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LLMs in Practice training course

Master modern transformer-based language models and AI agent design with this hands-on course. Learn to apply advanced prompting, build Retrieval-Augmented Generation systems, and optimize LLM deployments.

JBI training course London UK

"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. " Brian Leek, Data Analyst, May 2022

Public Courses

10/03/25 - 3 days
£2500 +VAT
21/04/25 - 3 days
£2500 +VAT
02/06/25 - 3 days
£2500 +VAT

Customised Courses

* Train a team
* Tailor content
* Flex dates
From £1200 / day
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JBI training course London UK

  • Understand the architecture and mechanisms of modern transformer-based language models
  • Design and implement AI agents using industry-standard frameworks
  •  Apply advanced prompting techniques for improved model performance
  • Implement Retrieval-Augmented Generation (RAG) systems with vector databases
  • Optimise LLM deployments for enterprise environments
  • Navigate the ethical and regulatory landscape of AI implementation

Workshop Format:

Each module follows a consistent pattern:

  • Core concept introduction and theory
  • Hands-on lab work
  • Review, troubleshooting, and best practices discussion

Module 1: Foundations of Modern LLMs

Theory Component:

  • Quick overview of Transformer Neural Network architecture
  • Key concepts in self-attention mechanisms

Practical Labs:

  • Implementing a basic attention mechanism from scratch
  • Visualizing attention patterns in practice
  • Analyzing the impact of different attention heads
  • Building a mini-transformer for practical understanding

Module 2: AI Agents and Framework Implementation

Theory Component:

  • Introduction to AI agents and their components
  • Overview of LangChain framework architecture

Practical Labs:

  • Setting up a development environment for AI agents
  • Building a basic agent with LangChain
  • Implementing custom tools and capabilities
  • Testing and debugging agent behaviors

Module 3: Advanced Agent Development

Theory Component:

  • Patterns for complex agent behaviors
  • Best practices for prompt engineering

Practical Labs:

  • Building an agent for data analysis
  • Implementing Chain-of-Thought reasoning
  • Creating custom tools for domain-specific tasks
  • Validation and testing

Module 4: Retrieval-Augmented Generation (RAG)

Theory Component:

  • Vector database concepts and selection criteria
  • Embedding strategies overview

Practical Labs:

  • Setting up a vector database
  • Building a document processing pipeline
  • Implementing efficient retrieval mechanisms
  • Optimizing search quality and performance

Module 5: Model Fine-tuning and Adaptation

Theory Component:

  • Understanding fine-tuning approaches
  • Overview of evaluation metrics

Practical Labs:

  • Preparing datasets for fine-tuning
  • Implementing LoRA fine-tuning
  • Evaluating model performance
  • Deploying fine-tuned models

Module 6: Advanced Optimisation Techniques

Theory Component:

  • Introduction to quantisation and optimization approaches
  • Overview of deployment considerations

Practical Labs:

  • Implementing QLoRA optimization
  • Testing different quantisation strategies
  • Benchmarking performance improvements
  • Optimizing for specific hardware configurations

Module 7: Ethical Implementation and Compliance

Theory Component:

  • Key regulatory requirements in the US and UK

Ethical considerations in AI implementation

JBI training course London UK

This course is designed for technical professionals in data analytics, particularly those working in forensic data analysis and large-scale data processing environments. It's ideal for team members who have strong foundations in Python programming and machine learning concepts, looking to incorporate LLM technologies into their existing data processing pipelines.

Prerequisites

  • Strong proficiency in Python programming
  • Experience with data processing frameworks (pandas, Hadoop, Spark)
  • Understanding of basic machine learning concepts
  • Familiarity with SQL and database concepts
  • Experience in handling large-scale data transformations

 


5 star

4.8 out of 5 average

"Our tailored course provided a well rounded introduction and also covered some intermediate level topics that we needed to know. " Brian Leek, Data Analyst, May 2022



“JBI  did a great job of customizing their syllabus to suit our business  needs and also bringing our team up to speed on the current best practices. ” Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022

 

 

JBI training course London UK

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The integration of Large Language Models (LLMs) into enterprise data workflows represents one of the most significant shifts in data analytics and processing capabilities of the past decade. For teams working in data analytics and large-scale data processing, LLMs offer unprecedented capabilities in pattern recognition, data interpretation, and automated analysis. However, moving from theoretical understanding to practical implementation presents unique challenges, particularly in environments where accuracy and reliability are paramount.

This hands-on workshop bridges the gap between LLM theory and practical implementation. Rather than focusing solely on theoretical concepts, we take a learn-by-doing approach, where participants spend approximately 70% of their time working on practical exercises and real-world implementations. Each module combines essential theoretical foundations with extensive hands-on labs, ensuring participants gain practical experience they can immediately apply in their own environments.

While a three-day workshop cannot cover every aspect of this rapidly evolving field, it provides the crucial foundations and practical experience needed to begin implementing LLM solutions effectively. The workshop is designed as a starting point, with the understanding that participants will likely want to explore specific aspects in greater depth through future specialised workshops.


This intensive, hands-on workshop is designed as a foundation for working with LLMs in practice. Participants are encouraged to view this as the beginning of their journey rather than its conclusion. Future specialized workshops will be available for deeper dives into specific aspects of LLM implementation, allowing teams to build on this foundation with more advanced techniques and specific use cases.

The field of LLMs continues to evolve rapidly, and this workshop provides both the practical skills and conceptual framework needed to adapt to new developments while maintaining robust and effective implementations.

Will there be practical exercises and hands-on training sessions?

Yes, the course includes practical exercises and hands-on training sessions aimed at reinforcing your understanding of LLMs and data analysis techniques. You will have the opportunity to apply theoretical concepts in real-world scenarios, allowing for a deeper immersion into the subject matter.

How will this course benefit my career in data analysis?

By mastering LLMs and advanced data analysis techniques, you will significantly enhance your skill set and marketability in the field of data analysis. The knowledge and expertise gained from this course will open up new opportunities for career advancement and enable you to tackle complex data analysis challenges with confidence and proficiency.

CONTACT
+44 (0)20 8446 7555

[email protected]

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