Learn agentic AI, generative AI, LangChain, Hugging Face API, OpenAI API, Pinecone, and LangGraph in Virginia. Build practical AI workflows, research agents, data analyst agents, and deployable multi-agent services 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₹
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Learning AI is only part of the path. You also need a clear way to present your projects, explain your architecture choices, and handle interviews for roles like AI Analyst, Junior AI Developer, and Business Analyst with AI exposure. Inventateq supports that process with practical placement help focused on the work you actually do in training.
Virginia hiring markets across tech, analytics, consulting, operations, and product teams need people who can work with AI workflows and data-driven systems. Salary grows as you move from assistant and analyst work into system design, team leadership, and architecture.
Artificial Intelligence Average Salary by Experience
Virginia hiring markets across tech, analytics, consulting, operations, and product teams need people who can work with AI workflows and data-driven systems. Salary grows as you move from assistant and analyst work into system design, team leadership, and architecture.
Artificial Intelligence Average Salary by Experience
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Success Result: Our students are competing at global levels. Watch their placement journey here.
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This course is built from the actual syllabus: agentic AI fundamentals, prompt engineering, tool use, memory, LangChain, LangGraph, AutoGen, CrewAI, evaluation, observability, and cloud deployment. Students work through the same sequence in a practical way so they understand how AI agents are designed, tested, and shipped.
We stand apart through our commitment to:
The live online batch is built for learners in Virginia who want the same structured training from home. You can attend mentor-led sessions, follow the project sequence, and complete assignments on agentic AI, generative AI, and deployment without missing the practical flow.
Good for learners starting with AI, data, or software basics who want a structured entry into agentic AI.
Useful for analysts who want to move into AI-driven workflows, automation, and dashboard-linked intelligence.
Fits professionals who need to understand AI systems, process automation, and decision support use cases.
Helpful for developers who want to build AI agents, APIs, and workflow-driven applications.
Suitable for people in Virginia who want practical AI skills for a role change or internal upskilling.
Duration: Structured around the syllabus sequence from fundamentals to deployment.
Mode: Available in classroom and live online formats.
Training style: Mentor-led sessions with practical examples and project work.
Learning pace: Built for step-by-step understanding of AI agents and generative AI.
No prior AI experience is required to begin.
Rated 4.9/5
Inventateq teaches AI in a practical sequence so learners can move from core concepts into working agent systems, generative AI workflows, and deployment. The course is organized around hands-on implementation, mentor review, and clear project outcomes.
By the end of the course, learners understand how to design agentic workflows, connect tools, manage memory, and deploy working AI services. The training is meant to produce usable project experience, not just notes.
Learn how to build agents that reason, act, and use tools through ReAct, planning, and multi-agent patterns.
Practice OpenAI API, LangChain, LangGraph, Hugging Face API, Pinecone, and FastAPI in guided exercises.
Understand short-term and long-term memory, vector databases, and retrieval for agent workflows.
Create research agents, data analyst agents, and chatbot projects that reflect the syllabus topics.
Use guardrails, approval steps, budget limits, and evaluation methods to control agent behavior.
Move from local experiments to Docker, async services, and cloud-based AI endpoints.
The certification validates that you have completed structured training in agentic AI, generative AI, tools, memory, evaluation, and deployment. It helps show employers that you have worked on practical AI workflows and not only studied the subject theoretically.
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 course begins with the basics of agentic AI, LLMs, and workflow logic before moving into advanced tools and deployment. That makes it suitable for learners who are new to AI but ready to study in a structured way.
Yes. The syllabus includes a research agent, a data analyst agent, and an end-to-end medical chatbot project. These projects help you practice prompts, tool calling, memory, evaluation, and deployment.
Yes. Placement support includes resume help, portfolio guidance, mock interviews, and career direction. The support is tied to the actual tools and projects you complete during training.
Yes, if they are ready to learn step by step. The course starts from the basics and explains concepts in a practical way, so learners from analytics, business, or other backgrounds can follow the training. The project work also helps build confidence.
Yes. The course is available in live online mode, so learners in Virginia can attend from home and still follow the same project-based training. You get mentor-led sessions, assignments, and support for the course flow.
The curriculum is structured across multiple modules, starting with foundational agentic AI and ending with production deployment. The generative AI track also includes project and deployment time. The exact batch pace can vary by mode.
You will work with OpenAI API, LangChain, Hugging Face API, Pinecone, LangGraph, AutoGen, CrewAI, FastAPI, Docker, and evaluation tools like LangSmith and Phoenix Arize. The course also covers function calling, guardrails, and vector database concepts. These tools are taught as part of the hands-on workflow, not as isolated topics.
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