Home Catalog Programs of Study List of Programs Artificial Intelligence

Artificial Intelligence

Folsom Lake College's artificial intelligence (AI) department fosters innovation, meets industry demands, and advances education in a rapidly evolving field. It provides a structured platform for AI. By offering a range of courses, from foundational subjects to advanced topics, the department prepares students with the skills needed to tackle real-world AI challenges. It also promotes interdisciplinary collaboration, ensuring AI professionals understand their work's ethical implications and societal impacts.

Certificates Offered

Artificial Intelligence and Machine Learning Certificate

Division Dean Dr. Lorena Navarro
Department Chair Dr. Suha Al Juboori
Phone (916) 608-6615
Email navarrl@flc.losrios.edu

Certificate of Achievement

Artificial Intelligence and Machine Learning Certificate

Artificial Intelligence and Machine Learning certificate focuses on building machine learning models that can be used for predicting, making decisions and enhancing human capabilities. The program provides opportunities to develop the necessary skills and basic aptitudes in Artificial Intelligence and Machine Learning that is required in different fields including the information technology, automotive, healthcare, aerospace, industrial, and manufacturing industries.

Catalog Date: August 1, 2026

Certificate Requirements

Course Code	Course Title	Units
AI 300	Introduction to Artificial Intelligence and Machine Learning	3
AI 310	Machine Learning	3
AI 305	Ethics and Artificial Intelligence	3
AI 311	Python for Applied AI and Visualization (4)	4
or CISP 407	Programming in Python (4)
AI 312	Natural Language Processing I (3)	3
or AI 314	Computer Vision I (3)
Total Units:		16

Student Learning Outcomes

Upon completion of this program, the student will be able to:

explain how artificial intelligence and machine learning is useful in business or career.
apply common artificial intelligence (AI) concepts and methodologies.
utilize methods of machine learning and deep learning to build and run analytical models.
explain how to use existing artificial intelligence and machine learning programming libraries on a data set to create a valid model that justifies their design decisions.

Career Information

Artificial intelligence programmer, machine learning engineer, data scientist, and business intelligence developer are possible job opportunities. The program provides the industry professional with the knowledge and skills used in a variety of fields using artificial intelligence.

Artificial Intelligence (AI) Courses

AI 299 Experimental Offering in Artificial Intelligence

Units:0.5 - 4
Prerequisite:None.
Catalog Date:August 1, 2026

This is the experimental courses description.

AI 300 Introduction to Artificial Intelligence and Machine Learning

Units:3
Hours:54 hours LEC
Prerequisite:None.
Transferable:CSU; UC
Catalog Date:August 1, 2026

This course introduces students to artificial intelligence (AI) and machine learning (ML) basics. It explores AI use cases and applications and explains AI concepts and terms like generative AI (GenAI), deep learning (DL), computer vision, and natural language processing (NLP). Students will also be exposed to various issues and concerns surrounding AI, such as ethics and bias. This course does not require programming. This course is not open to those who have completed CISD 300.

AI 305 Ethics and Artificial Intelligence

Units:3
Hours:54 hours LEC
Prerequisite:None.
Transferable:CSU; UC
Catalog Date:August 1, 2026

This introductory course on Artificial Intelligence (AI) ethics provides a comprehensive overview of ethical considerations in the domain of artificial intelligence. The course covers principles of AI ethics, strategies to foster fair and equitable AI systems, approaches to minimize biases, and methods to address key issues and establish user trust.

AI 310 Machine Learning

Units:3
Hours:54 hours LEC
Prerequisite:AI 300 with a grade of "C" or better
Transferable:CSU; UC
Catalog Date:August 1, 2026

This course introduces Machine Learning (ML) and Deep Learning (DL), focusing on their differences, mathematical foundations, and practical applications. Students will build classification, regression, and reinforcement learning models while exploring AI project structuring and emerging technologies. This course is not open to those who have completed CISD 307.

AI 311 Python for Applied AI and Visualization

Units:4
Hours:54 hours LEC; 54 hours LAB
Prerequisite:None.
Catalog Date:August 1, 2026

This course equips students with the foundational concepts and practice of Python programming, AI/ML tools and techniques, and visualization: Data, variables and structures, functions, AI datasets, arrays, lists, tuples, and objects; AI/ML algorithms and programming process; visualization and performance analysis for applications using current libraries/packages with NumPy, Pandas, Scikit-learn, TensorFlow, Keras, Matplotlib, and Seaborn.

AI 312 Natural Language Processing I

Units:3
Hours:54 hours LEC
Prerequisite:AI 300 with a grade of "C" or better
Transferable:CSU; UC
Catalog Date:August 1, 2026

This course introduces students to the basics of Natural Language Processing (NLP) and how to give the ability of a computer program to understand human language as it is spoken and written, referred to as natural language. It is a component of artificial intelligence (AI). This course is not open to those who have completed CISD 410.

AI 314 Computer Vision I

Units:3
Hours:54 hours LEC
Prerequisite:AI 300 with a grade of "C" or better
Transferable:CSU; UC
Catalog Date:August 1, 2026

This course introduces students to the basics of Computer Vision (CV) which is a subset of Artificial Intelligence that train computers to automatically process, extract and manipulate visual data from images and videos. This course is not open to those who have completed CISD 412.

AI 315 Deep Learning I

Units:3
Hours:54 hours LEC
Prerequisite:AI 300 with a grade of "C" or better
Catalog Date:August 1, 2026

This course provides students with the fundamental concepts of Deep Learning (DL) as a subset of Machine Learning (ML), including basic practice of DL and its applications, multi-layer neural network architectures in DL models, propagation algorithms, parameters, and collections of data, and DL tools/libraries/packages.

AI 316 Applied Generative Artificial Intelligence I

Units:3
Hours:54 hours LEC
Prerequisite:AI 300 with a grade of "C" or better
Catalog Date:August 1, 2026

This course introduces students to the fundamental concepts of Applied Generative Artificial Intelligence (GenAI) as part of AI technologies and application development. It explores basic practices of GenAI and its applications, large language models (LLMs), transformer architecture, retrieval-augmented generation (RAG), the world of graphics processing units (GPUs) and neural processing units (NPUs), and hands-on GenAI application development.

AI 400 Applied Generative Artificial Intelligence II

Units:3
Hours:54 hours LEC
Prerequisite:AI 316 with a grade of "C" or better
Catalog Date:August 1, 2026

This Advanced Generative Artificial Intelligence (GenAI) applications course will introduce Advanced GenAI applications in areas such as Healthcare and Autonomous Systems, forefront technologies and advanced techniques in testing and building combined GenAI and Retrieval-Augmented Generation (RAG) applications through complex and multi-language and data models, and applying advanced prompt engineering and concepts of federated learning (FL) in application development.

AI 402 Deep Learning II

Units:3
Hours:54 hours LEC
Prerequisite:AI 315 with a grade of "C" or better
Catalog Date:August 1, 2026

This Advanced Deep Learning (DL) course will provide forefront technologies and techniques for testing and building applications using complex and multi-layered neural networks (NNs), generative adversarial networks (GANs), variational autoencoders (VAEs), deep reinforcement learning (DRL), and other transformers and unsupervised models.

AI 499 Experimental Offering in Artificial Intelligence

Units:0.5 - 4
Prerequisite:None.
Catalog Date:August 1, 2026