Academic Catalogs

CHT A090N: Artificial Intelligence: Basic Concepts & Applications

Course Outline of Record
Item Value
Eff Term Fall 2026
Curriculum Committee Approval Date 10/15/2025
Top Code 051400 - Office Technology/Office Computer Applications (CTE)
Units 0 Total Units 
Hours 27 Total Hours (Lecture Hours 27-36)
Total Outside of Class Hours 0
Total Student Learning Hours 27
Course Credit Status Noncredit (N)
Material Fee No
Basic Skills Not Basic Skills (N)
Repeatable Yes; Repeat Limit 99
Open Entry/Open Exit No
Grading Policy P/NP/SP Non-Credit (D)

Course Description

This noncredit course introduces the basic understanding of Artificial Intelligence (AI) and its use in the world today. Students will explore history, key concepts, ethical concerns and learn how it can be used in everyday life. By the end of the course, students will understand AI fundamentals and skills to apply AI tools and technologies in real-world scenarios. Not Transferable.

Course Level Student Learning Outcome(s)

  1. Differentiate between key AI concepts such as machine learning, neural networks, and natural language processing.
  2. Analyze a real-world dataset using an AI tool to generate insights or solutions, demonstrating foundational skills in AI-assisted problem solving.

Course Objectives

  • 1. Understand the history, definition, and real-world applications of AI across industries.
  • 2. Identify core AI concepts such as machine learning, neural networks, and deep learning.
  • 3. Explain basic principles and applications of Natural Language Processing (NLP).
  • 4. Describe how AI is used in robotics and automation.
  • 5. Recognize key ethical issues related to AI, including bias and data privacy.
  • 6. Apply basic AI tools in hands-on projects to solve practical problems.

Lecture Content

Introduction to Artificial Intelligence 

  • History and definition
  • Applications of AI in industries including healthcare, education, and business 

Fundamental Concepts 

  • Key areas of AI
    • Machine learning
    • Neural networks
    • Deep learning 

Machine Learning Basics 

  • Supervised vs. unsupervised learning
  • Algorithms
    • Decision trees
    • Linear regression 

Natural Language Processing (NLP) 

  • Introduction to language models
  • Text processing
  • Applications like chatbots and sentiment analysis 

Robotics and Automation 

  • AI in robotics
  • Autonomous systems
  • Real-world examples of automation 

Ethics and AI 

  • Ethical concerns surrounding AI
    • Bias
    • Data privacy
    • Impact on employment

Hands-on Projects 

  • Applying AI tools to solve practical problems and analyze datasets 

AI Trends and Future Outlook 

  • Future AI developments
  • Potential societal changes 
  • Preparing for the future of AI 

Method(s) of Instruction

  • Enhanced NC Lect (NC1)
  • Live Online Enhanced NC Lect (NC9)
  • Online Enhanced NC Lect (NC5)

Instructional Techniques

Lecture and application of ideas. Demonstration and practice of problem-solving. Digital presentations and video.

Reading Assignments

Assigned readings from books, websites, PowerPoints, and content pages.

Writing Assignments

Provide written feedback from peer reviews, reflections on skills learned, and how they relate to real-world scenarios.

Out-of-class Assignments

Practice activities, videos related to course topics

Methods of Student Evaluation

  • Short Quizzes
  • Written Assignments
  • Projects (Individual/Group)
  • Oral Presentations
  • Skills Demonstration

Demonstration of Critical Thinking

Students demonstrate critical thinking by comparing real-world AI applications in different industries.

Required Writing, Problem Solving, Skills Demonstration

Hands-on demonstration using AI tools to solve an everyday challenge.

Other Resources

1. Instructor provided handouts

Resources Subscreen

  • Other: . . ().

Eligible Discipline(s)

  • Office technologies (secretarial skills, office systems, word processing, computer applications, automated office training): Any bachelor’s degree and two years of professional experience, or any associate degree and six years of professional experience.
  • Computer information systems (computer network installation, microcomputer technology, computer applications): Any bachelor’s degree and two years of professional experience, or any associate degree and six years of professional experience.