LangChain Developer
Profile Code: AL-AI-04
- ₹20 LPA (Median Salary)
- Lecture Duration 2hrs
- Course Duration 16 Weeks
Skills You Learn: LangChain Framework & LLM Orchestration | Prompt Engineering & Chain Design | Retrieval-Augmented Generation (RAG) | Vector Databases & Embeddings | AI Agent Development | Python & API Integration | Generative AI Application Development | MLOps & AI Deployment
Overview Video
About This Course
LangChain Developers design, build, and deploy intelligent AI applications by integrating large language models (LLMs) with external data sources, APIs, and business workflows using the LangChain framework. They create scalable AI solutions such as chatbots, AI agents, knowledge assistants, and Retrieval-Augmented Generation (RAG) applications that solve real-world business problems. This course prepares learners for a career as a LangChain Developer through hands-on projects, industry workflows, collaborative learning, and real-world case studies aligned with current hiring expectations in India. Learners gain expertise in Python, LangChain, prompt engineering, RAG, vector databases, embeddings, AI agents, API integration, workflow orchestration, and responsible AI practices. The curriculum includes practical experience with leading AI platforms and cloud technologies. Through live projects and capstone assignments, participants develop programming, problem-solving, and AI application development skills, preparing them for LangChain Developer, AI Engineer, LLM Engineer, and AI Solutions Developer roles across diverse industries.
Course Content
7 modules · 16 weeks · 2hrs/dayLangChain Course
The LangChain Course Basic to Advance provides learners with a strong foundation in building AI-powered applications using the LangChain framework. Participants learn prompt templates, chains, models, output parsers, document loaders, text splitters, tools, agents, memory, and workflow orchestration. Through hands-on projects and real-world business scenarios, the course develops practical skills to create intelligent applications that integrate large language models with external data sources, enabling scalable AI solutions for automation, knowledge management, and enterprise productivity.
Python Course
The Python Course Basic to Advance equips learners with advanced programming skills required for developing LangChain-based AI applications. Participants explore object-oriented programming, asynchronous programming, API integration, modular architecture, exception handling, file processing, performance optimization, and reusable code development. Through practical implementation projects, the course prepares learners to build scalable, secure, and maintainable AI applications for production environments
OpenAI API Course
The OpenAI API Course Basic to Advance focuses on integrating OpenAI language models into LangChain applications. Learners master API authentication, chat completions, embeddings, function calling, structured outputs, streaming responses, prompt optimization, rate limits, error handling, and application integration. The course emphasizes real-world implementation through enterprise AI projects and intelligent automation solutions.
Pinecone Course
The Pinecone Course Basic to Advance provides comprehensive training in vector database management for Retrieval-Augmented Generation (RAG) applications. Participants learn vector indexing, embeddings storage, similarity search, namespaces, metadata filtering, scalability, performance optimization, security, and integration with LangChain workflows. Through hands-on projects, learners build efficient semantic search and knowledge retrieval systems for AI applications.
ChromaDB Course
The ChromaDB Course Basic to Advance equips learners with the skills to build lightweight vector database solutions for AI-powered applications. Participants explore document collections, embeddings, metadata management, similarity search, persistence, indexing, retrieval optimization, integration with LangChain, and local deployment. The course focuses on creating fast and efficient retrieval systems through practical implementation and business use cases.
FAISS Course
The FAISS Course Basic to Advance develops expertise in high-performance vector similarity search using Facebook AI Similarity Search (FAISS). Learners master vector indexing, nearest neighbor search, clustering, embedding optimization, indexing strategies, large-scale search, performance tuning, and integration with LangChain pipelines. The course prepares participants to build scalable semantic search solutions for enterprise AI applications.
Streamlit Course
The Streamlit Course Basic to Advance teaches learners how to build interactive web applications for LangChain-powered AI solutions. Participants learn interface design, widgets, session state, file uploads, data visualization, API integration, chatbot development, deployment, performance optimization, and user experience design. Through hands-on projects, the course enables learners to create professional, user-friendly AI applications for business, research, and enterprise environments.
Key Responsibilities
- Design and develop AI applications using LangChain and large language models
- Build and orchestrate LLM pipelines, chains, and agent-based workflows for intelligent automation
- Implement retrieval-augmented generation (RAG) systems by integrating vector databases and external data sources
- Develop and optimize prompt templates, memory management, and tool integrations
- Collaborate with AI engineers, data scientists, and product teams to deploy scalable generative AI solutions.
Growth Path
Tools Used
Perfect For
Computer Science and Engineering Graduates | Software Developers and Backend Engineers | AI and Machine Learning Enthusiasts | Data Scientists and Generative AI Aspirants | Product and Innovation Professionals | Individuals Interested in Building LLM-Powered Applications
Fee Structure
Mentor
Analytics Learners
Professional Analyst & Mentor
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