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Submitter's Information
John Skellenger
Dean of Career Education
North/Far North
Folsom Lake College
CTE Dean
John Skellenger
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Program Details
Deep Learning
New Program
Other Information Technology (079900)
08/27/26
The certificate of achievement in Deep Learning (DL) provides students with foundational and advanced skills necessary for careers in Deep Learning engineering and development. It emphasizes analytical, methodological, and technical training in DL technologies, preparing students for further specialization in Generative AI, Natural Language Processing (NLP), Computer Vision (CV), autonomous systems, and healthcare applications.
20 completers
Program Proposal Attributes
- Certificate of Achievement: 16 or greater semester (or 24 or greater quarter) units (C)
Folsom Lake College is committed to preparing students for a rapidly evolving workforce by providing rigorous academic pathways and industry-aligned career education programs. In alignment with the mission of the California Community College system, the college develops programs that support completion, transfer, economic mobility, and workforce advancement in high-demand and emerging technology fields.
Deep Learning (DL) is the evolutionary core of machine learning (ML) and neural networks (NNs). It has seen continuous development due to advanced coding techniques, mathematical developments, and computing capabilities. It is at the forefront of technological advancements in artificial intelligence (AI). Major industries, including healthcare, finance, education, automotive, and entertainment, are increasingly relying on deep learning techniques for applications such as image recognition, natural language processing, autonomous systems, and predictive analytics. There is a shortage of skilled professionals in deep learning as many organizations struggle to find talent with the necessary skills, particularly in specialized areas such as neural networks, model optimization, and large-scale data processing. This gap represents a unique opportunity for the College to help bridge some of the skills divide and meet market demand by providing high-quality training and certifications.
Upon completion of the Deep Learning Program, the student will be able to: explain how artificial intelligence and machine learning is useful in business or career.
Analyze and apply advanced Deep Learning techniques.
Design and implement DL models in autonomous systems.
Develop different systems utilizing DL methodologies.
This certificate prepares students for continued study in artificial intelligence and related transfer pathways, as well as entry-level or support roles in areas such as AI development, data analysis, chatbot development, language data processing, and AI-assisted communication systems. It also supports professionals seeking to enhance their technical skills in language-based AI applications across industries.
Course Units and Hours
16
n/a
n/a
Course Report
This certificate prepares students for continued study in artificial intelligence and related transfer pathways, as well as entry-level or support roles in areas such as AI development, data analysis, chatbot development, language data processing, and AI-assisted communication systems. It also supports professionals seeking to enhance their technical skills in language-based AI applications across industries.
Students are required to complete 16 units to earn the certificate.
| Course | Title | Units | Year/Semester (Y1 or S1) |
|---|---|---|---|
| AI 300 | Introduction to Artificial Intelligence and Machine Learning | 3 | Y1, S1 |
| AI 311 | Python for Applied AI and Visualization | 4 | Y1, S1 |
| AI 305 | Ethics and AI | 3 | Y1, S2 |
| AI 315 | Deep Learning I | 3 | Y1, S2 |
| AI 402 | Deep Learning II | 3 | Y2, S1 |
Supporting Documents
North/Far North Regional Questions
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Submission Details
02/17/26 - 04:49 PM
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Return to Drafts
Please list the reason(s) for returning "Deep Learning". to John Skellenger's drafts. This message will be sent to skellej@flc.losrios.edu
Comments, Documents, Voting
Comments
All Comments
Shari Dempsey Super User · 03/11/26
Program approved for recommendation by the NFN Voting members on 3/6/26.