Deep Dive into Large language Models (LLM) Training Logo

Deep Dive into Large language Models (LLM) Training

Live Online & Classroom Enterprise Training

This Course explores the architecture, training, and applications of LLMs, covering topics like transformers, fine-tuning, and real-world AI integration. It provides hands-on experience in building and optimizing LLM-based solutions for various industries.

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What is Deep Dive into Large language Models (LLM) Course about?

This course offers an in-depth exploration of Large Language Models (LLMs), such as Open AI's GPT, BERT, and others, that have revolutionized the field of Natural Language Processing (NLP). Participants will gain comprehensive insights into how these models are trained, fine-tuned, and deployed for various applications, such as chatbots, summarization, translation, and content generation. The course also delves into the ethical considerations, challenges, and best practices in working with LLMs.

What are the objectives of Deep Dive into Large language Models (LLM) Course ?

  • Understand the architecture and functioning of LLMs, including transformer models.
  • Fine-tune pre-trained LLMs for specific use cases.
  • Develop and deploy applications powered by LLMs, such as chatbots and recommendation systems.
  • Address challenges such as biases, interpretability, and performance optimization in LLMs.
  • Apply ethical principles and best practices when working with large-scale AI models.

Who is Deep Dive into Large language Models (LLM) Course for?

  • Data Scientists and Machine Learning Engineers aiming to specialize in NLP.
  •  AI Researchers exploring advanced capabilities of LLMs.
  •  Developers building AI-driven applications that require language understanding.
  •  Product Managers and Business Analysts interested in leveraging LLMs for innovative business solutions.
  •  Academics and Students studying the latest advancements in AI and NLP.

What are the prerequisites for Deep Dive into Large language Models (LLM) Course?

  • Basic understanding of Machine Learning and NLP concepts.
  • Familiarity with Python programming.
  • Knowledge of frameworks such as TensorFlow or PyTorch is recommended but not mandatory.

Available Training Modes

Live Online Training

2 Days

Self-Paced Training

16 Hours

Course Outline Expand All

Expand All

  • Evolution of NLP and the rise of LLMs
  • Overview of transformer architecture
  • Key LLMs: GPT, BERT, T5, and others
  • Pre-training vs. fine-tuning
  • Dataset preparation for LLMs
  • Fine-tuning techniques for domain-specific applications
  • Hands-on lab: Fine-tuning GPT for text summarization
  • Building conversational agents and chatbots
  • Text classification and sentiment analysis
  • Machine translation and content generation
  • Hands-on lab: Developing a chatbot with GPT
  • Mitigating biases and ethical considerations
  • Handling large-scale computational requirements
  • Techniques for improving model interpretability
  • Case studies: Ethical dilemmas in LLM applications
  • Scalable deployment of LLMs using cloud platforms
  • Optimizing LLM performance for latency and cost
  • Integrating LLMs with enterprise systems
  • Hands-on lab: Deploying a fine-tuned LLM on Azure/AWS
  • Emerging architectures and techniques
  • Role of LLMs in multimodal AI systems
  • Innovations in zero-shot and few-shot learning
  • Discussion: The evolving landscape of AI and LLMs

Who is the instructor for this training?

The trainer for this Deep Dive into Large language Models (LLM) Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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