Agentic AI with Lang Chain and Lang Graph Training Course in Gurgaon
With high-demand of AI Skills, Join our Agentic AI and Lang Graph Training program to become a successful AI professional
- Get mastery in building Agentic AI workflow for intelligent automation and to drive key businesses powered through Agentic AI frameworks like Lang Graph and others.
- Experience blended learning through interactive offline and online sessions.
- Job Assured Course
- Course Duration - 3 months
- Trained from Industry Experts
Train using realtime course materials using online portals & trainer experience to get a personalized teaching experience.
Trained through leading industry professionals to get realtime project exposure
Gain professionals insights through leading industry experts across domains
24/7 Q&A support designed to address training needs
Agentic AI Workflow and Lang Graph Automation Course
Kick start your career in AI with certification in Generative AI Engineer course, that will help in shaping the career to the current industry needs that need automation using intelligent agentic ai workflow like n8n, Microsoft Auto Gen, Lang Graph and others in every domain and sphere of the industry that will allow organizations to boost decision making and also thrive business growth with improved customer satisfaction.
- Self-paced videos & training materials with archived session recordings
- Success Aimers targets industry employers to gain visibility
- Industry-paced training with real time scenarios using Agentic AI frameworks/tools (n8n, Microsoft Auto Gen, Lang chain, Lang Graph, AWS Bedrock, Azure Open AI and others) for intelligent automation.
- Real-World industry scenarios with projects implementation support
- Live Virtual classes heading by top industry experts along with project implementation
- 24/7 Q&A support sessions
- Job Interview preparation and use cases
Explain Gen AI Engineer?
AI Engineers automate business processes via AI development frameworks (Agentic AI) like n8n, Microsoft Auto Gen, Lang chain, Lang Graph, AWS Bedrock, Azure Open AI and others for intelligent automation that will allow organizations to boost decision making and also thrive business growth with improved customer satisfaction. AI engineers build optimized workflows, deployment and maintain the AI development life cycle to deliver high-précise solutions to the clients using Agentic AI frameworks/workflow builders.
Role of Gen AI Engineer?
Generative AI Engineers manages the end-to-end AI development life cycle using Agentic AI frameworks and intelligent workflow strategies.
Responsibilities include:
- Agentic AI Tools Adoption & automation using patterns like RAG, Tools, Reflection and others
- Continuously exploring new AI based frameworks/tools to build optimized workflows
- Deploying AI model within cloud infrastructure securely & seamlessly.
- Develop and Design AI workflows that meets business needs with automation scripts
- Success Aimers helps aspiring AI professionals to build, deploy, manage these Agents effectively seamlessly and to scale as per business needs.
Who should opt for Gen AI Engineer course?
Gen AI course accelerates/boost carrier in AI & technology-driven organizations
- AI & Application Engineers – Develop Agentic AI workflows to automate business processes.
- Data Engineers – Implementing Data Pipelines using AI
- AI Developers – Automated workflows using Agentic AI frameworks/tools
- AI Leaders – Leading AI Governance and initiative within enterprise.
- Cloud and Infrastructure Engineers – Deploying AI developed applications seamlessly and effectively.
Prerequisites of Gen AI Engineer Course?
Prerequisites required for the Generative AI Engineer Certification Course
- Below is the prerequisite to become a successful AI Professional:
- High School Diploma or a undergraduate degree
- Python Programming language
- IT Foundational Knowledge along wit Data Science and Software Development skills
- Knowledge of Cloud Computing Platforms like AWS, AZURE and GCP will be an added advantage.
Kind of Job Placement/Offers after Gen AI Engineer Certification Course?
Job Career Path in Generative AI and N8N Automation
- Generative AI Engineer – Develop & Deploy AI developed solutions/applications using agentic frameworks/tools
- AI/ML Engineer – Build context-aware, Enterprise ready AI systems.
- AI Automation Engineer – Design, Developed and build automated workflows to drive key business processes/decisions
- Cloud AI Engineer / AI Cloud Architect – Deploy AI Solutions seamlessly and effectively across enterprises with AI Governance strategy
- AI Model Deployment Engineer – Automate Model Deployment and AI Life cycle management via ML Ops pipeline and Agentic AI Frameworks
| Training Options | Weekdays (Mon-Fri) | Weekends (Sat-Sun) | Fast Track |
|---|---|---|---|
| Duration of Course | 2 months | 3 months | 15 days |
| Hours / day | 1-2 hours | 2-3 hours | 5 hours |
| Mode of Training | Offline / Online | Offline / Online | Offline / Online |
Agentic AI and Lang Graph Automation Certification Course Curriculum
Start your career in AI with certification in Generative AI Engineer course, that will help in shaping the career to the current industry needs that need automation using intelligent workflows like n8n, Microsoft Auto Gen, Lang Graph and others in every domain and sphere of the industry that will allow organizations to boost decision making and also thrive business growth with improved customer satisfaction.
Generative AI Basics
- Introduction
- Develop Gen AI App
- Prompt Engineering Basics
- Open AI Key & Integration
- Using OLlama models locally
- Using Streamlit UI
- Gen AI Models
LLM Introduction & Basics
- Basics of LLM
- Basics of Prompting
- Basics of Prompt Engineering
- Few Shot Prompting
- Chain of Thought (CoT) Prompting
- Pipeline-Prompts
- Prompt Serialization
Chains - Basic to Advanced Chains
LLM Chains
- Chains Introduction
- LLMChain Basics
- Response Schemas and OuputParsers
- LLMChain with multiple Inputs
- SequentialChains
- RouterChains
Callbacks (Function Calling)
- AsyncIteratorCallbackHandler
- AsyncFinalIteratorCallbackHandler
- FinalStreamingStdOutCallbackHandler
- LoggingCallbackHandler
Memory
- Memory Basics - ConversationBufferMemory
- ConversationSummaryMemory
- ConversationBufferMemory
- ConversationBufferWindowMemory
- InMemoryEntityStore
- VectorStoreRetrieverMemory
Retreival Augmented Generation (RAG)
- RAG - Theory and building locks
- Loaders and Splitters
- Embeddings
- VectorStores and Retreivers
- RetreivalQAChain
- RAG Service and Fast API
- Prompt Serialization
Agents
- Agents Basics - LLMs learn to use tools
- Agents with a custom RAG-Tool
- Chat Agents
- Agent Executor
- ChatOutputParser
- VectorStoreInfo
- LLMSingleActionAgent
Indexing API
- Indexing API - Keep our Documents in Sync
- Setup of PgVector and RecordManager
- Indexing Documents
- Document Retrieval with PgVector
LangSmith
- Introduction to LangSmith
- LangSmith Projects
- LangSmith Datasets and Evaluation
- Tracing an Application
LangChain Expression Language (LCEL)
- LangChain Expression Language
- Intro to LangChain Expression Language
- LCEL Basics - Operator Overloading
- LCEL Deep Dive - Let's implement our own LCEL
- LCEL - Invoke,Stream, Batch
- Retrieval Augmented Generation (RAG) with LCEL
- Migration - Chain to Runnable Interfaces - Basics
- Migration - ConversationQAChain with History in LCEL
- LCEL Part 1 - Pipes and OpenAI Function Calling
- LCEL Part 2 - VectorStores,ItemGetter, Tools
- LCEL Part 3 - Arbitrary Functions, Runnable Interface, Fallbacks
LangChain - Agentic AI Orchestrator/ Framework
AI Agents – Deep Dive
- AI Agents Deep Dive – A Full Overview
- Agents Characteristics and Use Cases
- Building our First AI Agent – Project Setup (Open AI API)
- Building our First AI Agent – Creating the Agent Class and Prompt
- First AI Agent – Running our First Agent and Seeing the Results
- Passing Complex Queries Through the Agent
- First Agent – Using a Loop to automate our Agent
- Adding Interactive to our Agent – Console App
Build AI Agents with Lang Graph – Deep Dive
- Lang Graph – Overview & Key Concepts
- How Lang Graph helps to build AI Agents
- Lang Graph Core Concepts – Simple Flow Diagram
- Lang Graph - Data and State – Overview
- Building a Simple Agent with Lang Graph
- Lang Graph Simple Bot – Streaming Values – ConsoleApp
- Adding Tools to our Basic Lang Graph Agent
- Adding Tools to the Agent – Part 1
- Adding Tools to the Agent - Using Built-In Tools – Part 2
- dding Memory to our Agent State
- Adding Human-in-the-Loop to the AI Agent
LangGraph Ecosystem – LangGraph Studio, LangGraph Cloud API , LangGraph Cloud
- LangGraph Studio (AKA LangGraph IDE)
- LangGraph Cloud API – Environment Setup (Local)
- LangGraph Cloud API Deep Dive – Assistants, Threads , Runs (Local)
- Deploying to LangGraph Cloud
Hours of content
Live Sessions
Software Tools
After completion of this training program you will be able to launch your carrer in the world of AI being certified as Generative AI Certified Professional.
With the AI Certification in-hand you can boost your profile on Linked, Meta, Twitter & other platform to boost your visibility
- Get your certificate upon successful completion of the course.
- Certificates for each course
- Gen AI
- Agentic AI
- Agentic AI Frameworks
- LangGraph
- Azure AI
- LangChain
- Model Context Protocol
- Generative AI
- Vector DB
- Embedding Models
- LLM Models & Integration
- AI Governance
- AWS Bedrock
- Gaurdrails
60% - 100%
Designed to provide guidance on current interview practices, personality development, soft skills enhancement, and HR-related questions
Receive expert assistance from our placement team to craft your resume and optimize your Job Profile. Learn effective strategies to capture the attention of HR professionals and maximize your chances of getting shortlisted.
Engage in mock interview sessions led by our industry experts to receive continuous, detailed feedback along with a customized improvement plan. Our dedicated support will help refine your skills until your desired job in the industry.
Join interactive sessions with industry professionals to understand the key skills companies seek. Practice solving interview question worksheets designed to improve your readiness and boost your chances of success in interviews
Build meaningful relationships with key decision-makers and open doors to exciting job prospects in Product and Service based partner
Your path to job placement starts immediately after you finish the course with guaranteed interview calls
Why should you choose to pursue a Gen AI/Agentic AI course with Success Aimers?
Success Aimers teaching strategy follow a methodology where in we believe in realtime job scenarios that covers industry use-cases & this will help in building the carrer in the field of AI & also delivers training with help of leading industry experts that helps students to confidently answers questions confidently & excel projects as well while working in a real-world
What is the time frame to become competent as a Gen AI engineer?
To become a successful Gen AI Engineer required 1-2 years of consistent learning with dedicated 3-4 hours on daily basis.
But with Success Aimers with the help of leading industry experts & specialized trainers you able to achieve that degree of mastery in 6 months or one year or so and it’s because our curriculum & labs we had formed with hands-on projects.
Will skipping a session prevent me from completing the course?
Missing a live class won’t prevent you from completing the course. You can conveniently watch the recorded session of any class you miss at your own pace.
What industries lead in Gen AI implementation?
- Manufacturing
Financial Services
Healthcare
E-commerce
Telecommunications
BFSI (Banking, Finance & Insurance)
“Travel Industry
Does Success Aimers offer corporate training solutions?
At Success Aimers, we have tied up with 500 + Corporate Partners to support their talent development through online training. Our corporate training programme delivers training based on industry use-cases & focused on ever-evolving tech space.
How is the Success Aimers Gen AI Certification Course reviewed by learners?
Our Gen AI Engineer Course features a well-designed curriculum frameworks focused on delivering training based on industry needs & aligned on ever-changing evolving needs of today’s workforce due to AI.
Also our training curriculum has been reviewed by alumi & praises the thoroguh content & real along practical use-cases that we covered during the training. Our program helps working professionals to upgrade their skills & help them grow further in their roles…
Can I attend a demo session before I enroll?
Yes, we offer one-to-one discussion before the training and also schedule one demo session to have a gist of trainer teaching style & also the students have questions around training
programme placements & job growth after training completion.
What batch size do you consider for the course?
On an average we keep 5-10 students in a batch to have a interactive session & this way trainer can focus on each individual instead of having a large group
Do you offer learning content as part of the program?
Students are provided with training content wherein the trainer share the Code Snippets, PPT Materials along with recordings of all the batches
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