Introduction to AI and Machine Learning

About the Course

We have received support for our online Artificial Intelligence courses and will be able to offer them free of charge.   The Upskilling Grant, however, has very specific eligibility requirements.   NYS Department of Labor requires our students to (1) be legally permitted to work in the U.S., (2) be a New York resident, (3) unemployed or underemployed, and (4) be able to provide a Social Security Number as part of the application.  

Registration is open.  Applicants have to be eligible to participate.  

This course offers a beginner-friendly introduction to Artificial Intelligence (AI) and Machine Learning (ML). Students will explore how AI technologies recognize patterns, make predictions, and automate decisions—core components of machine learning. Through real-world examples and simplified explanations, the course ensures a broad understanding of AI's potential to reshape industries like healthcare, finance, and entertainment.

By the end of the course, students will understand key AI and machine learning concepts, explore ethical considerations like AI bias, and analyze future trends in AI development. This course is suitable for those with no prior experience in AI or ML.

Curriculum Includes:

• Introduction to AI Concepts and History
• Machine Learning Basics and Algorithms
• Neural Networks and Deep Learning
• Applications of AI in Various Sectors
• AI Ethics: Bias and Fairness
• Future Trends in AI and Machine Learning

Course Learning Outcomes

By the end of this course, students will be able to:

1. Understand and explain fundamental concepts of AI and machine learning.
2. Apply basic machine learning techniques to solve real-world problems.
3. Analyze the ethical implications of AI, including bias and fairness.
4. Recognize the potential of AI across industries and explore future trends.

Required Text

Online Educational Resource: Introduction to AI and Machine Learning: Beginners Edition by Professor Carlos J. Garcia, provided as an ebook through the course platform.

This course equips beginners with the knowledge needed to engage with AI technologies responsibly and prepares them for further exploration in AI and machine learning.

Eligibility

We have received support for our online Artificial Intelligence courses and will be able to offer them free of charge.   The Upskilling Grant, however, has very specific eligibility requirements.   NYS Department of Labor requires our students to (1) be legally permitted to work in the U.S., (2) be a New York resident, (3) unemployed or underemployed, and (4) be able to provide a Social Security Number as part of the application.  

Registration is open.  Applicants have to be eligible to participate.  

Register Here

Schedule

Fall 2024:  Introduction to Artificial Intelligence and Machine Learning, 11/18/2024-12/18/2024, 6:00-8:00, Mondays and Wednesdays, ONLINE

Total Instructional Hours: 18; Total Sessions: 8

Spring 2025:  Introduction to Artificial Intelligence and Machine Learning (same syllabus as Fall class), 1/22/2025-3/5/2025. 6:00-8:00, Mondays and Wednesdays, ONLINE

Total Instructional Hours: 18; Total Sessions: 9

Instructor 

Professor Carlos J. Garcia brings a wealth of experience in AI and machine learning with a solid foundation in cybersecurity, networking, and law enforcement education.

With a Master of Science in Information Assurance from Eastern Michigan University and numerous certifications in IT and public safety, Professor Garcia has been at the forefront of cybersecurity and digital forensics education. He played a pivotal role in initiating the cybersecurity curriculum for high schools in Michigan, significantly shaping the state's approach to cybersecurity education. As a tenure-track Assistant Professor at SUNY Westchester Community College and an adjunct professor at Eastern Michigan University, he has developed and administered a wide range of curriculum materials across various teaching platforms, from traditional classrooms to asynchronous online courses. At Eastern Michigan University, he has taught through the master's level, contributing to the development of courses in Information Assurance.

Known for his dynamic presentations and deep industry knowledge, Professor Garcia has guided numerous learners through complex IT topics and practical applications in both educational and industry settings. He was also a co-chair for the National Initiative for Cybersecurity Education (NICE) committee at NIST, where he contributed to shaping national strategies on cybersecurity education, training, and workforce development. His leadership extends into national cybersecurity defense competitions and significant contributions to community and professional educational initiatives, making him a distinguished figure in the fields of AI, cybersecurity, and public safety education.

Register Here