4/26/2025 7:50:44 PM	BAD 81 Course Outline as of Fall 2025	New Course (First Version)
CATALOG INFORMATION
Discipline and Nbr:  BAD 81	Title:  AI IN BUSINESS
Full Title:  Artificial Intelligence in Business
Last Reviewed:12/9/2024

Units		Course Hours per Week			Nbr of Weeks	Course Hours Total
Maximum	3.00	Lecture Scheduled	3.00		17.5 max.	Lecture Scheduled	52.50
Minimum	3.00	Lab Scheduled	0		6 min.	Lab Scheduled	0
		Contact DHR	0			Contact DHR	0
		Contact Total	3.00			Contact Total	52.50
		Non-contact DHR	0			Non-contact DHR Total	0

Total Out of Class Hours:  105.00

Total Student Learning Hours: 157.50

Title 5 Category:  AA Degree Applicable
Grading:  Grade or P/NP
Repeatability:  00 - Two Repeats if Grade was D, F, NC, or NP
Also Listed As: 
Formerly: 

Catalog Description:

Students will be introduced to the basics of Artificial Intelligence (AI) and its application in the business environment. Topics will include the history and scope of AI, ethical implications, use of generative AI including textual and visual/video applications, use of predictive/analytic AI in business, Big Data, and the application of AI in human resources.

 

 

 

Prerequisites/Corequisites:

Recommended Preparation:
Eligibility for ENGL C1000 or equivalent

Limits on Enrollment:

Schedule of Classes Information
Description:

Students will be introduced to the basics of Artificial Intelligence (AI) and its application in the business environment. Topics will include the history and scope of AI, ethical implications, use of generative AI including textual and visual/video applications, use of predictive/analytic AI in business, Big Data, and the application of AI in human resources.

 

 

 

 

(Grade or P/NP)
Prerequisites:
Recommended:Eligibility for ENGL C1000 or equivalent
Limits on Enrollment:
Transfer Credit:CSU;
Repeatability:00 - Two Repeats if Grade was D, F, NC, or NP

ARTICULATION, MAJOR, and CERTIFICATION INFORMATION

Associate Degree:		Effective:		Inactive:
Area:
CSU GE:	Transfer Area			Effective:	Inactive:
IGETC:	Transfer Area			Effective:	Inactive:
CSU Transfer:	Transferable	Effective:	Fall 2025	Inactive:
UC Transfer:		Effective:		Inactive:
C-ID:

Certificate/Major Applicable: Certificate Applicable Course

COURSE CONTENT

Student Learning Outcomes:
At the conclusion of this course, the student should be able to:

1. Understand and describe the history, development, and ethical implications of AI in relation to business.

2. Appraise opportunities for implementing generative and analytic/predictive AI in business.

3. Create and edit business materials and communications using generative AI.

4. Evaluate business data using analytic AI. 

 

Objectives:

At the conclusion of this course, the student should be able to:

1. Compare and contrast generative and analytic/predictive AI.

2. Construct prompts and generate accurate and goal-oriented outcomes from generative and analytic/predictive AI.

3. Make use of analytic/predictive AI as a business research tool.

4. Develop a training plan and module using generative AI.

5. Create resumes, cover letters, business communications, sales and marketing materials, and presentations using generative AI.

6. Apply generative and analytic/predictive AI to human resource functions.

7. Describe how AI is used in business data analysis and apply analytic/predictive AI to a basic small business data set.

Topics and Scope

I. History of AI

II. AI and Ethics: Generative and Analytic/Predictive

    A. Ethics and training  

     B. Ethical use  

III. Effective Use of AI to Achieve Goal-oriented Outcomes

    A. Choosing the proper AI tool

    B. Effective use of prompts

IV. AI and Business Communication

    A. Marketing

    B. Business presentations

    C. Job-related communications

    D. Customer service AI

    E. Creating and editing resumes and cover letters

V. AI and Accessibility

    A. Disability access

    B. Multilingual users

VI. Overview of the Role of Data Analytics and Big Data in Generative AI

VII. AI and Business Research

VIII. AI and Human Resources

    A. Hiring process

    B. Training

    C. Accessibility

IX. The Future of AI in Business

Assignments:

1. Weekly AI practice assignments

2. Ethics reflections paper

3. AI marketing project

4. AI-generated resume and cover letter

5. Data analytics project

6. AI human resources project

7. Final team presentation

8. Reading assignments of approximately 30 pages per week from text and/or handouts

Methods of Evaluation/Basis of Grade.

Writing: Assessment tools that demonstrate writing skill and/or require students to select, organize and explain ideas in writing.		Writing 5 - 20%
Ethics Reflections Paper
Problem solving: Assessment tools, other than exams, that demonstrate competence in computational or non-computational problem solving skills.		Problem Solving 10 - 20%
Data analytics project, AI human resources project
Skill Demonstrations: All skill-based and physical demonstrations used for assessment purposes including skill performance exams.		Skill Demonstrations 40 - 60%
Weekly AI practice assignments, AI Marketing Project, AI-generated resume & cover letter
Exams: All forms of formal testing, other than skill performance exams.		Exams 0 - 0%
None
Other: Includes any assessment tools that do not logically fit into the above categories.		Other Category 5 - 20%
Final team presentation

Representative Textbooks and Materials:

Instructor prepared materials

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