Chat GPT & LLMs: An Implementation Guide for Leaders

Learn how large language models work, their risks and mitigations and the set of frameworks for driving LLM strategy and implementation in practical terms.

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About This AI Online Course

This online course, created by FedLearn content partner, aiLeaders, provides leaders in the public and private sectors a set of frameworks for planning the implementation of large language models—for instance, how risks vary across the different tasks LLMs can perform. 

In the final lesson, we will delve into the five activities and 17 tasks you must consider to implement an LLM. 

In sum, this course provides what you, as a leader in your organization, needs to think through LLM implementations, as well as an enterprise strategy for LLMs.

Benefits of this course:

  • Drive LLM Implementation with knowledge of capabilities, limitations and risks versus being driven by hype, fear or hope that something will work
  • Become thoroughly literate in what happens “under the hood” in these models, equipped with a sufficiently technical—yet accessible to every leader—understanding
  • Evaluate candidate projects from an understanding of the many technology choices available against the desired work role you need to perform
  • Select which LLM projects to fund based on a clear understanding of the total work and, therefore, costs associated with implementation
  • Develop project plans from the three roles and four functions LLMs perform, how risks vary, which of five implementation paths is best and five activities and 17 tasks
  • Create an enterprise LLM strategy based on understanding of the variety and complexity presented by LLM tech instead of “throwing stuff at the wall”
  • Put learning into practice by using the reflection exercise to apply course content to your organization’s LLM strategy
  • Decide with an eye to the future based on an understanding of the major factors evolving in this dynamic tech space

What You Will Learn

  • Summarize the types of work LLMs perform
  • Explain three major factors affecting further development of LLM technology
  • Summarize how LLMs work
  • Analyze your options for implementing LLMs
  • Assess the challenges and risks of implementing LLMs to your option(s)
  • Create the case that secures stakeholder support of an LLM project
  • Create a plan of the implementation activities and key tasks required for your project

Your Instructors

Frank Strickland, owner and founder of aiLeaders, began his 22 years of Federal service as a U.S. Marine and finished as a member of the Central Intelligence Senior Intelligence Service, where he helped lead several innovations, including transitioning to production the nation’s first long endurance unmanned aerial system and delivering intelligence to the tactical edge using narrow and wide-band technologies and agile prototyping of big data analytics. Mr. Strickland was awarded the National Intelligence Medal of Achievement in recognition of these accomplishments by the Director of Central Intelligence. 

In the private sector, Mr. Strickland co-founded Edge Consulting and helped lead the company’s growth—resulting in an acquisition by IBM. As a partner in IBM and subsequently Deloitte, he led large practices providing artificial intelligence and analytics solutions and services to national security clients, including innovations in massive-scale property graphs and agent-based simulation. 

Chris Whitlock, owner and founder of aiLeaders, began Federal service as a U.S. Army infantry officer and then was a CIA military analyst before starting a career in industry. He spent the majority of his 40-year career providing advanced analytics, AI and management consulting services primarily to national security clients in the U.S. Department of Defense, Intelligence Community and U.S. Department of State. Mr. Whitlock helped pioneer the rapid prototyping and integration of advanced algorithms with software applications starting in the early 1990s. 

In the past 10 years, Mr. Whitlock’s work has emphasized machine learning and AI applications. He led a large-market offering in Deloitte Consulting focused on mission analytics and AI, in addition to leading large programs for cabinet-level departments. Mr. Whitlock co-founded Edge Consulting, personally leading the development of algorithmic approaches to quantify the value of intelligence. After an acquisition by IBM, he served as a partner in the company. 

Who Should Take This Course

This course is designed for executives, program managers, project managers and staff officers who need a practical understanding of how to leverage LLM technology. The course does not involve math or programming. However, you will learn a thorough understanding of how LLMs work and how the models’ mechanics are relevant to strengths, weaknesses and risks.



Course Certificate

To achieve a course certificate of completion you must complete all modules in their entirety, including each corresponding knowledge check. The reflection exercise is strongly encouraged as an engaged and applied learning activity, but is not required to receive the certificate. 

Course Format

Self-paced, online training course

Course Pricing

Individual courses are $297 (per person).

The course is not included in seat licenses for the FedLearn AI and data science course catalog.

If you are interested in learning about special team rates for Federal government and government contractor organizations, email [email protected].

Continuing Education Unit Credits

This course provides 3 CEUs.