Learn Artificial Intelligence in Mumbai with a practical focus on agentic AI, generative AI, LangChain, OpenAI API, Hugging Face, Pinecone, and deployment workflows. You will build prompt-driven agents, memory-based systems, and end-to-end AI projects that match the tools listed in the syllabus.
14,200+ (Placed)
Freshers to IT
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Non-IT to Tech
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Learning AI is only useful when you can show real work and explain it clearly in interviews. Inventateq supports you with project-based training, resume preparation, and interview practice so you can apply for AI and analytics roles in Mumbai with confidence.
Mumbai hiring for AI skills comes from startups, product teams, analytics groups, and companies building automation and chatbot workflows. Salaries rise with experience, especially when you can show agent design, deployment, and tool integration.
Artificial Intelligence Average Salary by Experience
Mumbai hiring for AI skills comes from startups, product teams, analytics groups, and companies building automation and chatbot workflows. Salaries rise with experience, especially when you can show agent design, deployment, and tool integration.
Artificial Intelligence Average Salary by Experience
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Inventateq teaches Artificial Intelligence with a practical structure built around the syllabus in this row: agentic AI, prompt engineering, tools and function calling, memory, frameworks, multi-agent systems, evaluation, and deployment. The course is not limited to theory. You work through real workflows in LangChain, LangGraph, AutoGen, CrewAI, OpenAI API, Pinecone, Hugging Face, Docker, FastAPI, and cloud deployment.
We stand apart through our commitment to:
Live online Artificial Intelligence training is available for learners in Mumbai who want flexibility without losing hands-on guidance. Sessions stay practical, with screen-sharing, project walkthroughs, and mentor support for assignments and deployment tasks.
Good for learners starting an AI career and needing a structured path from prompts to deployment.
Useful for developers, analysts, and testers who want to move into AI and agent workflows.
Fits people already using Python, SQL, or dashboards who want AI project skills.
Suitable if you can follow logical steps and want a practical introduction to AI tools.
Helps candidates build portfolio projects for AI, chatbot, and business automation roles.
Mode: Offline classroom and live online options
Learning style: Practical, project-based training
Pace: Structured week-wise progression through the syllabus
Support: Trainer guidance during projects and assignments
You can start without advanced AI experience. The course is designed to build your skills step by step.
Rated 4.9/5
Inventateq focuses on practical AI training that follows the flow of real project work: understand the model, connect tools, manage memory, test behavior, and deploy. The teaching style is direct and useful, so learners leave with something they can explain and show.
By the end of the course, you will have practical AI project experience, not just notes and definitions. You will know how to structure prompts, connect tools, manage memory, test agents, and deploy working applications.
You practice creating agents that can reason, act, call tools, and complete tasks. The syllabus includes research agents, data analyst agents, and multi-agent systems.
You work through generative AI projects, chatbot creation, deployment, vector databases, and cloud-based delivery. This gives you portfolio material you can discuss in interviews.
Training includes OpenAI API, LangChain, Hugging Face, Pinecone, LangGraph, AutoGen, CrewAI, FastAPI, and Docker. That makes your learning practical and job-focused.
You learn how long-term memory, RAG, tracing, and observability affect AI systems. This is useful when you need to explain why an agent works or fails.
You gain the language to explain architecture, workflows, prompt logic, and deployment choices clearly. That helps in Mumbai interviews for AI and analytics roles.
The course includes deployment steps for cloud and API-based AI applications. You do not stop at prototypes; you learn how to package and present them.
The certification validates that you completed practical AI training covering agentic systems, generative AI workflows, and deployment basics. It helps show employers that you have worked with the tools and project structure used in modern AI roles.
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 is designed to build understanding from the basics of NLP, LLMs, and agents before moving into workflows and deployment. You do not need to arrive with advanced AI experience. You should be comfortable learning step by step and practicing the tools as the course progresses.
Yes, the syllabus is project-led and includes research agents, data analyst agents, chatbot work, and deployment tasks. You also practice prompt design, function calling, memory, guardrails, and evaluation. That means the course gives you more than theory.
Yes, placement support is included through resume help, mock interviews, and guidance on how to present your projects. The support is tied to the roles mentioned in the course, such as AI Analyst, AI Engineer, and Generative AI Developer. The aim is to help you prepare for interviews with a clear portfolio and explanation of your work.
Yes, non-technical learners can join if they are ready to follow the structured training and practice consistently. The course explains concepts in a practical way and gradually introduces tools, workflows, and deployment steps. A basic comfort with computers and logical thinking is enough to start.
Yes, live online training is available for learners in Mumbai who want flexibility. The online format still includes mentor interaction, project walkthroughs, and support for assignments. It is a good choice if you want to learn without commuting to the classroom every day.
The syllabus is organized across 11 weeks, followed by buffer time in the combined course outline. The pace covers introduction, prompting, tools, memory, frameworks, multi-agent systems, safety, evaluation, advanced architectures, and deployment. This structure helps you learn in a sequence that makes sense.
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