What will you in ChatGPT and LangChain: The Complete Developer’s Masterclass Course
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Integrate ChatGPT into production-grade apps using LangChain components and pipelines.
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Build multi-step text-generation workflows with retrieval augmentation, memory, and user-feedback loops.
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Implement real-time server-to-browser streaming via Celery, Redis, and observability tooling.
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Create custom ChatGPT plugins for database access and code execution within your applications.
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Develop a fully-featured Chat-with-a-PDF web app, including file upload, authentication, streaming, and tracing.
Program Overview
Module 1: Intro & Setup
⏳ 30 minutes
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Environment setup: Python, LangChain, ChatGPT‑4 API integration.
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Foundations: chains, conversational memory, and feedback-driven refinement.
Module 2: Chains & Pipelines
⏳ 90 minutes
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Build pipelines combining LangChain components and feedback logic.
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Introduce semantic memory and RAG using embeddings and retrievers.
Module 3: Retrieval-Augmented Generation
⏳ 120 minutes
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Integrate vector stores (ChromaDB, Pinecone) with embeddings.
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Enable conversational memory, context summarization, and plugin-driven tool chains.
Module 4: Web App – Chat With PDF
⏳ 90 minutes
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Build and deploy a PDF chatbot with authentication and streaming UX.
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Manage large documents via streaming, memory, and backend optimizations.
Module 5: Plugins & Tools
⏳ 75 minutes
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Develop OpenAI plugins: database lookups, calculations, code execution.
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Integrate custom tools into your ChatGPT workflows.
Module 6: Distributed Systems & Observability
⏳ 45 minutes
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Use Celery, Redis for asynchronous LLM processing pipelines.
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Implement tracing and telemetry to monitor user & AI interactions.
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Job Outlook
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High demand for AI engineers specializing in production-ready LLM pipelines, agents, and AI-driven apps.
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Elevates credentials for roles in AI engineering, backend development, and intelligent system design.
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Salary potential: $120K–$180K+ for GenAI-enabled software developers.
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Freelance potential: Develop chatbot systems, AI plugin integrations, and backend pipelines.
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