• views: 199
• date: 19 March 2026
• posted by: 0nelove

LangChain v1, Gemini 3, LangSmith, Tool Calling, Streaming, Image Analysis, PDF Analysis, Context Caching, Grounding
What you'll learn
✓ Build Agentic AI apps using LangChain and Gemini 3 models
✓ Implement tool calling, web search and weather tools in AI systems
✓ Analyze images and financial PDFs using Gemini models
✓ Apply context caching, grounding and streaming in real AI workflows
Requirements
● Basic Python knowledge is helpful but not mandatory, everything is explained step by step
Description
Learn how to build powerful Agentic AI and GenAI applications using LangChain and Google Gemini with real-world, hands-on examples. This course takes you step-by-step from setting up APIs to building intelligent systems that can interact with tools, analyze data, and generate meaningful responses.
You will start by setting up Google AI Studio, Gemini API, and LangSmith for tracing and debugging. Then, you will dive deep into ChatGoogleGenerativeAI and understand how modern chat models work, including message structures, streaming responses, and model comparisons.
This course focuses on practical implementation, where you will learn how to
• Chat with Gemini models
• Analyze images (URL and local files)
• Work with financial PDF documents
• Build and integrate real-world tools like web search and weather APIs
• Use tool calling (function calling) to create intelligent workflows
You will also explore advanced capabilities such as
• Context caching for performance and cost optimization
• Grounding using Google's built-in search tool
• Rate limits and pricing strategies for different Gemini models
• Controlling reasoning (thinking) in Gemini models
By the end of this course, you will have a strong understanding of how to build real-world AI systems using LangChain and Gemini, and how to optimize them for performance, cost, and scalability.
What You Will Learn
• Build Agentic AI and GenAI applications using LangChain and Gemini
• Set up Google AI Studio, Gemini API, and LangSmith
• Understand ChatGoogleGenerativeAI, SystemMessage, HumanMessage, and AIMessage
• Work with streaming responses from chat models
• Compare Gemini models and analyze response metadata
• Analyze images using Gemini (URL and local files)
• Perform financial PDF document analysis
• Build tools like web search and weather APIs using LangChain
• Implement tool calling (function calling) in LLMs
• Use grounding with Google's built-in search tool
• Apply context caching for cost optimization
• Understand Gemini pricing and rate limits
• Control reasoning (thinking) behavior in Gemini models
Who this course is for
■ Python developers, AI engineers and beginners who want to build real-world GenAI and Agentic AI applications using LangChain and Gemini




   
   
   

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