Generative AI with Vector Databases and RAG Certification Course in Gurgaon
AI is the future innovation with Agentic AI tools and frameworks (n8n, Auto-Gen, ChatGPT, Gen AI ) for intelligent automation. We are delivering this training in Gurgaon where-in core Gen AI principles using patterns like multi-agents, reflection & others will be taught using hands-on training to become a Gen AI Engineer.
- Get mastery in building Agentic AI workflows for intelligent automation & to drive key businesses powered through agentic ai frameworks like n8n,Auto GPT, ChatGPT & others.
- Experience blended learning through interactive offline and online sessions.
- Job Oriented Training Course
- Course Duration - 3 months
- Get 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
Generative AI with Vector Databases and RAG, Chat GPT, Lang Chain & AI Agent Course
Kickstart your carrer in AI with certification in Generative AI Engineer course, that will help in shaping the carrer to the current industry needs that need automation using intelligent workflows like n8n, Microsoft AutoGen ,LangGraph, Vector DB & others in every domain & sphere of the industry that will allow organizations to boost decision making & 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 realtime scenarios using Agentic AI frameworks/tools (n8n, Microsoft AutoGen, Langchain, LangGraph, AWS Bedrock, Azure Open AI & others) for intelligent automation.
- Real-World industry scenarios with projects implementation support
- Live Virtual classes heading by top industry experts alogn with project implementation
- 24/7 Q&A support sessions
- Job Interview preparation & use cases
Explain Gen AI Engineer?
AI Engineers automate business processes via AI development frameworks (Agentic AI) like n8n, Microsoft AutoGen, Langchain, LangGraph, AWS Bedrock, Azure Open AI & others for intelligent automation that will allow organizations to boost decsion making & also thrive business growth with improved customer satisfaction. AI engineers build optimized workflows, deployment & maintain the AI development lifecycle to deliver high-précised 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 lifecycle using Agentic AI frameworks and intelligent workflow strategies.
Responsibilities include:
- Agentic AI Tools Adoption & automation using patterns like RAG ,Tools ,Reflection & others
- Continuously exploring new AI based frameworks/tools to build optimized workflows
- Deploying AI model within cloud infrastructure securly & seamlessly.
- Develop & Design AI workflows that meets business needs with automation scripts
- Success Aimers helps aspiring AI professionals to build, deploy, manage these Agents effectively seamlessly & 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 & initiative within enterprise.
- Cloud & Infrastructure Engineers – Deploying AI developed applications seamlessly & 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 & Software Development skills
- Knowledge of Cloud Computing Platforms like AWS, AZURE & GCP will be an added advantage.
Kind of Job Placement/Offers after Gen AI Engineer Certification Course?
- Job Carrer Path in Generative AI & 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 & build automated workflows to drive key business processes/decisions
- Cloud AI Engineer / AI Cloud Architect – Deploy AI Solutions seamlessly & effectively across enterprises with AI Governance strategy
- AI Model Deployment Engineer – Automate Model Deployment & AI Lifecycle management via MLOps pipeline & 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 |
Gen AI Engineer Certification Course Curriculum
Start your carrer in AI with certification in Generative AI Engineer course, that will help in shaping the carrer to the current industry needs that need automation using intelligent
workflows like n8n, Microsoft AutoGen ,LangGraph & others in every domain & sphere of the industry that will allow organizations to boost decision making & also thrive business growth with improved customer satisfaction.
Generative AI(Gen AI) - Deep Dive
Gen AI Introduction
- Evolution of AI: AI → Machine Learning → Deep Learning → Generative AI
- Introduction & Architecture of Generative AI
- Key Limitations, Technologies & Challenges
- Overview of Generative AI Components
- Generative AI Model Architectures: Types & Applications
Large Language Models (LLMs)
- LLMs Overview & How They Work
- Fundamentals of Transformer Architecture
- LLMs Tokenization
- LLM Capabilities: Text Generation, Summarization, Q&A, Classification
- Real-World Applications & Use Cases
- Limitations & Best Practices
- LLM Settings: Temperature, Max Tokens, Stop Sequences, Top-P, Frequency Penalty
- Function Calling & Structured Output
Prompt Engineering
- Understanding Prompts & Prompt Engineering
- Advanced Prompt Techniques: Zero-Shot, One-Shot, Few-Shot
- Chain-of-Thought Prompting
Ollama & Open-Source Models
- Ollama Introduction
- Key Features, Use Cases & Models
- Ollama CLI: Pulling and Testing Models
Context & Memory Management for LLMs
- Overview of Context & Memory Management
- Adding Memory & Context to Chatbots
Retreival-Augmented Generation (RAG)
- Introduction & Importance of RAG
- How RAG Works: Ingestion, Retrieval, Generation
- Architecture of RAG & End-to-End Workflow
- Applications & Use Cases
- Challenges in Implementing RAG
Vector Databases & Embeddings
- Vector Databases & Embeddings for RAG Workflows
- Introduction, Benefits, and Use Cases of Vector Databases
- Traditional vs. Vector Databases: Limitations & Advantages
- Overview of Top Vector Databases
- Chroma Database: Setup, Document Ingestion, Querying & Embeddings
- Using OpenAI LLM to Generate Responses from Vector Data
- LangChain & Pinecone Integration
- LangChain Embeddings Pinecone
Implementation of RAG PDF Workflow - Build RAG Workflows Deep Dive
- Building a RAG Pipeline
- Architectural Diagrams & Workflow Setup
- Embedding Models & RAG Workflow with UI (Streamlit)
LLM Tools and Frameworks - LangChain Deep Dive
- Introduction to LangChain & Main Components
- LangChain Setup, Chat Models, Prompt Templates
- Data Preparation: TextLoaders, Splitting & Cleaning
- Embeddings & FAISS VectorStore Integration
- Chains, RAG QA Bots, and End-to-End RAG Systems
Multimodal RAG
- Overview of Multimodal RAG & Benefits
- Comparing RAG vs. Multimodal RAG
- Multimodal Search & Image Embeddings in Vector Databases
AI Agents & Agentic Workflows
- Overview of AI Agents, Characteristics & Use Cases
- Building AI Agents: Project Setup, Agent Class & Prompts
- Handling Complex Queries & Adding Tools
- LangGraph Concepts: Data, State, Nodes, Edges
- Human-in-the-Loop (HIL) Integration with Agents
- Building Agentic Workflows with LangChain
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
- Vector DB
- Agentic AI
- Lang Chain
- Lang Graph
- AWS Bedrock
- Azure Open AI
- Auto GEN
- Model Context Protocol (MCP)
- AI Governance
- Autonomous Agents
- N8N
- Multimodal RAG's
- MLOps
45% - 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 session doesn’t impact your training because we have the live recorded session that’s students can refer later.
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 alumni & praises the thorough 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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