Learn Artificial Intelligence in Nagpur with a practical path through Agentic AI, Generative AI, LangChain, Hugging Face API, vector databases, Pinecone, OpenAI API, and deployment tools like FastAPI and Docker. You will build working agents, chatbots, and end-to-end AI projects instead of only studying theory.
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
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Learning AI is useful only when you can apply it in real roles. Inventateq focuses on practical preparation for Artificial Intelligence jobs in Nagpur by connecting the course work to the roles employers actually hire for, such as AI developer, data analyst, and business intelligence roles.
AI, automation, analytics, and chatbot roles are opening across product teams, service companies, data teams, and IT consulting firms in Nagpur. Salary usually grows with experience, project depth, and how well you can build and deploy practical AI systems.
Artificial Intelligence Average Salary by Experience
AI, automation, analytics, and chatbot roles are opening across product teams, service companies, data teams, and IT consulting firms in Nagpur. Salary usually grows with experience, project depth, and how well you can build and deploy practical AI systems.
Artificial Intelligence Average Salary by Experience
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Inventateq teaches Artificial Intelligence through working modules, not passive lectures. The syllabus moves from the evolution of NLP and LLMs into prompt engineering, tool calling, memory, agent frameworks, multi-agent systems, guardrails, evaluation, and production deployment so learners can follow a real build process.
We stand apart through our commitment to:
The live online Artificial Intelligence experience from Nagpur gives you the same structured syllabus with the convenience of remote attendance. Sessions stay practical and trainer-led, with demonstrations, project work, and doubt clarification carried out in a live format.
Good for fresh graduates who want a practical start in Artificial Intelligence, data, and automation roles.
Useful for developers, analysts, and IT professionals who want to move into AI agent and generative AI work.
Fits non-AI learners who want structured training and project practice instead of self-study confusion.
Helps learners who already know data work and want to add AI, LangChain, and deployment skills.
Suitable for people who want to build chatbots, agents, and end-to-end AI applications in Nagpur.
Duration: Structured across multiple weeks with module-based learning
Mode: Classroom and live online training
Format: Trainer-led theory with practical sessions
Projects: Includes guided hands-on AI builds
Suitable for beginners and professionals who want a practical AI learning path.
Rated 4.9/5
Inventateq keeps the training practical and job-focused, with a syllabus that moves from core concepts to real implementation. Learners spend time on agent design, structured prompting, memory, frameworks, evaluation, and deployment so the course stays useful beyond theory.
This course gives you direct practice with AI tools, agent workflows, chatbot builds, and deployment steps. You finish with clearer project experience and a better understanding of how AI systems are built and evaluated.
Learn how to design agents that reason, act, use tools, and manage tasks across steps. The course walks you through research agents, data analyst agents, and multi-agent patterns.
Move from API use to full application builds with OpenAI, LangChain, Hugging Face, and vector databases. You also see how a medical chatbot can be built and deployed.
Use system prompts, CoT, ToT, JSON mode, and function calling to make prompts more reliable. This is useful when the output must be structured and stable.
Work with short-term, long-term, semantic, and episodic memory concepts. You also learn how RAG and vector search support better AI responses.
Learn how to package and deploy AI systems using FastAPI, Docker, AsyncIO, and cloud platforms. This helps bridge the gap between learning and production use.
The course connects training outcomes to AI developer, data analyst, and analytics roles. That makes it easier to explain your skills during interviews and career discussions.
The certification shows that you completed practical training in Agentic AI, Generative AI, and deployment-focused workflows. It helps employers see that you have worked with real tools, not only learned concepts.
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.
Yes. The syllabus starts with the evolution from NLP to LLMs and agents, so the learning path is organized from basics to advanced topics. Beginners should still be ready to practice consistently, but they do not need prior AI project experience to start.
Yes. The course includes practical work on research agents, data analyst agents, Generative AI projects, and chatbot development. You also get deployment-focused practice so the work is not limited to theory.
Yes. Placement support includes resume help, portfolio guidance, mock interviews, and career mentoring. The support is designed to help you present your skills for AI, data, and analytics roles.
You can join if you are willing to learn step by step and practice the tools regularly. The course is practical and the trainers explain the modules in a guided way, but learners from non-technical backgrounds may need more revision on coding and data concepts. The structure still makes the subject easier to approach than self-learning alone.
Yes. Live online training is available for learners who want to attend from home or from another city while still following the same practical syllabus. You get trainer-led sessions, project guidance, and module-based learning.
The course is organized into multiple weekly modules plus additional project and buffer time. That gives you enough room to understand the concepts, practice the tools, and complete the guided projects. The exact pace can vary by batch mode and learner progress.
The course works with OpenAI API, LangChain, Hugging Face, Pinecone, LangGraph, AutoGen, CrewAI, LangSmith, Phoenix Arize, FastAPI, Docker, AsyncIO, Playwright, and Selenium. These tools are chosen because they support practical AI agent and chatbot development. You also learn the idea behind memory, vector databases, and deployment workflows.
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