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Fine-tuning Language Models for Business Tasks

This course is part of Harnessing LLMs: Strategy, Fine-Tuning & Evaluation Specialization

Instructors: Soheil Haddadi, Reza Moradinezhad

Included with

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1 module

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

3 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Analyze key concepts of Large Language Models, Evolution of Language AI, and fine-tuning.
Identify and analyze how to use LLMs Fine-Tuning for business-specific tasks.
Apply LLM fine-tuning to create your own custom model.
Evaluate the future of LLMs for business use cases and stay updated with the latest trends in Language AI.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

1 assignment

Taught in English

91% of learners achieved a positive career outcome

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Harnessing LLMs: Strategy, Fine-Tuning & Evaluation Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There is 1 module in this course

This course demystifies the concept of "LLM fine-tuning" and its critical applications in the business world. In the context of rapidly evolving AI technologies, understanding how to fine-tune Large Language Models (LLMs) is essential for businesses to stay competitive. The course covers foundational concepts, the background of LLMs, current uses in various industries, and a glimpse into future possibilities. Through real-life examples, learners will see how fine-tuning LLMs can lead to more efficient, personalized, and innovative business solutions.

Main Outcome and Takeaways: 1. Review and apply different LLMs and tools to fine-tune a model for business-specific tasks for making better use of AI in your own business growth. 2. Comprehend LLM Fundamentals: Understand the basics of LLMs and the significance of fine-tuning. (Knowledge) 3. Analyze Business Applications: Evaluate how LLM fine-tuning is applied in different business scenarios. (Analysis) Develop Fine-Tuning Strategies: Create strategies for fine-tuning LLMs to meet specific business needs. (Application) Forecast Future Trends: Anticipate and plan for future developments in LLM technology in business contexts. (Evaluation)