Instructed by Barclay R. Brown, Ph.D, Assoc. Dir AI Research, Collins Aerospace
ü From 13–22 May 2025 (2 Weeks, 4 Lectures/Classes, 8 Total Hours)
ü Every Tuesday and Thursday from 1–3 p.m. Eastern Time (all sessions will be recorded and available for replay; course notes will be available for download)
ü Explore AI's Frontiers in Aviation and Aerospace!
ü All students will receive an AIAA Certificate of Completion at the end of the course.
OVERVIEW
This is the fourth in a series of AIAA Artificial Intelligence (AI) short courses focusing on Responsible AI. These courses are tailored to equip aerospace professionals with the essential knowledge, skills, and analytical abilities to tackle the challenges of responsibly designing and deploying AI-integrated systems. As AI becomes increasingly embedded in aerospace, it presents significant opportunities for efficiency, cost reduction, and safety enhancement. However, recognizing and mitigating the associated risks is essential to ensure the safety, reliability, and ethical integrity of these technologies.
Join our new course on Large Language Model (LLM) Application Development, focused on AI applicability in the aviation and aerospace industries. This course is tailored for beginners, requiring no prior knowledge of computer programming or AI, and provides a comprehensive journey through the essentials of AI and LLMs, leading up to specialized applications in high-impact industries.
- Industry-Specific Insights: Understand how AI and LLMs are revolutionizing aviation and aerospace, from enhancing safety to optimizing operations.
- Broader Application Knowledge: Expand your understanding of where and how AI technologies can be applied beyond traditional tech domains, preparing you for diverse developmental challenges.
This course promises an engaging introduction to AI's vast potentials, emphasizing practical applications and ethical considerations. Whether you're curious about AI, aiming to pivot your career towards technology, or interested in the specific impacts of AI on sectors like aviation and aerospace, this course offers the knowledge and tools to embark on that journey.
LEARNING OBJECTIVES
- Grasp the Basics: Understand the fundamental concepts of AI, machine learning, and LLMs.
- Tool Mastery: Get familiar with key tools and libraries essential for LLM application development.
- Hands-On Application: Learn to implement and customize applications using LLMs for various tasks.
- Ethical Insight: Gain insight into the ethical considerations in AI development, focusing on bias and fairness.
- Project Completion: Apply everything you've learned to workshop a real-world project, applying your new skills.
AUDIENCE
- Anyone curious about AI and large language models, especially:
- Individuals looking to understand the impact of LLMs in technology and society.
- Professionals and students aiming to get a head start in AI application development.
- Beginners without prior programming or AI knowledge.
COURSE FEES (Sign-In
To Register)
- AIAA Member Price: $495USD
- Non-Member Price: $695 USD
- AIAA Student Member Price: $295 USD
LEARNING TRACK: Responsible AI in Aerospace
- While courses can be taken on their own, students can bundle all four courses in the Responsible AI in Aerospace Learning Track with significant discounts.
- Students that attend all 4 courses will receive an additional AIAA Certificate of Completion.
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OUTLINE
- Introduction to LLMs (e.g., GPT, BERT) and their significance.
Module 2: Fundamentals of Working with LLMs
- Basics of LLM architecture, functioning, and the concept of pretraining and fine-tuning.
- A brief overview of key tools and libraries for LLM development.
Module 3: Developing Applications with LLMs
- Core applications: text generation, summarization, and basic chatbot implementation.
- An introduction to adapting LLMs for specific tasks with hands-on activities.
Module 4: Retrieval-Augmented Generation (RAG)
- Introduction to RAG and its importance for enhancing LLMs.
- Practical exercise: Building a RAG-enhanced application.
Module 5: AI in Aviation and Aerospace
- Overview of AI's impact on aviation and aerospace, including safety enhancements, predictive maintenance, and automated air traffic control.
- Case studies on AI-driven innovations in these industries.
- Discussion on the future of AI in enhancing operational efficiency and sustainability in aviation and aerospace.
Module 6: Deployment and Ethical Considerations
- Essentials of deploying LLM applications, focusing on scalability and performance.
- Ethical considerations in AI, with a focus on responsible use in sensitive sectors like aviation and aerospace.
Module 7: Project Workshop and Wrap-Up
- Project Workshop: Participants will choose a focus area inspired by previous modules, potentially incorporating RAG or AI applications in aviation and aerospace, to develop a project proposal or a basic model.
- Course
wrap-up: Summarizing key takeaways and discussing paths for further learning
and involvement in the AI community.
Dr. Barclay R. Brown is Associate Director for AI Research at Collins Aerospace, a division of RTX. He is the lead instructor for the RTX AI education program, and chair of the INCOSE AI Systems International Working Group. Dr. Brown has served as adjunct faculty at Worcester Poly Tech, the Quality Management Institute and the University of Central Florida. Dr. Brown holds a bachelor’s degree in electrical engineering, master’s degrees in psychology and business and a PhD in systems engineering. He is author of Engineering Intelligent Systems, published by Wiley, and is a certified Expert Systems Engineering Professional (ESEP), certified Systems Engineering Quality Manager, and former CIO of INCOSE.
Classroom
hours / CEUs: 8 classroom hours, 0.8 CEU/PDH
Course Delivery and Materials
- The course lectures will be delivered via Zoom. You can test your connection here: https://zoom.us/test
- All sessions will be available on-demand within 1-2 days of the lecture. Once available, you can stream the replay video anytime, 24/7. All slides will be available for download after each lecture.
- No part of these materials may be reproduced, distributed, or transmitted, unless for course participants. All rights reserved.
- Between lectures, the instructors will be available via email for technical questions and comments.
Cancellation Policy: A refund less a $50.00 cancellation fee will be assessed for all cancellations made in writing prior to 7 days before the start of the event. After that time, no refunds will be provided.
Contact: Please contact Lisa Le or Customer Service if you have questions about the course or group discounts (for 5+ participants).