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Practical AI for Cybersecurity Bootcamp

Build practical AI skills in this immersive bootcamp designed for undergraduate ¼ø»Æʦapp. Learn how to build and secure large language models (LLMs), master prompt engineering, and create AI agents using tools such as OpenAI, Hugging Face, and LangChain. Participants will gain hands-on experience with techniques used across today’s AI industry.

Monday, August 17 - Friday, August 21, 2026

9:00 A.M. - 11:00 A.M.

Please note that each class will be recorded. The recordings will be available online, allowing participants to access them if they miss a class or want to review any session.

Bootcamp Overview

  • Length: One week | Monday–Friday | 2 hours per day
  • Cost: FREE for ¼ø»Æʦapp Students, Faculty, and Staff
  • Time: 9:00 A.M. - 11:00 A.M.
  • Location: Engineering East (EE-96), Room 207
  • Instructor: Charles Givre
  • Email: cgivre@fau.eduÌý

About the Instructor

, CISSP, is an adjunct professor at ¼ø»Æʦapp and a cybersecurity and data science professional with more than 20 years of industry experience. He holds a master’s degree in Middle Eastern Studies from Brandeis University and bachelor’s degrees in Computer Science and Music from the University of Arizona.

Givre began his career in the intelligence community as a counterterrorism analyst at the Central Intelligence Agency and later worked at Booz Allen Hamilton and the National Security Agency. He has led technical teams developing AI-driven solutions for major international banks and is a frequent instructor at industry conferences, including Black Hat.

Tools and Resources

  • Sessions will include lectures, demonstrations, group discussions and opportunities for questions.
  • Slides and supporting materials will be made available to participants.
  • Students should have access to the internet and a computer capable of using the required AI tools and platforms.

Bootcamp Schedule

The bootcamp includes five two-hour modules combining instruction, demonstrations, hands-on activities and discussion.

Module 1: Introduction to AI and Machine Learning

  • Intro to Artificial Intelligence & Machine Learning
  • Overview of providers: OpenAI, Meta, HuggingFace

Module 2: LLMs

  • Embedding and Tokenization
  • Fine Tuning
  • Retrieval Augmented Generation (RAG)

Module 3: Prompt Engineering

  • Basic Prompting
  • Few Shot Learning
  • Chain of Thought, LangChain

Module 4: Red Teaming AI

  • AI Security
  • Prompt Injection attacks

Module 5: Agents

  • Building AI Agents

NSF logo

Supported by the NSF Scholarship for Service. Learn more at sfs.fau.edu.