This is by far the best course out there to delve into LLMs. The course content is very in depth and there's a lot that is covered about fine-tuning LLM models and i appreciate the practical project about the sentiment analysis model because its very useful for me as a social analytics student. Overall, i would definitely revisit this content again and recommend it to others.
Fine-Tuning for LLMs: from Beginner to Advanced
With Axel Sirota
Liked by 475 users
Duration: 3h 25m
Skill level: Advanced
Released: 9/3/2024
Course details
This course capitalizes on the latest advancements in Large Language Models (LLMs) like FLAN-T5, enabling professionals to harness these tools effectively in the rapidly-evolving AI landscape. Instructor Axel Sirota helps you establish a strong foundation in the basics of LLMs, exploring their architecture, evolution, and role in the current AI landscape. Delve into prompt engineering and learn how to craft effective prompts that guide LLM outputs for specific tasks. Then deep dive into transfer learning and PEFT fine-tuning using LoRA and find out how to adapt and optimize LLMs for varied NLP tasks. Each course section comprises live-action clips, slides, and demos, as well as real-world challenges covering prompt engineering, transfer learning, and fine-tuning techniques to enhance FLAN-T5's capabilities. Plus, you’ll complete a final project focused on building an NLP solution encompassing sentiment analysis, text summarization, and question answering.
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
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Showcase on your LinkedIn profile under “Licenses and Certificate” section
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Meet the instructor
Learner reviews
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Nazir Harris N.
Nazir Harris N.
Business Analytics Undergraduate at UNSW | Data-Driven | Avid Python/R User | Aspiring Data Professional
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Asif Tandel
Asif Tandel
Data Scientist & GenAI Engineer | Python | Data Science | Machine Learning | Generative AI | Artificial Intelligence | RAG | AWS | LLM | Predictive…
Contents
What’s included
- Practice while you learn 1 exercise file
- Learn on the go Access on tablet and phone
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