-
Welcome to LangChain for QA: What You Will Build
1 Lesson-
PreviewCourse Overview: The Real Projects You Will Build
-
-
Hands On Setup: Python, VS Code and LLM API Keys
7 Lessons-
PreviewWhat Is LangChain and Why QA Teams Are Adopting It
-
PreviewA Quick Tour of LangChain Docs So You Never Get Stuck
-
StartDownload and Install Python
-
StartSetting Up VS Code as Your AI Development Environment
-
StartConfiguring Python in VS Code Step by Step
-
StartInstalling LangChain and Connecting Your First LLM
-
StartGetting Your Anthropic and OpenAI API Keys
-
-
Build Your First AI Agent: Tools, Memory and Streaming
11 Lessons-
StartBuild and Run Your First AI Agent in Minutes
-
StartExtracting Clean Output Text From Your Agent
-
StartWhy System Messages Make or Break Your Agent
-
StartGiving Your Agent Tools to Take Real Actions
-
StartInitializing and Configuring Your Chat Model
-
StartStreaming Responses for a Real Time Feel
-
StartWhy Your Agent Forgets Everything Without Memory
-
StartImplementing Short Term Memory in Your Agent
-
StartMastering the Messages Module in LangChain
-
StartTeaching Your Agent to Understand Images and More
-
StartHands On: Analysing Local Image Files With Your Agent
-
-
Production Ready Agents: Middleware for HITL, Fallbacks and PII
9 Lessons-
StartWhat Middleware Is and Why Production Agents Need It
-
StartAutomatically Summarizing Long Agent Conversations
-
StartAdding Human in the Loop (HITL) Approval to Your Agent
-
StartHuman in the Loop in Action: A Second Real Example
-
StartProtecting Your Budget With Call Limit Middleware
-
StartNever Let Your Agent Go Down: Model Fallback Middleware
-
StartProtecting Sensitive Data With PII Middleware
-
StartKeeping Long Running Agents on Track With Todo Middleware
-
StartPrebuilt Tools and Building Your Own Custom Middleware
-
-
Download Sample Documents Used for Building Agentic RAG
1 Lesson-
StartDownload Sample Documents used for Agentic RAG
-
-
Build a Working RAG Pipeline: Embeddings to Retrieval
12 Lessons-
StartWhat Retrieval Is and Why Your Agent Needs It
-
StartRAG Architecture Explained
-
StartUnderstanding Embedding Models
-
StartMapping Out a Complete Retrieval Pipeline
-
StartLoading Real Documents With LangChain Docling
-
StartConfiguring Your Hugging Face Token and Symlinks
-
StartSplitting Text the Right Way for Better Retrieval
-
StartComparing Text Splitters and When to Use Each
-
StartGenerating Embeddings From Your Documents
-
StartStoring Your Documents in a Vector Store
-
StartRunning Similarity Search and Building a Retriever
-
StartHands On Project: Build a Complete 2 Step RAG System
-
-
Hands On MCP Project: Connect Your Agent to Jira
5 Lessons -
Trace and Chat With Your Agent: LangGraph, LangSmith, Agent Chat UI
6 Lessons -
Python for Testers
46 Lessons-
StartIntroduction
-
StartIntroduction to Python Tutorial
-
StartVariables in Python
-
StartVariable Rules in Python
-
StartOperators in Python
-
StartArithmetic Operators in Python
-
StartPython Operator Precedence
-
StartBoolean Data Type in Python
-
StartWhat are Strings in Python
-
StartString Functions in Python
-
StartString Slicing in Python
-
StartHow to Format Strings in Python
-
StartLists in Python
-
StartList Methods in Python
-
StartSets in Python
-
StartSet Methods in Python
-
StartTuples in Python
-
StartTuple Methods in Python
-
StartDictionaries in Python
-
StartDictionary Methods in Python
-
StartHow to Use If else in Python
-
StartWhile Loop in Python
-
StartBreak and Continue in Python
-
StartFor Loop in Python
-
StartZip Function in Python
-
StartRange Function in Python
-
StartFunctions in Python
-
StartReturn Statement in Python
-
StartKeyword and Positional Arguments in Python
-
StartVariable Scope in Python
-
StartBuild in Functions in Python
-
StartDatetime Module in Python
-
StartClasses and Objects in Python
-
StartCreating Objects and Methods in Python
-
StartClass Variables Vs Instance Variables in Python
-
StartInheritance in Python
-
StartMultiple Inheritance in Python
-
StartMultilevel Inheritance in Python
-
StartModules in Python
-
StartException Handling in Python
-
StartHow to Write File in Python
-
StartHow to Read File in Python
-
StartWith Keyword in Python
-
StartHow to Write Data to Excel in Python Openpyxl
-
StartHow to Read Excel File in Python Openpyxl
-
StartHow to Generate Test Data Using Python
-
About This Course
LangChain is transforming how QA professionals approach test automation and quality assurance. If you're tired of purely manual testing workflows and want to leverage AI to make smarter decisions, faster, this course is built for you.
What makes this different? Unlike generic AI courses, we focus on practical LangChain implementation for QA professionals. You'll learn to build production-ready AI agents that handle test analysis, automate bug triage, process test data with retrieval-augmented generation (RAG), and create intelligent chatbots that answer testing questions. All without needing a machine learning background.
Throughout this hands-on course, you'll progress from LangChain fundamentals to building three real-world solutions: a RAG system that answers questions from your test documentation, a conversational chatbot for test case recommendations, and an agentic AI workflow specifically designed for QA automation. You'll understand system messages that guide AI behavior, implement memory to maintain context across conversations, stream outputs for responsive interfaces, and handle multimodal inputs like screenshots and logs from your test environments.
We cover everything step-by-step: setting up Python and VS Code, integrating APIs from Anthropic and OpenAI, working with LangGraph for complex workflows, and using LangSmith for debugging and monitoring your agents. You'll also explore middleware, memory management, and tools. These are the building blocks of effective AI agents.
By the end, you'll have a complete toolkit to bring AI into your QA strategy. You'll automate repetitive testing decisions, build knowledge systems that learn from your test history, and create AI-powered workflows that scale your QA efforts without adding headcount. Whether you're an SDET, QA engineer, or test automation specialist, you'll gain hands-on skills to stay ahead in an AI-augmented testing landscape.
What You'll Learn
Build LangChain AI Agents from Scratch
Design and build LangChain AI agents from scratch that handle test automation workflows.
Retrieval-Augmented Generation (RAG)
Implement RAG to create intelligent test documentation systems that answer questions from your own data.
Agentic AI for QA Decisions
Create agentic AI solutions that automate bug triage, test analysis, and QA decision-making.
Multi-Step Workflows with LangGraph
Work with LangGraph to orchestrate multi-step workflows for complex QA scenarios.
Stream Agent Outputs
Stream agent outputs for responsive, interactive testing tools that feel fast and alive.
Debug & Monitor with LangSmith
Debug and monitor AI agents using LangSmith for production reliability.
Conversational QA Chatbots
Build conversational chatbots that provide intelligent test case and strategy recommendations.
Core Agent Mechanics
Understand system messages, tools, and middleware — the core mechanics of AI agents.
Meet Your Instructor
Manish Verma
Founder & Senior QA Architect
20+ years of QA expertise, now focused on AI-augmented testing
Manish is the founder of RCV Academy and a recognized leader in QA training and AI-powered test automation. With extensive experience at companies like IBM and Capgemini, he brings real-world insights from applying Agentic AI, RAG, and LangChain to practical QA workflows.
His teaching approach combines practical, hands-on learning with industry best practices. Over 225,000 students trust his content across multiple platforms, making him one of the most recognized QA educators in the industry.
Choose Your Learning Plan
Start learning today with flexible pricing options designed for every budget and commitment level.
Monthly
Start with flexibility
$5.99/month
Cancel anytime, first payment non-refundable
- 8.5+ hours of content
- Lifetime access
- All course materials
- Certificate included
- Cancel anytime
One-Time
Best value for commitment
$29.99once
Own it forever with no recurring charges
- 8.5+ hours of content
- Lifetime access
- All course materials
- Certificate included
- 30-day guarantee
Most Popular
Lifetime
Ultimate value package
$99once
Access all courses + future releases
- All RCV Academy courses
- Lifetime updates
- All new courses included
- Priority support
- 30-day guarantee
What You Need
Course Requirements
- Basic familiarity with command line and terminal
- Prior QA or testing experience is helpful but not mandatory
- Python fundamentals (Python tutorials available in course if you are new to Python)
Frequently Asked Questions
How long do I have access to the course? +
Forever. Once you enroll, you have lifetime access to all videos, materials, and future updates. Whether you choose monthly, one time, or lifetime membership, the access does not expire.
I don't have a machine learning background. Will I understand everything? +
Yes. This course is built specifically for QA professionals, not data scientists. We walk through LangChain step by step, starting with Python and VS Code setup, so no prior machine learning background is needed.
What is the difference between the three pricing options? +
Monthly at $5.99 per month lets you start cheap but costs $71.88 yearly if you keep it. One time at $29.99 lets you own this course forever. Lifetime membership at $99 gives you access to all courses on the platform, all future updates, and any new courses released. All plans include a 30 day guarantee.
Do I get a certificate? +
Yes. After completing the course, you will receive a certificate of completion that you can share on LinkedIn or include on your resume as proof of your LangChain and AI agent skills for QA.
What if I am not satisfied? +
We offer a 30 day money back guarantee with no questions asked. If you enroll and decide the course is not right for you within 30 days, we will refund your full payment. We are confident you will love it, but we want you to feel secure.
How many hours of content are there? +
The course contains 8.5 hours of on-demand video, plus 2 articles and 3 downloadable resources. Most students complete it in 4 to 6 weeks at 1 to 2 hours per week. You can watch at your own pace and revisit sections anytime.
Who This Course Is For
SDETs
Want to integrate AI into their automation frameworks and scale their testing capabilities.
QA Leads & Managers
Exploring how AI can scale QA workflows across teams without adding headcount.
QA Engineers / Manual Testers
Transitioning to AI-powered testing strategies and looking to future-proof their skill set.
Test Architects
Designing next-generation QA systems that incorporate agentic AI and RAG pipelines.
Anyone Curious About AI in QA
Curious about practical AI applications in testing, no machine learning background needed.
30 Day Money Back Guarantee
Your satisfaction is guaranteed. Enroll risk free. If the course is not what you expected within 30 days, get a full refund with no questions asked. We are this confident you will love it.
