students desiring to pursue a degree in a related area of study. consistent with preparation for baccalaureate study in these areas. 

Alignment with Pasadena City College Mission

PCC’s Computer Science department is evolving alongside the tech industry, recently launching a new AS-T degree in Computer Science and new CoA and AS degrees in Data Science. Adding a CoA in AI and Machine Learning reflects a natural and timely expansion, especially as four-year institutions broaden their offerings in this domain. This directly supports Vision 2030’s call for community colleges to lead in innovation and generative AI, while building workforce-aligned programs that support equity and economic mobility.

Need for Skills

The program competencies and curriculum were informed by industry advisory board input. AI/ML skills are in high demand across industries. Like Data Science, this program will attract new and returning adult learners, offering them a future-ready, skills-based pathway. While PCC’s Data Science program introduces foundational ML, a dedicated AI/ML pathway is essential to cover critical and rapidly growing areas such as natural language processing, computer vision, deep learning, AI ethics, and human-centered design—addressing Vision 2030’s emphasis on equitable workforce development and the future of learning.

Adequate Resources

PCC’s current CS/CIS faculty bring relevant expertise and meet minimum teaching qualifications in areas such as AI/Data Science (Prof. Shaw, Prof. Ashraf), AI/Machine Learning (Prof. Levine), AI/Cybersecurity (Prof. Lee), and AI/Natural Language Processing (Prof. Shaw), enabling immediate coverage of core courses. With lab-equipped classrooms already in use by Computer Science and Data Science, no additional facilities or equipment are required. This model aligns with Vision 2030’s focus on using existing infrastructure efficiently to expand high-impact programs for underrepresented and working learners.

The proposed Artificial Intelligence and Machine Learning program directly supports Pasadena City College’s mission to provide a high-quality, academically rigorous learning environment that promotes student success, access, and economic mobility. The program expands access to emerging technology fields and prepares students for both career advancement and continued education, consistent with the College’s commitment to serving a diverse student population.

Alignment with Educational Master Plan (EMP)

The program is strongly aligned with the Educational Master Plan (EMP), particularly the mission-critical priority of Curriculum Responsive to Market Needs, which emphasizes aligning academic programs with labor market demand. The proposed Artificial Intelligence and Machine Learning [EA1] program responds directly to this priority by preparing students for high-demand careers in artificial intelligence and machine learning.

The program also supports additional EMP priorities, including:

Student Success, Equity, and Access by increasing opportunities for disproportionately impacted students to enter high-growth, high-wage STEM fields

Technology by integrating modern computational tools and AI systems into instruction

Pathways (K–12, two-year, four-year, and community connections) by providing a structured pathway that supports both workforce entry and transfer

Life-Long Learning by serving working professionals and adult learners seeking upskilling and reskilling opportunities

Alignment with Statewide Master Planning (Vision 2030)

At the statewide level, the program aligns with the California Community Colleges Vision 2030, particularly its emphasis on equity, workforce development, and innovation in teaching and learning.

The program supports:

Equity in Access and Success by providing inclusive pathways into artificial intelligence and computing fields

Equitable Workforce and Economic Development by preparing students for high-demand, living-wage careers

Innovation in Teaching and Learning through the integration of emerging technologies such as machine learning and generative AI

Program Origins and Development

The development of the Artificial Intelligence and Machine Learning [EA2] program reflects the ongoing evolution of Pasadena City College’s Computer Science curriculum. Building on the recent introduction of Data Science degrees and certificates, the program represents a natural expansion into artificial intelligence and machine learning.

Program development was informed by industry advisory board input and departmental program review processes, which identified a need for expanded coursework in AI, machine learning, and emerging technologies such as generative and agentic AI systems. This process ensures that the curriculum remains responsive to workforce needs and aligned with industry expectations.

Regional Need and Workforce Alignment

The need for the program is supported by regional labor market data indicating strong demand for artificial intelligence and machine learning skills (see Item 1). These fields are associated with high-growth, high-wage occupations and are increasingly important across industries.

The program is designed to address this need by providing students with both foundational and applied skills, supporting entry into the workforce as well as continued education and career advancement.

Relationship to Existing Programs and Non-Duplication

The proposed AI/ML program complements existing programs at Pasadena City College and does not create unnecessary duplication. As discussed in Item 7, the program is distinct from regional offerings in its Computer Science–based approach, comprehensive curriculum, and emphasis on modern AI systems.

The program also complements PCC’s existing Data Science degree and certificate by focusing on model development and intelligent systems, whereas Data Science emphasizes data analysis and interpretation. Together, these programs provide complementary and stackable pathways for students.

Facilities and Resource Considerations

The program will utilize existing facilities and resources within the Computer Science and Data Science programs. Current faculty possess the expertise required to teach the proposed courses, and existing lab-equipped classrooms are sufficient to support instruction. No additional facilities or major equipment expenditures are required to implement the program.

Role within Community College Education

The program is appropriate to the mission and scope of California Community Colleges, as it provides:

Career technical education aligned with workforce demand

Opportunities for lifelong learning, upskilling, and reskilling

Courses designated for transfer that may be of interest to students desiring to pursue a degree in a related area of study

The curriculum is designed at the appropriate level for a community college, focusing on foundational and intermediate competencies rather than advanced specialization.

The proposed Artificial Intelligence and Machine Learning (AI/ML) program will be offered within the Computer Science Department at Pasadena City College and represents an expansion of existing curriculum in computing and data science.

Impact on Existing Inventory

No active programs in the college’s inventory need to be made inactive or modified as a result of this proposal. The proposed AI/ML program does not replace or eliminate any existing programs, nor does it require the termination or scaling down of current offerings.

Relationship to Existing Programs

Pasadena City College currently offers related programs in:

Computer Science (AS-T pathways)

Data Science (AS and Certificate of Achievement)

Software Development (Certificate of Achievement)

The proposed AI/ML program is closely related but distinct from these offerings.

The Computer Science program provides foundational knowledge in programming, algorithms, and computational theory. The AI/ML program builds on this foundation by applying these principles to artificial intelligence and machine learning systems.

The Data Science program focuses on data analysis, statistical methods, and visualization. While it includes introductory machine learning concepts, it does not provide the depth of coursework in AI system development, deep learning, and generative AI that is included in the proposed program.

The CIS program emphasizes applied computing, business applications, and information systems. In contrast, the AI/ML program focuses on computational modeling, algorithmic thinking, and the development of intelligent systems.

Program Role within Curriculum

The AI/ML program complements existing offerings by providing a specialized pathway in artificial intelligence and machine learning, extending beyond the scope of current Computer Science and Data Science programs. It allows students to:

Build on foundational programming and data skills

Develop practical skills in machine learning and AI systems

Pursue pathways aligned with emerging industry demands

Together, these programs form a cohesive and complementary curriculum ecosystem, offering students multiple entry points and pathways in computing, data science, and artificial intelligence without unnecessary duplication.

Pasadena City College conducted a review of similar programs within the Los Angeles and Orange County service area using the Labor Market Information (LMI) report and CCC Curriculum Inventory. Several colleges offer related programs in fields such as Computer Science, Data Science, Computer Information Systems (CIS), and Information Technology (IT). While these programs share some overlapping skills, they differ significantly in scope, structure, and emphasis from the proposed Artificial Intelligence and Machine Learning (AI/ML) program.

Regional Program Landscape

Programs at neighboring colleges generally fall into the following categories:

Computer Science programs (AS-T degrees): These programs emphasize programming, algorithms, and theoretical foundations but typically do not include dedicated coursework in artificial intelligence, machine learning, or emerging areas such as generative AI.

Data Science programs (AS degrees or certificates): These programs focus on data analysis, statistics, and visualization. While some include introductory machine learning, they do not provide the depth of coursework in AI systems, deep learning, or model development included in the proposed program.

CIS/IT programs: These programs focus on applied technologies, systems administration, or business applications of computing. They generally emphasize tools and systems rather than computational modeling or AI development.

Short-term certificates or specialized offerings: Some institutions offer limited coursework or certificates in AI-related topics; however, these are often not part of a cohesive, multi-course sequence and may not support transfer preparation.

Similarities and Differences

The proposed PCC AI/ML program shares foundational elements with regional programs, including programming, data handling, and introductory computing concepts. However, it differs in several key ways:

It is grounded in computer science, emphasizing programming, algorithms, and computational problem-solving

It provides a cohesive, multi-course sequence dedicated specifically to AI/ML

It includes state-of-the-art coursework in:

Machine Learning and Deep Learning

Generative and Agentic AI Systems

Natural Language Processing and Large Language Models

It emphasizes model development, training, and evaluation, rather than solely data analysis or tool usage

These distinctions position the program as more comprehensive and technically rigorous than many existing offerings in the region.

Justification of Need and Capacity

Regional labor market data indicates strong and sustained demand for AI-related skills, with over 6,300 annual job openings projected in the Los Angeles and Orange County region. Despite this demand, the number of program completers across related fields remains insufficient to meet workforce needs.

While approximately 1,440 community college awards are conferred annually in related programs, demand continues to exceed supply. In addition, most existing programs are not specifically focused on artificial intelligence and machine learning as a primary area of study.

The proposed program addresses this gap by offering a focused, modern curriculum aligned with current and emerging industry practices. It expands regional capacity by preparing students with specialized AI/ML skills not consistently covered in existing programs.

Annual Enrollment projects are expected to be greater than the Projected Annual Program Completers: 15 -20 (See above.)

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