Learn agentic AI and generative AI in New York using OpenAI API, LangChain, Hugging Face API, Pinecone, LangGraph, AutoGen, CrewAI, Docker, FastAPI, and Python-based tooling. You will build practical AI workflows, research agents, and deployable projects with the tools listed in the syllabus.
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 agentic AI is useful only when you can show practical work and explain it clearly in interviews. Inventateq helps you turn the course projects into interview-ready proof, with support for resumes, portfolio presentation, and role-specific preparation for AI and analytics jobs in New York.
New York hires for AI, analytics, business intelligence, and automation roles across tech, finance, consulting, media, and enterprise teams. Salary grows as you move from project execution into workflow design, deployment, and architecture.
Artificial Intelligence Average Salary by Experience
New York hires for AI, analytics, business intelligence, and automation roles across tech, finance, consulting, media, and enterprise teams. Salary grows as you move from project execution into workflow design, deployment, and architecture.
Artificial Intelligence Average Salary by Experience
4.7/5 Google Rating | 1,432+ Verified Reviews
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Success Result: Our students are competing at global levels. Watch their placement journey here.
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Inventateq teaches artificial intelligence through the actual workflow you need on the job: prompt engineering, tool calling, memory, agent frameworks, evaluation, and deployment. The course is built from the syllabus itself, so the learning path moves from foundational agent concepts to LangGraph, AutoGen, CrewAI, FastAPI, Docker, and cloud deployment in a practical sequence.
We stand apart through our commitment to:
Live online training gives you the same syllabus, mentor guidance, and project-based learning from wherever you are in New York. It is suitable for working professionals and students who want structured sessions without commuting. You can still participate in exercises, review code, and complete project work with support.
A good fit if you want to start with agentic AI, prompt engineering, and practical projects without guessing what to learn first.
Useful for people who already know basic Python, SQL, or analytics and want to move into AI workflows.
Helps developers, analysts, and automation professionals add LangChain, LangGraph, and deployment skills.
Good for learners moving from operations, reporting, or support roles into AI and business intelligence work.
A strong option if you want project-based AI training that can support interviews and portfolio building.
Duration: Structured across modules that cover agentic AI, generative AI, and deployment topics.
Mode: Available through classroom and live online training.
Training Style: Concepts are taught through guided practical work and project tasks.
Location: Built for learners in New York and accessible online from anywhere.
No prior AI project experience is required to start the course.
Rated 4.9/5
Inventateq keeps the training practical from the first module. You learn by building the kinds of AI systems employers actually ask about: agents, tool-based workflows, memory-backed systems, and deployable services.
You do not just read about agents. You practice prompt design, tool calling, memory handling, workflow planning, evaluation, and deployment in a structured way that builds usable skill.
Work on a research agent and a data analyst agent, using structured function calling, code execution, and visual outputs.
Understand how to connect agents to tools, define schemas, handle errors, and manage parallel actions.
Practice short-term and long-term memory design so your AI workflows can keep context across sessions.
Get hands-on exposure to LangChain, LangGraph, AutoGen, and CrewAI in the context of real tasks.
Learn how to deploy agent services with FastAPI, Docker, AsyncIO, and cloud hosting patterns.
Translate course work into a clear project story for AI, analytics, BI, and automation roles.
The certification confirms that you completed practical training in agentic AI, generative AI, tools, memory, frameworks, and deployment. It helps employers see that you have done structured work with the tools used in current AI workflows.
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, beginners can join if they are willing to learn step by step. The course starts with agent concepts, prompt engineering, and the basic building blocks before moving into frameworks and deployment. If you do not have a full AI background, the structured format helps you catch up.
Yes, the syllabus includes practical work such as a research agent, a data analyst agent, and deployment exercises. You will also practice tool use, memory handling, and multi-agent workflows. The focus is on learning by doing, not only listening to theory.
Yes, Inventateq provides placement support tied to the roles covered in the course. That includes help with resume preparation, interview practice, and project presentation. The goal is to help you apply for roles with a clear story around your skills and projects.
Yes, non-technical learners can join if they are ready to build basic workflow understanding and practice regularly. The course explains concepts in a practical way and gradually moves into more advanced topics. Candidates from analytics, operations, support, and business roles often find this kind of training useful.
Yes, live online training is available for learners in New York and beyond. You can attend sessions remotely and still follow the same module flow, exercises, and project work. This is useful if you want structured training without traveling to a classroom.
The course is organized across multiple modules and weeks, covering a complete workflow from fundamentals to deployment. The actual pace can vary based on the batch format and learner background. The important part is that each module builds on the previous one so you can follow the course logically.
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