This course provides practical experience in designing, customising and evaluating applications powered by large language models using LangChain. Through hands-on exercises, you'll explore techniques used to develop chatbots, summarisation tools and sentiment analysis solutions. By the end of the course, you'll understand how to structure, refine and assess LLM applications so you can contribute more effectively to AI initiatives within your organisation.
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Advanced Generative AI - Building LLM Applications
Develop advanced LLM engineering skills
Delivered over 22 hours, this course is aimed at professionals who want to understand how production-ready LLM applications are designed and refined. You'll explore workflow orchestration, prompt design, model adaptation and performance assessment using LangChain. Suitable for those expanding into AI engineering or applied AI roles, the course helps develop skills that can support the delivery, improvement and maintenance of LLM-based solutions.
Learning objectives
- Design LangChain workflows
- Apply prompt engineering techniques
- Create applications using LangChain components
- Fine-tune models for specific tasks
- Measure response quality and effectiveness
- Assess summarisation performance
- Explore chatbot development
- Analyse sentiment applications
Key facts
Certification
This is a skills and knowledge-based course with no formal accreditation.
Who it’s for
This course is designed for professionals looking to gain more from generative AI by building their own LLM applications.
Prerequisites
There are no formal prerequisites; however, a basic understanding of machine learning concepts may be beneficial.
Exam information
There is no exam associated with this course.
Optional extras
There are no optional extras with this course.
Pre-course
There are no mandatory pre-course activities for this course.
FAQs
These FAQs explain what the course covers, who it is suitable for and the skills you'll develop when learning to design and refine applications using large language models and LangChain.
What is this course about?
The course explores the techniques used to design, customise and assess applications developed with large language models. Using LangChain, you'll investigate areas such as prompt design, workflow orchestration, model refinement and practical use cases including conversational interfaces and text analysis.
What technologies will the course cover?
The course centres on LangChain and the development of LLM-based solutions. Topics include workflow orchestration, prompt design, model evaluation, fine-tuning techniques and the integration of supporting application components.
What practical skills will I gain?
You'll develop the ability to structure LangChain workflows, assess model responses, adapt models for defined use cases and design applications that combine prompts, memory and external integrations.
What can I use LLM application development skills for?
Large language models can support a wide range of business and technical applications, including chatbots, content generation, translation, summarisation and sentiment analysis. This course explores the techniques used to build and customise these types of solutions, helping you understand how LLMs can be applied to practical challenges and opportunities within modern organisations.
Why learn LangChain for LLM development?
LangChain provides tools for structuring interactions with large language models, managing context and connecting models with external systems. Understanding how these capabilities work together can help you develop more maintainable and scalable LLM applications.
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