This advanced training module offers a deep dive into Large Language Models (LLMs)—the technology powering modern AI applications like ChatGPT and other generative tools. Participants will gain a clear understanding of how LLMs work, including their architecture and training processes. The course explores real-world applications across sectors such as customer service, content generation, healthcare, legal, and more. It also addresses key challenges such as bias, data privacy, and interpretability. Additionally, learners will get hands-on exposure to popular tools and platforms for implementing LLMs, concluding with interactive demonstrations and practical use cases.

LLMs are transforming how businesses interact with data, automate processes, and engage customers. This course enables professionals to unlock the full potential of generative AI, empowering teams to streamline workflows, reduce costs, and innovate faster. Whether you’re aiming to implement LLMs in your organization or seeking to upskill in one of the fastest-growing tech domains, this module delivers the knowledge and practical skills to lead with confidence.

Duration : 1-Day – Offered Virtually or Face-to-Face

Language : French or English

The training program includes the following topics:

  • 1. Introduction to LLMs

    This section provides a foundational overview of Large Language Models—what they are, how they differ from traditional AI models, and their role in natural language processing. You’ll learn about key milestones in the development of LLMs and understand why they’ve become central to modern AI.

  • 2. Language Model Architecture

    Dive into the underlying architecture of LLMs, including transformers, attention mechanisms, and tokenization. This part explains how these models process and generate language, enabling high-performance capabilities like translation, summarization, and question answering.

  • 3. Training LLMs

    Explore the data-driven process of training LLMs, including supervised learning, pretraining vs. fine-tuning, and the immense computational resources required. You’ll also examine training objectives like next-word prediction and masked language modeling.

  • 4. Applications of LLMs

    Discover the wide-ranging applications of LLMs across industries—from customer service chatbots and code generation to medical research and content creation. Real-world examples illustrate how businesses leverage LLMs to drive innovation and efficiency.

  • 5. Challenges and Issues with LLMs

    Learn about the technical, ethical, and societal challenges posed by LLMs, such as hallucinations, bias, misinformation, data privacy, and environmental impact. This section encourages critical thinking around responsible AI deployment.

  • 6. Introduction to Tools and Platforms for Using LLMs

    Get introduced to leading platforms and tools that enable the use and customization of LLMs, including OpenAI, Hugging Face, LangChain, and cloud-based APIs. Learn how developers and organizations can easily integrate these tools into their workflows.

  • 7. Advanced Demonstration and Practical Use Cases

    Experience hands-on demonstrations showcasing how LLMs solve complex tasks in real-time. From building a chatbot to automating document analysis, this section brings theoretical knowledge into practical application with live examples and case studies.