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⇱ Foundations and Enterprise Applications of LLM | Coursera

Foundations and Enterprise Applications of LLM

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Foundations and Enterprise Applications of LLM

This course is part of LLMs in Enterprise Specialization

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand the key concepts and evolution of LLMs in enterprise applications.

  • Learn how to apply LLMs in various industries, such as healthcare and education.

  • Explore advanced fine-tuning techniques for deploying LLMs effectively in business environments.

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Recently updated!

April 2026

Assessments

3 assignments

Taught in English

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This course is part of the LLMs in Enterprise Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

In this course, you'll dive into large language models (LLMs) and explore their significant role in transforming enterprise applications. You’ll learn how LLMs are revolutionizing industries like healthcare and education, enhancing user interfaces, and driving innovation in business workflows.

Through a combination of theoretical knowledge and practical insights, you'll gain the tools to identify LLM deployment opportunities within your organization and understand how to integrate them for business advantage. The course provides real-world examples and expert guidance to give you a comprehensive view of LLMs' potential in enterprise environments. What sets this course apart is its blend of foundational principles with real-world use cases, ensuring you not only understand the theory but can apply it to solve practical problems. This course is perfect for professionals working in fields such as AI, machine learning, or enterprise software development, looking to expand their knowledge of LLMs. Some prior experience in machine learning or AI concepts will be helpful. This course is part one of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization.

This module explores the development and impact of large language models (LLMs), tracing their evolution from rule-based systems to advanced AI capable of natural conversation. Learners will examine the training processes behind models like GPT, clarify common misconceptions, and consider future directions in objective-driven AI. By the end, you'll gain foundational knowledge of how LLMs are built, refined, and applied.

What's included

1 video8 readings1 assignment

1 video•Total 1 minute
  • Overview•1 minute
8 readings•Total 42 minutes
  • Introduction•4 minutes
  • Evolution over time•4 minutes
  • LLMs and Transforming User Interfaces into Natural Conversations•6 minutes
  • GPT Assistant Training Recipe•5 minutes
  • Building Base Model Recap•6 minutes
  • Supervised Fine-Tuning Stage•6 minutes
  • Decoding the Realities and Myths of LLMs•6 minutes
  • Objective-Driven AI•5 minutes
1 assignment•Total 16 minutes
  • Foundations of Large Language Models•16 minutes

This module explores how large language models (LLMs) are transforming key enterprise sectors such as healthcare and education, while addressing the technical and operational challenges of deploying these models at scale. Learners will examine strategies for improving model efficiency, reliability, and return on investment, as well as best practices for integrating LLMs into business workflows.

What's included

1 video8 readings1 assignment

1 video•Total 1 minute
  • Overview•1 minute
8 readings•Total 44 minutes
  • Introduction•4 minutes
  • Healthcare•8 minutes
  • Education and Training•4 minutes
  • Challenges in Scaling and Deploying LLMs•6 minutes
  • Model Pruning•6 minutes
  • Model Reliability•6 minutes
  • ROI Considerations•6 minutes
  • LLM Design Patterns•4 minutes
1 assignment•Total 16 minutes
  • Enterprise Applications of Large Language Models•16 minutes

This module explores advanced methods for fine-tuning large language models, including dataset curation, prompt engineering, and integration strategies for business applications. Learners will gain hands-on experience with techniques such as K-shot prompting, LoRA configuration, and Retrieval-Augmented Generation (RAG) to optimize LLM performance for specific organizational needs.

What's included

1 video6 readings1 assignment

1 video•Total 1 minute
  • Overview•1 minute
6 readings•Total 36 minutes
  • Introduction•6 minutes
  • Dataset Collection•4 minutes
  • Approaches to Integration in Business Processes•6 minutes
  • Providing K-Shot Examples•6 minutes
  • Model Building•6 minutes
  • Implementing RAG•8 minutes
1 assignment•Total 16 minutes
  • Mastering Advanced LLM Fine-Tuning and Integration•16 minutes

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Frequently asked questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

This course is currently available only to learners who have paid or received financial aid, when available.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,