TAKE
ALL
COURSES FOR £49
1 Year Access 
2 Students 
3 hours, 42 minutes 
LangChain in Action: Develop LLM-Powered Applications Overview
In the fast-paced world of AI, LangChain stands out as a powerful framework for building applications that fully utilise large language models (LLMs). This hands-on course, Lang Chain in Action: Develop LLM-Powered Applications, empowers you to master the skills and knowledge needed to unlock the full potential of Lang Chain. You’ll start by diving into the basics and quickly progress to advanced techniques. As you move through the course, you will explore a variety of topics, including memory management, OpenAI function calling, retrieval-augmented generation (RAG), and microservice architecture for LLM applications. By the end of this course, you will have the expertise to create sophisticated LLM-powered applications that can turn data into actionable insights.
Learning Outcomes
- Understand the foundational concepts of LangChain and its significance in LLM-powered applications.
- Develop and implement basic to advanced chains in LangChain for efficient data processing.
- Utilise callbacks in LangChain to enhance application performance and interactivity.
- Manage memory effectively within LangChain to optimise application efficiency.
- Implement OpenAI function calling within LangChain to integrate powerful language models.
- Apply Retrieval Augmented Generation (RAG) techniques to improve the accuracy and relevance of generated content.
- Develop and deploy agents within LangChain for automating complex tasks.
- Leverage the Indexing API to efficiently organise and retrieve information in LLM applications.
- Understand and implement LangSmith and LangChain Expression Language (LCEL) for advanced LLM application development.
- Design and deploy a microservice architecture tailored for LLM-powered applications.
Who Is This Course For
This Lang Chain course is ideal for developers, data scientists, and AI enthusiasts who already have a foundational understanding of machine learning. If you’re eager to dive into integrating large language models into your applications, this course will be your perfect guide. You’ll master the skills needed to develop cutting-edge AI-driven applications, fully leveraging the power of LangChain. Whether you’re working on solo projects, collaborating with a team, or looking to boost your professional skills, this course equips you with the essential tools and knowledge. With a strong focus on active learning and practical application, you’ll confidently navigate the complexities of building LLM-powered applications.
Eligibility Requirements
Participants should have a basic understanding of AI concepts and programming. Familiarity with Python is recommended, as the course involves practical coding exercises. No prior experience with LangChain is required, but a willingness to learn and experiment with large language models will be beneficial.
Entry Requirements
- Age Requirement: Applicants must be aged 16 or above, allowing both young learners and adults to engage in this educational pursuit.
- Academic Background: There are no specific educational prerequisites, opening the door to individuals from diverse academic histories.
- Language Proficiency: A good command of the English language is essential for comprehension and engagement with the course materials.
- Numeracy Skills: Basic numeracy skills are required to effectively understand and work with course-related information.
Why Choose Us
- Affordable, engaging & high-quality e-learning study materials;
- Tutorial videos/materials from the industry-leading experts;
- Study in a user-friendly, advanced online learning platform;
- Efficient exam systems for the assessment and instant result;
- The UK & internationally recognised accredited
- Access to course content on mobile, tablet or desktop from anywhere, anytime;
- The benefit of career advancement opportunities;
- 24/7 student support via email.
Career Path
Participants should have a solid grasp of machine learning concepts and basic programming skills. Familiarity with Python and frameworks such as TensorFlow or PyTorch will enhance your learning experience. While prior experience with LangChain is not necessary, a background in AI or software development will be beneficial for understanding the advanced topics covered in this course. By building on your existing knowledge, you’ll seamlessly transition into mastering LangChain and developing sophisticated LLM-powered applications.
Frequently Asked Questions
LangChain is a framework for developing applications that use large language models (LLMs). It provides components that can help developers connect language models with prompts, external data, tools, memory and application workflows.
LangChain can be used to develop LLM-powered applications such as conversational assistants, question-answering systems, document-based applications and workflows that combine language models with external tools or information sources.
LangChain can provide components for retrieving and processing information from external sources before passing relevant context to an LLM. This approach can help applications generate responses based on information beyond the model’s original training data.
Chains allow developers to connect multiple operations into a structured workflow, such as preparing a prompt, sending it to a language model and processing the resulting output. They are useful for building repeatable LLM application logic rather than relying on a single model call.
LangChain can be learned by developers who are new to LLM application development, provided they have a basic understanding of programming concepts. A practical course can help learners understand how LangChain components fit together when building applications powered by large language models.
TAKE
ALL
COURSES FOR £49
