AI agents are quickly becoming one of the most powerful applications of large language models. This two-day course provides the knowledge and hands-on skills you need to design, build and deploy intelligent agents that can reason, interact with data sources and deliver meaningful insights.
You will begin by understanding what AI agents are and how they can be applied in real-world scenarios. From there, you will explore transformer architectures, advanced prompting methods and the LangChain framework. Practical exercises throughout the course give you the opportunity to build working agents and link them into pipelines that can handle multi-step tasks.
By the end of the course, you will have designed and implemented your own agents and pipelines, giving you the confidence to apply these techniques to real business challenges.
Target Audience:
This course is aimed at software developers, data scientists and AI/ML engineers who want to advance their skills in modern AI development. It is ideal for professionals who have experience with machine learning and natural language processing and are ready to explore the next step: building intelligent, production-ready AI systems.
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7 lesson covers:
Introduction and Agent Demo
Discover what AI agents are and why they are useful. See a live demonstration of a multi-step agent that collects data, analyses it and generates a clear summary, giving a preview of the concepts covered in the course.
Transformer Models Deep Dive
Learn how transformer models such as GPT and BERT work. Explore the mechanics of attention, encoders and decoders, and see how transformers are trained. You will gain hands-on experience with Hugging Face to explore pre-trained models.
Prompting Techniques
Master the fundamentals of zero-shot, one-shot and few-shot prompting, along with advanced methods such as chain-of-thought and ReAct prompting. You will practise designing prompts that enable models to perform complex, multi-step reasoning.
LangChain Refresher
Review the core features of LangChain and its role in building agents. Learn how to use prompts, chains, tools and agents effectively. You will also be introduced to Langflow, which allows for visual development of LangChain applications.
Developing AI Agents
Understand the components that make up an agent, including prompts, tools and memory. Learn how to define goals, integrate APIs and design prompts that guide agent behaviour. You will build a news summarisation agent as a practical exercise.
Agent Pipelines
Explore how multiple agents can be linked together to solve complex tasks. Learn best practices for inter-agent communication, error handling and scalability. In the practical session, you will create a pipeline that generates financial reports by combining data collection, analysis and summarisation agents.
Putting It All Together
Bring together everything you have learned with a live coding demo and collaborative exercises. You will design potential agent use cases for your own organisation, present your ideas, and receive feedback to help you take the next steps in applying agents at scale.
