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Large Language Models Course

Large Language Models Course
flexible workload of 4 to 360h
valid certificate in your country

What will I learn?

Gain hands-on expertise in large language models through this intensive programme. You will cover data ingestion, preprocessing, and basic NLP classification, advancing to LLM-powered routing and summarisation using effective prompt strategies. Develop repeatable experiments, thorough documentation, and CI pipelines, culminating in a practical guide for secure, monitored, and regulation-compliant production rollouts ensuring dependable performance.

Elevify advantages

Develop skills

  • Design LLM classification systems to create strong prompt-driven ticket routing solutions quickly.
  • Prepare data for LLMs by efficiently cleaning, anonymising, and versioning ticket datasets.
  • Evaluate and monitor LLMs to measure accuracy, detect drift, control costs, and ensure safety.
  • Develop summarisation pipelines for generating brief, verifiable ticket summaries at large scale.
  • Manage production LLM operations including deployment, governance, and compliant pipeline documentation.

Suggested summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

Your classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... I appreciate everything you do, I've already recommended you to others...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can switch chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the supplementary videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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