Large Language Models

Master cutting-edge AI techniques—learn to build, evaluate, and optimize LLMs like BERT and ChatGPT, apply them to real-world challenges through hands-on projects, and gain the skills to lead responsible, innovative AI initiatives in your organization.

Johns Hopkins University Certificate of Completion

In person executive learning experience

Real-world relevant content and use cases

LIVE monthly seminars with JHU Faculty

The course is live. Click Register to start. Investment: $500

Advance your knowledge of today’s AI landscape

Earn a certificate of completion from JHU, a recognized leader in education and research. Earn 2 Continuing Education Units (CEUs) upon course completion.

The image is for illustrative purposes only. The actual certificate may be subject to change at the discretion of Johns Hopkins University

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Course description

Johns Hopkins Engineering Lifelong Learning’s online and asynchronous Large Language Models (LLMs) course offers a unique blend of technical insight and real-world application. This course equips you with the skills to prepare data, evaluate models, and optimize performance using advanced techniques like Retrieval-Augmented Generation (RAG) and prompt engineering.

Engage with Johns Hopkins faculty and AI experts as you explore the mechanics of BERT, ChatGPT, and T5, mastering the fundamentals of natural language processing, transformers, and attention models. Learn to assess and mitigate critical risks such as biases, security vulnerabilities, and governance challenges, ensuring responsible AI use.

Hands-on assignments and a capstone project connect theoretical knowledge with practical implementation, preparing you to lead AI-driven projects and initiatives. Enhance your technical expertise, drive innovation, and advance your career in the rapidly evolving field of AI and machine learning.

Who is the program for?

Data Scientists
Machine Learning Engineers
Product Managers
Knowledge Management Specialists
IT Consultants

Acquire essential knowledge in LLMs

Data Preparation
Model Evaluation
Risk Mitigation
Prompt Engineering
Governance Challenges

Built for Everyone

Dynamic Online Learning

Engage in dynamic, interactive learning from anywhere in this online, asynchronous course.

Dedicated course support

Johns Hopkins University faculty are readily accessible to address your questions in the course, ensuring a personalized learning experience.

Engaging materials

Content and use cases ensure it is current and relevant to today’s civil space exploration.

Hands-on activities

Hands-on activities that ensure you leave with actionable takeaways.

Faculty

Dr. Ian McCulloh leads AI Continuing and Executive Education at Johns Hopkins University, where he specializes in data science, network analysis, and artificial intelligence. He holds a PhD in Computer Science from Carnegie Mellong University.McCulloh’s professional experience includes leading the U.S. Army’s network science initiative and establishing Accenture’s U.S. Federal AI practice, where he grew a team of over 1,200 professionals. His work spans advanced data analysis, machine learning, and Python programming, with applications in healthcare, defense, and business. He is a published author in peer-reviewed journals and has taught courses in data science and AI, making him uniquely qualified to lead a course in Python programming. McCulloh’s teaching emphasizes practical applications, bridging technical expertise with real-world problem-solving.

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Large Language Models