Artificial Intelligence and Machine Learning
This award has been submitted to the Department of Education and is pending approval of Title IV Federal Financial Aid.
The Bachelor of Science (BS) in Artificial Intelligence and Machine Learning provides students with the skills needed for designing and developing machine learning models for predictive analysis, automated decision-making, and the augmentation of human capabilities. The program prepares students for careers as developers and engineers in various fields using artificial intelligence, including information technology, automotive, healthcare, aerospace, finance, industrial, semiconductor, and manufacturing industries. Program content includes in-depth coverage of artificial intelligence, statistical machine learning, deep learning, natural language processing, computer vision, hardware-based optimization, and industrial automation. The curriculum emphasizes computer science, mathematics, and engineering content.
Details
Field of Interest
Science, Technology, Engineering and Mathematics
Degree Type
Bachelor of Science (BS)
Academic Plan
Artificial Intelligence and Machine Learning (DEG)
Academic Plan Code
9310
Total credits required
120
Catalog Year
2025-2026
Effective Term
Fall 2025
Notes
Students must earn a grade of C or better in each course in the program.
What You'll Learn
- Design robust software-based solutions applying computer science and engineering principles with an emphasis on artificial intelligence and machine learning.
- Demonstrate proficiency in mathematical concepts and techniques essential for designing, implementing, and optimizing machine learning algorithms to solve complex problems in AI.
- Analyze complex datasets for developing data-driven strategies and solutions that apply statistical techniques and machine learning algorithms.
- Evaluate hardware systems for their processing capabilities as it applies to machine learning algorithms and models.
- Apply ethical principles toward the design and implementation of AI systems.
- Develop effective communication skills for presenting technical information to diverse audiences.
- Apply project management principles to oversee the product lifecycle and meet requirements in diverse and evolving organizational contexts.
- Integrate business requirements into the development and deployment of artificial intelligence solutions to ensure alignment with organizational objectives.
Career statistics
Successful completion of this degree may lead to employment in a variety of different occupations and industries. Below are examples of related occupations with associated Arizona-based wages* for this degree. Education requirements vary for the occupations listed below, so you may need further education or degrees in order to qualify for some of these jobs and earn the related salaries. Please visit with an academic advisor and/or program director for additional information. You can click on any occupation to view the detail regarding education level, wages, and employment information.
Computer and Information Research Scientists
$148,090 Show expanded career information for Computer and Information Research Scientists
Computer Programmers
$79,350 Show expanded career information for Computer Programmers
There are additional career opportunities associated with this degree that do not have occupational data available for Arizona at this time. These occupations are listed below:
- Data Scientists
- Software Developers
* Career and wage information provided by Pipeline AZ using data, reports, and forecasts which are generated using government data sources. Sources
Course Sequence by Term
The following is the suggested course sequence by term. Please keep in mind:
- Students should meet with an academic advisor to develop an individual education plan that meets their academic and career goals. Use the Degree Progress Report Tool in your Student Center to manage your plan.
- The course sequence is laid out by suggested term and may be affected when students enter the program at different times of the year.
- Initial course placement is determined by current district placement measures and/or completion of 100-200 level course and/or program requirements.
- Degree and transfer seeking students may be required to successfully complete a MCCCD First Year Experience Course (FYE) within the first two semesters at a MCCCD College. Courses include FYE101 and FYE103. Course offerings will vary by college. See an academic, program, or faculty advisor for details.
Full-time Sequence
Full-time status is 12 credits to 18 credits per semester.
| Awareness Areas |
|---|
|
Term 1
| Course Number | Course Name | Requisites | Notes | Area | Credits |
|---|---|---|---|---|---|
| AIM100 | Introduction to Artificial Intelligence | 3 | |||
| CSC101 | Introduction to Computing with Python | 3 | |||
| MAT220 or MAT221 |
Calculus with Analytic Geometry I or Calculus with Analytic Geometry I | MA or MA | 4–5 | ||
| ENG101 or ENG107 |
First-Year Composition or First-Year Composition for ESL | FYC or FYC | 3 | ||
| FYE101 or FYE103 |
Introduction to College, Career and Personal Success or Exploration of College, Career and Personal Success | 1–3 |
Term 2
| Course Number | Course Name | Requisites | Notes | Area | Credits |
|---|---|---|---|---|---|
| AIM111 | Introduction to Data Science | 3 | |||
| CSC100 or CSC100AA or CSC100AB or CSC110 or CSC110AA or CSC110AB |
Introduction to Computer Science (C++) or Introduction to Computer Science (C++) or Introduction to Computer Science (C++) or Introduction to Computer Science (Java) or Introduction to Computer Science (Java) or Introduction to Computer Science (Java) | CS or CS or CS or CS or CS or CS | 3–4 | ||
| MAT230 or MAT231 |
Calculus with Analytic Geometry II or Calculus with Analytic Geometry II | MA or MA | 4–5 | ||
| ENG102 or ENG108 |
First-Year Composition or First-Year Composition for ESL | FYC or FYC | 3 | ||
| COM100 or COM110 or COM225 or COM230 or COM263 |
Introduction to Human Communication or Interpersonal Communication or Public Speaking or Small Group Communication or Elements of Intercultural Communication | SB or SB or L or SB or C, G, SB | 0–3 |
Term 3
| Course Number | Course Name | Requisites | Notes | Area | Credits |
|---|---|---|---|---|---|
| CSC/EEE120 | Digital Design Fundamentals | CS | 4 | ||
| CSC205 or CSC205AA or CSC205AB |
Object Oriented Programming and Data Structures or Object Oriented Programming and Data Structures or Object Oriented Programming and Data Structures | CS or CS or CS | 3–4 | ||
| MAT225 | Elementary Linear Algebra | 3 | |||
| MAT206 | Elements of Statistics | CS | 3 |
Term 4
| Course Number | Course Name | Requisites | Notes | Area | Credits |
|---|---|---|---|---|---|
| AIM250 | + AIM250 Machine Learning | 3 | |||
| CSC240 or CSC240AA |
Introduction to Different Programming Languages or Introduction to Different Programming Languages | 3–4 | |||
| MAT227 | Discrete Mathematical Structures | 3 | |||
| ECE150 | Exploring Engineering and its Impact on Society | 3 | |||
| SQ | Natural Sciences Quantitative | Sequential university level BIO, CHM, or PHY | SQ | 4 |
Term 5
| Course Number | Course Name | Requisites | Notes | Area | Credits |
|---|---|---|---|---|---|
| BAM310 | BAM310 Machine Learning II: Deep Learning | 3 | |||
| BAM/MAT305 | Mathematics for Machine Learning | 3 | |||
| CSC310 | Data Structures and Algorithms | 3 | |||
| SQ | Natural Sciences Quantitative | Sequential university level BIO, CHM, or PHY | SQ | 4 |
Term 6
| Course Number | Course Name | Requisites | Notes | Area | Credits |
|---|---|---|---|---|---|
| BAM320 | Computer Vision | 3 | |||
| BAM330 | Natural Language Processing | 3 | |||
| CSC/EEE230 | Computer Organization and Assembly Language | 4 | |||
| HU | Humanities, Fine Arts & Design | Recommend additional designations: L, C, H/G | HU | 3 | |
| SB | Social-Behavioral Sciences | Recommend additional designations: L, C, H/G | SB | 3 | |
| L | Literacy & Critical Inquiry | Recommend additional designations: L, C, H/G | L | 0–3 |
Term 7
| Course Number | Course Name | Requisites | Notes | Area | Credits |
|---|---|---|---|---|---|
| BAM440 | Hardware Optimization for Machine Learning | 3 | |||
| BAM490 | Capstone Project I | 3 | |||
| CSC350 | Logic Programming for Artificial Intelligence | 3 | |||
| RE | Restricted Elective | Students should consult with their college’s Program Director or their faculty or academic advisor to select courses from the list to complete a minimum of 120 total semester credits. | 0–3 | ||
| RE | Restricted Elective | 0–3 |
Term 8
| Course Number | Course Name | Requisites | Notes | Area | Credits |
|---|---|---|---|---|---|
| BAM450 | Planning and Optimization for Automation | 3 | |||
| BAM499 | Capstone Project II | 3 | |||
| RE | Restricted Elective | Students should consult with their college’s Program Director or their faculty or academic advisor to select courses from the list to complete a minimum of 120 total semester credits. | 0–3 | ||
| RE | Restricted Elective | 0–3 | |||
| SB | Social-Behavioral Sciences | Recommend additional designations: L, C, H/G | SB | 3 |
Footnote
Restricted Electives
Students should consult with their college’s Program Director or their faculty or academic advisor to select courses that best align with academic and professional goals.
Students should select 0-12 credits from the following list of courses to complete a minimum of 120 total semester credits:
AIM110 Introduction to Machine Learning 3
AIM210 Natural Language Processing 3
AIM220 Artificial Intelligence for Computer Vision 3
AIM230 Artificial Intelligence for Business Solutions 3
AIM240 Artificial Intelligence Capstone Project 3
CIS119DO Introduction to Oracle: SQL 3
CIS276DA MySQL Database 3
CIS276DB SQL Server Database 3
ECE105 MATLAB Programming 1
MAT240 Calculus with Analytic Geometry III (5) OR
MAT241 Calculus with Analytic Geometry III (4) 4-5
MAT276 Modern Differential Equations (4) OR
MAT277 Modern Differential Equations (3) 3-4
Course Area Key
- C = Cultural Diversity in the US
- CS = Computer/Statistics/Quantitative Application
- FYC = First Year Composition
- G = Global Awareness
- HU = Humanities, Fine Arts, and Design
- L = Literacy & Critical Inquiry
- MA = Mathematics
- SB = Social-Behavioral Sciences
- SQ = Natural Sciences Quantitative
Disclaimer
Students must earn a grade of C or better in all courses within the program.
Course Sequence total credits may differ from the program information located on the MCCCD curriculum website due to program and system design.
View MCCCD’s official curriculum documentation for additional details regarding the requirements of this award (https://aztransmac2.asu.edu/cgi-bin/WebObjects/MCCCD.woa/wa/freeForm10?id=189188).
At Maricopa, we strive to provide you with accurate and current information about our degree and certificate offerings. Due to the dynamic nature of the curriculum process, course and program information is subject to change. As a result, the course list associated with this degree or certificate on this site does not represent a contract, nor does it guarantee course availability. If you are interested in pursuing this degree or certificate, we encourage you to meet with an advisor to discuss the requirements at your college for the appropriate catalog year.