Artificial Intelligence and Machine Learning

The Associate in Applied Science (AAS) in Artificial Intelligence and Machine Learning focuses on building machine learning models that can be used for predicting, making decisions and enhancing human capabilities. The program prepares students for entry level positions in a variety of fields using artificial intelligence, including the information technology, automotive, healthcare, aerospace, industrial, and manufacturing industries. Program content includes an introduction to artificial intelligence and machine learning, natural language processing, computer vision, and artificial intelligence for business solutions and other applications. The curriculum also includes coursework in computer programming, math, engineering, and statistics.

Details

Field of Interest
Science, Technology, Engineering and Mathematics
Degree Type
Associate in Applied Science (AAS)
Academic Plan
Artificial Intelligence and Machine Learning (DEG)
Academic Plan Code
3891
Total credits required
61-76
Catalog Year
2023-2024
Effective Term
Fall 2022
Notes

Students must earn a grade of C or better for all courses required within the program.

What You'll Learn

This pathway map will help you gain the expertise needed to:

  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.
  2. Apply artificial intelligence (AI) project development and machine learning life cycle to address social and business issues, opportunities, and problems.
  3. Apply statistical analysis and machine learning algorithms to predict usefulness of artificial intelligence (AI) programming solutions.
  4. Use appropriate programming languages to implement artificial intelligence (AI) solutions.
  5. Communicate in varied settings, orally and visually and in writing, in a culturally responsive manner.
  6. Collaborate with diverse individuals and teams to design and implement artificial intelligence and machine learning solutions.
  7. Evaluate issues of bias, culture, environment, ethics, regulations, and professional expectations in the field of artificial intelligence (AI) and machine learning.
  8. Apply relevant knowledge, skills, and habits of mind to seek career opportunities in the field.

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 annual median wages* for this program. 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.

Computer and Information Research Scientists

$141,440

Software Developers and Software Quality Assurance Analysts and Testers

$99,330

* Wage information sourced from the Bureau of Labor Statistics, Occupational Employment Statistics Program. Updated May 2019.

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 Pathway Planner 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.
  • Consult with your faculty mentor or academic advisor to determine educational requirements, including possible university transfer options, for your chosen career field.

Full-time Sequence

Full-time status is 12 credits to 18 credits per semester.

Term 1

A sequence of suggested courses that should be taken during Term 1
Course Number Course Name Requisites Notes Area Credits
AIM100 Introduction to Artificial Intelligence Critical course Gateway course 3
CIS105 Survey of Computer Information Systems May be waived by permission of the Program Director CS 0–3
MA Any approved general education course in the Mathematical Applications [MA] area (that serves as a prerequisite for) MAT22+. MA 0–9
FYE101 or
FYE103
Introduction to College, Career and Personal Success or Exploration of College, Career and Personal Success 1–3

Term 2

A sequence of suggested courses that should be taken during Term 2
Course Number Course Name Requisites Notes Area Credits
ENG101 or
ENG107
First-Year Composition or First-Year Composition for ESL FYC 3
MAT206 Elements of Statistics Critical course CS 3
CIS156 Python Programming: Level I Critical course 3
CIS119DO or
CIS276DA or
CIS276DB
Introduction to Oracle: SQL or MySQL Database or SQL Server Database 3
ECE102 Engineering Analysis Tools and Techniques 2

Term 3

A sequence of suggested courses that should be taken during Term 3
Course Number Course Name Requisites Notes Area Credits
MAT220 or
MAT221
Calculus with Analytic Geometry I or Calculus with Analytic Geometry I MA 4–5
AIM110 Introduction to Machine Learning Critical course 3
ECE103 Engineering Problem Solving and Design 2
ENG102 or
ENG108
First-Year Composition or First-Year Composition for ESL FYC 3
RE Restricted Elective 0–3

Term 4

A sequence of suggested courses that should be taken during Term 4
Course Number Course Name Requisites Notes Area Credits
CRE101 College Critical Reading and Critical Thinking L 0–3
MAT225 Elementary Linear Algebra 3
AIM210 Natural Language Processing 3
AIM220 Artificial Intelligence for Computer Vision 3
SG or SQ Natural Sciences Any approved general education course in the Natural Sciences area. 4
COM100 or
COM110 or
COM225 or
COM230
Introduction to Human Communication or Interpersonal Communication or Public Speaking or Small Group Communication Or any approved general education course from the Oral Communication area SB or L 3

Term 5

A sequence of suggested courses that should be taken during Term 5
Course Number Course Name Requisites Notes Area Credits
AIM230 Artificial Intelligence for Business Solutions 3
AIM240 Artificial Intelligence Capstone Project 3
HU Humanities, Fine Arts & Design HU 3
SB Social-Behavioral Sciences Recommend PSY101 or SOC101 SB 3

Restricted Electives:

Select a programming language from below that best aligns with academic and professional goals (to complete the minimum total program credits required for this degree) in one of the following areas:

A list of additional, alternative, or supplemental courses for this pathway map
Course Number Course Name Requisites Notes Area Credits
CIS150 Programming Fundamentals 3
CIS150AB Object-Oriented Programming Fundamentals 3
CIS159 Visual Basic Programming I 3
CIS162++ Any C Programming: Level I course 3
CIS163AA Java Programming: Level I CS 3
CIS165++ Any Mobile Application Development course 3
CSC100++ Introduction to Computer Science (C++) 3–4
CSC110++ Introduction to Computer Science (Java) 3–4

Part-time Sequence

Part-time status is 11 credit hours or less.

Term 1

A sequence of suggested courses that should be taken during Term 1
Course Number Course Name Requisites Notes Area Credits
CIS105 Survey of Computer Information Systems May be waived by permission of the Program Director CS 0–3
ENG101 or
ENG107
First-Year Composition or First-Year Composition for ESL FYC 3
MA Any approved general education course in the Mathematical Applications [MA] area (that serves as a prerequisite for) MAT22+. MA 0–9
FYE101 or
FYE103
Introduction to College, Career and Personal Success or Exploration of College, Career and Personal Success 1–3

Term 2

A sequence of suggested courses that should be taken during Term 2
Course Number Course Name Requisites Notes Area Credits
AIM100 Introduction to Artificial Intelligence Critical course Gateway course 3
ENG102 or
ENG108
First-Year Composition or First-Year Composition for ESL FYC 3

Term 3

A sequence of suggested courses that should be taken during Term 3
Course Number Course Name Requisites Notes Area Credits
MAT206 Elements of Statistics Critical course CS 3
CIS156 Python Programming: Level I Critical course 3
ECE102 Engineering Analysis Tools and Techniques 2

Term 4

A sequence of suggested courses that should be taken during Term 4
Course Number Course Name Requisites Notes Area Credits
MAT220 or
MAT221
Calculus with Analytic Geometry I or Calculus with Analytic Geometry I MA 4–5
AIM110 Introduction to Machine Learning Critical course 3

Term 5

A sequence of suggested courses that should be taken during Term 5
Course Number Course Name Requisites Notes Area Credits
CIS119DO or
CIS276DA or
CIS276DB
Introduction to Oracle: SQL or MySQL Database or SQL Server Database 3
ECE103 Engineering Problem Solving and Design 2
MAT225 Elementary Linear Algebra 3

Term 6

A sequence of suggested courses that should be taken during Term 6
Course Number Course Name Requisites Notes Area Credits
AIM210 Natural Language Processing 3
CRE101 College Critical Reading and Critical Thinking L 0–3

Term 7

A sequence of suggested courses that should be taken during Term 7
Course Number Course Name Requisites Notes Area Credits
AIM220 Artificial Intelligence for Computer Vision 3
AIM230 Artificial Intelligence for Business Solutions 3

Term 8

A sequence of suggested courses that should be taken during Term 8
Course Number Course Name Requisites Notes Area Credits
SG or SQ Natural Sciences Any approved general education course in the Natural Sciences area. 4
AIM240 Artificial Intelligence Capstone Project 3

Term 9

A sequence of suggested courses that should be taken during Term 9
Course Number Course Name Requisites Notes Area Credits
HU Humanities, Fine Arts & Design HU 3
SB Social-Behavioral Sciences Recommend PSY101 or SOC101 SB 3

Term 10

A sequence of suggested courses that should be taken during Term 10
Course Number Course Name Requisites Notes Area Credits
RE Restricted Elective 0–3
COM100 or
COM110 or
COM225 or
COM230
Introduction to Human Communication or Interpersonal Communication or Public Speaking or Small Group Communication Or any approved general education course from the Oral Communication area SB or L 3

Restricted Electives:

Select a programming language from below that best aligns with academic and professional goals (to complete the minimum total program credits required for this degree) in one of the following areas:

A list of additional, alternative, or supplemental courses for this pathway map
Course Number Course Name Requisites Notes Area Credits
CIS150 Programming Fundamentals 3
CIS150AB Object-Oriented Programming Fundamentals 3
CIS159 Visual Basic Programming I 3
CIS162++ Any C Programming: Level I course 3
CIS163AA Java Programming: Level I CS 3
CIS165++ Any Mobile Application Development course 3
CSC100++ Introduction to Computer Science (C++) 3–4
CSC110++ Introduction to Computer Science (Java) 3–4
Course Area Key

Gateway Course = Generally the first major-specific course in a pathway.

Critical Course = A course that is highly predictive of future success in a pathway.

Disclaimer

Students must earn a grade of C or better for all courses required 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 curriculum website for the Associate in Applied Science in Artificial Intelligence and Machine Learning (https://aztransmac2.asu.edu/cgi-bin/WebObjects/MCCCD.woa/wa/freeForm13?id=176790).

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.

Previous Catalog Years

The pathway map presented above is for the current catalog year and is the intended pathway map for new students. All previous catalog years for this pathway map are available at the link below.