Dear all,

Just a friendly reminder that registration is still open and the class starts on June 2, 2025. We’ll cover efficient prompt design, LLM app and agent building, and demonstrate vibe coding that turns prompts into runnable code. Course details are below; the web version is here<https://news.vt.edu/notices/univlib-AI-prompt-engineering.html>.

Prompt engineering has evolved from a niche specialty to a foundational skill for every professional, essential for interacting with everyday AI applications, building custom applications, and advancing cutting-edge research. Join Intro to Prompt Engineering, an online course offered by the Center for Digital Research & Scholarship, Virginia Tech University Libraries, and certified by Virginia Tech Continuing and Professional Education.

Dates: June 2 – July 14
Format: Fully online, self-paced, six-week program with weekly two-hour sessions.
This course dives into Generative AI (GenAI) and Prompt Engineering, providing essential skills and knowledge to excel in these advanced areas of artificial intelligence. With a balanced blend of theory and hands-on practices, you'll master core AI concepts, explore NLP fundamentals, and build tangible Large Language Model (LLM) applications that turn your ideas into reality.
Participants will receive a digital badge of completion from Virginia Tech Continuing and Professional Education upon successfully completing the course.
 Course Objectives:

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Establish a Foundation: Learn the history, key concepts, and evolution of AI, with a particular emphasis on generative AI models. Understand the basics of Natural Language Processing (NLP) and the significance of prompt engineering.
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Develop Skills: Build essential skills in prompt engineering techniques and design. Gain hands-on experience integrating prompt engineering with advanced AI models—including both open-source models (e.g., Llama 3) and proprietary models (e.g., GPT-4o)
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Apply Knowledge: Put theory into practice with dedicated modules on the practical implementation of AI solutions. Engage in hands-on coding exercises and assignments to develop LLM-powered chat-based applications, implement Retrieval-Augmented Generation (RAG) techniques, and build intelligent agents.

Agenda:

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Introduction to AI and Generative AI
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Foundations of Natural Language Processing (NLP) and Prompt Engineering
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Prompt Engineering Techniques and Design
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Integrating Prompt Engineering with Models
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Practical Implementation of Retrieval-Augmented Generation (RAG)
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Building and Implementing AI Agents

Instructor: Yinlin Chen, assistant professor and assistant director at the Center for Digital Research and Scholarship, Virginia Tech University Libraries, and affiliate faculty in Virginia Tech’s Department of Computer Science, has over 15 years of experience in software development and research, including 10 years specifically in AI and Machine Learning research, and about five years of teaching experience. His research interests include AI, Machine Learning, Cloud Computing, Natural Language Processing, and Information Retrieval.
Learn more on the Virginia Tech Continuing and Professional Education website and register<https://register.cpe.vt.edu/search/publicCourseSearchDetails.do?method=load&courseId=8811904> today.
Regards,
Yinlin

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Yinlin Chen, Ph.D.
Assistant Professor
Assistant Director, Center for Digital Research & Scholarship
Affiliate faculty, Department of Computer Science
Instructor, Department of Computer Science
Virginia Tech University Libraries
560 Drillfield Drive (0434)
Blacksburg, VA 24061
540-231-0271
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https://www.yinlinchen.com/