Learn practical Artificial Intelligence Training in Ranchi with a focus on Agentic AI, Generative AI, LangChain, LangGraph, OpenAI API, Hugging Face, Pinecone, FastAPI, Docker, and cloud deployment. You will build agent workflows, memory-based AI apps, tool-using assistants, and end-to-end projects that match real job roles.
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
Get Job with our Guaranteed Placement Support Program
9 LPA • AI Engineer
9 LPA • AI Engineer
12 LPA • Data Engineer
16 LPA • Data Engineer
4.3 LPA • AI Engineer
8.45 LPA • Computer Vision Engineer
6.3 LPA • AI Engineer
8.2 LPA • AI Engineer
Learning AI is only useful when you can show real work and talk about it clearly in interviews. Inventateq helps you turn the syllabus into a job-ready portfolio, with guided project practice, resume support, and interview preparation for AI and data-focused roles.
Artificial Intelligence roles in Ranchi are commonly linked with analytics, automation, chatbot development, and AI application support. Salary grows with hands-on project experience, deployment ability, and familiarity with tools like LangChain, OpenAI API, and vector databases.
Artificial Intelligence Average Salary by Experience
Artificial Intelligence roles in Ranchi are commonly linked with analytics, automation, chatbot development, and AI application support. Salary grows with hands-on project experience, deployment ability, and familiarity with tools like LangChain, OpenAI API, and vector databases.
Artificial Intelligence Average Salary by Experience
4.7/5 Google Rating | 1,432+ Verified Reviews
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By Google Reviews
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Success Result: Our students are competing at global levels. Watch their placement journey here.
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BTM Layout @ Inventateq - -
Genuine Reviews @ Inventateq - 25 LPA - 50LPA
Data Engineering @ Accenture - 12 LPA
Junior Accountant @ Fortis - 8 LPA
SQL Developer @ Wipro - 10 LPA
Salesforce Administrator @ Deloitte - 15 LPA
RPA Developer @ IBM - 20 LPA
Tableau Developer @ Genpact - 20 LPA
Talent Acquisition Executive @ Tech Mahindra - 12 LPA
Angular Developer @ Capgemini - 15 LPA
Data Analyst @ Amazon - 25 LPA
Java Developer @ Oracle - 25 LPA
CATIA Design Engineer @ TATA Motors - 20 LPA
AWS Solutions Architect @ Accenture - 25 LPA
Python Developer @ Mphasis - 15 LPA
QA Engineer @ HCLTech - 15 LPA
Cloud DevOps Engineer @ LTIMindtree - 18 LPA
Digital Marketer @ Google - 20 LPA
BTM Layout @ Inventateq - -
Genuine Reviews @ Inventateq - 25 LPA - 50LPA
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GOOGLE RATING
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REVIEWS
4.7/5 · 1,432+ Verified Reviews
Inventateq teaches Artificial Intelligence through the tools and workflows used in real projects, not just theory. The course follows a clear path from agent basics and prompt engineering to LangChain, memory, multi-agent systems, guardrails, evaluation, and cloud deployment.
We stand apart through our commitment to:
The live online Artificial Intelligence course is designed for learners in Ranchi who want flexibility without losing interaction. You attend mentor-led sessions, work on the same projects, and get support for assignments, tools, and deployment tasks from home.
Good for learners starting with AI, data, or automation and wanting a job-oriented path.
Useful for people moving into AI-enabled analytics, chatbot, or automation roles.
Fits developers who want to learn agents, LangChain, and AI app workflows.
Helps non-coders understand how AI tools support analysis and decision-making.
Best for learners who want structured training instead of scattered self-study.
Duration: 11 weeks of structured learning with theory, practice, and projects.
Mode: Available in classroom and live online formats.
Training Style: Mentor-led sessions with practical tasks after each major topic.
Project Focus: Built around agentic AI, generative AI, and deployment work.
No prior AI experience is required. You can start from the basics and move step by step.
Rated 4.9/5
Inventateq keeps the training practical from the first week. You learn the actual workflow behind modern AI apps, from prompt design and memory to framework selection, evaluation, and deployment.
You will not just read about agents and generative AI. You will build workflows, connect tools, manage memory, test agent behavior, and deploy working applications.
Learn how to create agents that plan, call tools, keep state, and complete tasks across multiple steps.
Work on chatbot projects using OpenAI, LangChain, vector databases, and retrieval workflows.
Understand how to add memory, guardrails, approvals, and error handling to AI systems.
Move projects beyond notebooks and into FastAPI, Docker, and cloud-based deployment setups.
Present your project choices, technical steps, and tools in a way recruiters can follow.
Prepare for job paths that connect Artificial Intelligence with analytics, business support, and automation.
The certification shows that you completed structured training in agentic AI, generative AI, and AI application development. It helps employers see that you have worked with the tools, workflows, and deployment steps expected in practical entry-level 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 starts from the basics of agentic AI and the evolution from NLP to LLMs, chatbots, and agents. You move step by step into prompts, tools, memory, frameworks, and deployment. If you are new to AI, the structure is designed to make the learning path manageable.
Yes, the syllabus includes hands-on work such as building a research agent, porting workflows into LangGraph, and creating a data analyst agent. You also practice deployment with FastAPI and cloud platforms. The course is built around doing the work, not just reading concepts.
Yes, placement support is part of the course approach. You get help with resume preparation, mock interviews, and project presentation so you can apply for entry-level AI and analytics roles. The support is aimed at making you interview-ready, not just course-complete.
Yes, non-technical learners can join if they want a structured introduction to AI and its practical use cases. The course covers core concepts clearly and gradually adds tools, workflows, and projects. You may need to spend extra time on practice, but the path is still accessible.
Yes, the course is available in a live online format, so you can attend from Ranchi without traveling. You still get mentor-led sessions, assignments, and project support. This works well if you want flexibility but still need live interaction.
The core training is structured across 11 weeks, with a final focus on production deployment. There is also time for projects and buffer support depending on the batch plan. This makes the course long enough to cover the tools properly without dragging on.
The syllabus includes OpenAI API, LangChain, LangGraph, AutoGen, CrewAI, Hugging Face, Pinecone, FastAPI, Docker, and cloud deployment tools. It also covers evaluation and observability concepts like LangSmith and Phoenix Arize. These tools are chosen because they match the project workflow and current AI application development.
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