Learn artificial intelligence in Delhi with a practical focus on agentic AI, generative AI, LangChain, LangGraph, OpenAI API, Hugging Face, Pinecone, Docker, FastAPI, and cloud deployment. Build working agents, structured outputs, memory workflows, multi-agent systems, and deployment-ready projects step by step.
14,200+ (Placed)
Freshers to IT
7,100+ (Placed)
Non-IT to Tech
5,800+ (Placed)
Career Gap Fillers
6,400+ (Placed)
Upskilling Success
24,999₹
In 60 Days + Placement
Free Session
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Learning artificial intelligence is useful only when you can show practical work and explain it clearly in interviews. Inventateq supports Delhi learners with project-based training, interview preparation, and guidance for roles that use agentic AI, generative AI, data workflows, and deployment tools.
Delhi companies hire for AI, analytics, automation, and data roles across IT services, product teams, consulting, and startups. Pay usually grows with project depth, deployment skills, and experience with tools like Python, LangChain, and cloud platforms.
Artificial Intelligence Average Salary by Experience
Delhi companies hire for AI, analytics, automation, and data roles across IT services, product teams, consulting, and startups. Pay usually grows with project depth, deployment skills, and experience with tools like Python, LangChain, and cloud platforms.
Artificial Intelligence Average Salary by Experience
4.7/5 Google Rating | 1,432+ Verified Reviews
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Inventateq teaches artificial intelligence in a practical sequence, starting from agent basics and moving into prompting, tool calling, memory, planning, multi-agent design, guardrails, evaluation, and deployment. The training uses real tools such as OpenAI API, LangChain, LangGraph, AutoGen, CrewAI, Pinecone, LangSmith, Phoenix Arize, Docker, FastAPI, AWS, and Render.
We stand apart through our commitment to:
Live online training is available for Delhi learners who want flexible access to the same practical curriculum. The sessions stay interactive, so you can ask questions, follow along with projects, and complete the course from home or office.
Good for learners starting a career in AI, data, or analytics and wanting practical project work.
Useful for people moving into AI-enabled roles, automation, or LLM-based development.
Fits learners who already know reporting or analysis and want to move into AI workflows.
Helps software professionals learn agentic AI, tools, memory, and deployment patterns.
Suitable for learners who want a guided start and can follow a structured, hands-on path.
Mode: Offline classroom and live online training
Format: Instructor-led practical sessions
Pace: Structured module-wise learning
Support: Mentor guidance throughout the course
No prior AI experience is required to get started.
Rated 4.9/5
Inventateq focuses on practical AI training that connects concepts to working systems. Learners move through prompting, tools, memory, frameworks, evaluation, and deployment in a clear sequence that matches how real AI projects are built.
You work on agent-based AI workflows, multi-step prompting, tool use, memory design, observability, and deployment. By the end, you have practical project experience you can explain in interviews and use in your portfolio.
Create research and data-focused agents that use prompts, tools, memory, and structured outputs. The course moves beyond theory and shows how agent logic is actually assembled.
Use LangChain, LangGraph, AutoGen, and CrewAI to build workflows with different levels of control. This helps you understand how modern AI applications are organized.
Work with short-term context, vector database memory, and episodic memory. This is important when building AI systems that need to remember actions and outcomes.
Add human approval steps, guardrails, and budget limits to agent workflows. These controls matter when systems can take actions or call external tools.
Use tracing and observability tools to find latency, token usage, and failure points. You learn how to measure whether an agent behaves reliably.
Package projects with Docker, expose them with FastAPI, and deploy on cloud platforms. This makes your work closer to what employers expect from production-ready training.
The certification validates that you have completed practical training in agentic AI, generative AI, tools, memory, workflows, and deployment. It helps show employers that you have learned real tools and completed structured project work.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Earn this certificate upon successful completion of our training program.
Validate your skills with recognized industry credentials.
Yes. The training starts with core concepts like chatbots, LLMs, and agents before moving into tools, memory, and workflows. Beginners can follow it if they are consistent with practice and assignments.
Yes. You work on projects such as a research agent, a data analyst agent, and deployment-focused exercises. The projects are based on the syllabus and are meant to show practical AI workflow skills.
Yes, Inventateq provides placement-oriented support that includes resume preparation, mock interviews, and portfolio guidance. The support is designed around the job roles linked to AI, analytics, and business analysis.
You can join if you are ready to learn the required basics and follow the guided process. The course is practical, but it still expects regular practice with prompts, tools, and project work. Mentors help you move through the difficult parts.
Yes. Delhi learners can join live online sessions and follow the same instructor-led training as classroom batches. This is useful if you want flexibility without losing the interactive format.
The course uses tools like OpenAI API, LangChain, LangGraph, AutoGen, CrewAI, Pinecone, LangSmith, Phoenix Arize, Docker, FastAPI, AWS, and Render. You also work with structured prompting and deployment workflows that connect these tools together.
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