LCCC Catalog 2025-2026

Apr 04, 2025

LCCC Catalog 2025-2026

Artificial Intelligence, AAS

Location(s): Cheyenne Campus; Online

Print Degree Planner (opens a new window) |

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. The competencies of TREX 2000 are embedded into this program to ensure students benefit from and complete the requirements of the Transition Experience prior to graduating from LCCC.

Contact Information

Contact information is available on the Artificial Intelligence website.

Map your individual academic plan of courses with your Student Success Coach.

If students choose to transition to another program within the STEM pathway, they should be particularly aware of the choice points that indicate when a decision to branch off into another program must be made to ensure credits and time are not lost.

Coursework common to all degrees within this pathway is indicated by CAC, Common Academic Coursework, in the program map.

Competencies

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

Evaluate business problems using common artificial intelligence (AI) concepts and methodologies, including neural networks/Deep Learning, machine learning, Natural Language Processing, Computer Vision, for analysis and decision making.
Solve social and business issues by applying artificial intelligence (AI) project development principles and appropriate machine learning cycles.
Evaluate usefulness of artificial intelligence (AI) programming solutions with statistical analysis and machine learning algorithms.
Create artificial intelligence solutions using appropriate programming languages.
Communicate in varied settings, orally and visually and in writing, in a culturally responsive manner.
Create artificial intelligence using machine learning solutions/principles.
Collaborate with diverse individuals and teams.
Evaluate issues of bias, culture, environment, ethics, regulations, and professional expectations in the field of artificial intelligence (AI) and machine learning.

First Semester

Course Requirements

AIML 1010 - Introduction to Artificial Intelligence Credits: 3
AIML 1020 - Ethics in Artificial Intelligence Credits: 3
COSC 1010 - Intro to Computer Science Credits: 4
STAT 2050 - Fundamentals of Statistics Credits: 4
STRT 1000 - Strategies for Success Credits: 3 | CAC

Milestones

Students are introduced to AI concepts.

Semester Total: 17 Credits

Second Semester

Choice Points

Students interested in understanding the mathmatical foundations of AI should take MATH 1400 .
See Program Comments below regarding Math course options if students place higher than MATH 1400 .
Students interested in applied AI software development should take COSC 2409 .

Course Requirements

AIML 1030 - Introduction to Machine Learning Credits: 3
CMAP 1815 - Database Applications Credits: 3
ENGL 1010 - English Composition I Credits: 3 | CAC
Choose an approved U.S./Wyoming Constitution course Credits: 3 | CAC
MATH 1400 - College Algebra Credits: 3 | CAC
OR
COSC 2409 - Programming Credits: 3

Milestones

Students develop a solid foundation in data management and AI techniques to prepare for advanced AI applications and projects.

Semester Total: 15 Credits

Third Semester

Choice Points

Students interested in understanding the mathmatical foundations of AI should take MATH 1405 during the summer semester.

Course Requirements

MATH 1405 - Trigonometry Credits: 3

Semester Total: 3 Credits

Fourth Semester

Choice Points

Students interested in understanding the mathmatical foundations of AI should take MATH 2200 .
Students interested in applied AI software development should take COSC 1030 .

Course Requirements

AIML 2030 - Natural Language Processing Credits: 3
AIML 2040 - Computer Vision Credits: 3
COMM 1015 - Foundations of Communication Credits: 3
OR
COMM 2010 - Public Speaking Credits: 3 | CAC
MATH 2200 - Calculus I Credits: 4
OR
COSC 1030 - Computer Science I Credits: 4

Milestones

Students will have the fundamental tools to apply and build AI products.

Semester Total: 13 Credits

Fifth Semester

Choice Points

Students interested in understanding the mathmatical foundations of AI should take MATH 2250 .
Students interested in applied AI software development should take COSC 2030 .

Course Requirements

AIML 2050 - Artificial Intelligence for Business Solutions Credits: 3
AIML 2395 - Artificial Intelligence Capstone Credits: 3
COSC 2060 - Data Engineering Credits: 3
HMDV 1510 - Professionalism in the Workplace Credits: 3
MATH 2250 - Elementary Linear Algebra Credits: 3
OR
COSC 2030 - Computer Science II Credits: 4

Milestones

Completion of Artificial Intelligence, AAS.

Semester Total: 15-16 Credits

Program Credit Hour Total: 63-64 Credits

Program Comments

The information below is intended to be a guide, and does not guarantee regional job placement, job availability, or a specific wage after completion of the program.

The AI program offers two focused tracks designed to get students job-ready faster: Mathematics and Computer Science. These specializations equip students with the in-demand skills for entry-level positions in the booming AI field.

Mathematics for AI:

Develop strong problem-solving skills and logical thinking
Build a solid foundation in mathematical concepts, including linear algebra and calculus
Prepare for careers in AI, data science, and related fields, with a deep understanding of mathematical principles

Computer Science for AI:

Gain programming skills in Python and C++
Develop problem-solving skills and logical thinking
Prepare for entry-level positions in software development, data analysis, and IT

Both tracks will equip students with a solid foundation in AI, but the chosen specialization will provide a sharper edge for entry-level positions in today’s AI job market. Possible careers related to AI with a mathmatical foundtion include AI/ML Technician, Data Analyst, Business Intelligence Analyst, Operations Research Assistant, and Statistical Technician. Possible careers related to AI with a computer science foundation include Junior AI/ML Engineer, Data Science Analyst, AI/ML Data Analyst, Natural Language Processing (NLP) Technician, and Computer Vision Technician.

Additional information on careers in Artificial Intelligence is available through Career Coach.

Transfer Information

This degree is well suited for those who may be interested in pursuing a Bachelor of Applied Science degree at Laramie County Community College.

LCCC courses may transfer to institutions in addition to those above with formal articulation agreements. Students are strongly encouraged to determine the degree requirements and transfer policy of the specific college/university and program to which they plan to transfer.