This course offers a theoretical introduction to Large Language Models, focusing on how they are built, trained, and used in real-world applications.

You’ll learn the basics of language modeling, the role of transformer architecture, and key techniques like pre-training, fine-tuning, and transfer learning. 

Led by Andreea Turcu, this course also includes hands-on work with LLM DataStudio and covers how to evaluate and improve model performance.

 

 

What you'll learn

  • Foundations of Language Models
    Understand what language models are, how they work, and their role in natural language processing.
  • Neural Networks, Deep Learning, and Transformer Architecture
    Learn the core concepts behind modern LLMs, including how transformers power these models.
  • Pre-training, Fine-tuning, and Performance Evaluation
    Gain practical skills in training, adapting, and benchmarking large language models.
  • Real-World Applications and Use Cases
    Explore how LLMs are used across industries, from text generation to advanced NLP solutions.

Course access

 headshot

Andreea Turcu, Head of Global Training

Andreea is a data scientist with over 7 years of experience in demystifying AI and Data Science concepts for anyone keen on working in this exciting field using cutting-edge technology. Having obtained a Master’s Degree in Quantitative Economics and Econometrics from Lumière Lyon 2 University, she enjoys integrating machine learning principles with real-world applications. Andreea’s passion lies in developing engaging training programs and ensuring an optimal customer education journey. As she frequently likes to remark, “AI is essentially Economics turbocharged by data, with a sprinkle of innovation.”

You can view her LinkedIn profile HERE.