Agentic AI Training Course in Rajkot from Uncodemy

Rajkot offers growing scope for Agentic AI engineers, because the city combines a strong industrial and manufacturing base with an emerging IT services and startup ecosystem. Both sectors are beginning to add AI agents, tool-calling workflows and automation to their products and internal operations.

Industrial hiring is concentrated around the Aji GIDC, Bhaktinagar and Metoda GIDC areas, where engineering, automotive and manufacturing firms are exploring AI for predictive maintenance, quality inspection and workflow automation. Alongside industry, Rajkot's IT services, agri-tech, healthcare-tech and education technology companies are adding roles in LLM applications, tool-calling agents and workflow automation.

When hiring freshers and career switchers, interviewers usually weigh three things above all. First, a firm grasp of LLM and agentic AI fundamentals — how agents plan, call tools and manage context. Second, performance in coding rounds, typically Python-based problem solving and API integration. Third, the depth of your project portfolio: candidates who can explain why they designed an agent a certain way, how they handled tool errors and how they deployed it tend to stand out. This course is structured around exactly these areas, with live sessions, graded projects and a deployed capstone.

The focused scope of this program means you can apply for a range of Agentic AI roles rather than a single job title. Because the curriculum covers LLM fundamentals, tool and function calling, agent architecture, RAG-augmented agents, LangChain, LangGraph, multi-agent systems, evaluation, security and deployment, you can match your applications to the kind of work you enjoy most and point to a relevant project for each role.

Over two to four years, growth usually comes from depth and ownership. Engineers who start with agent building often move into owning complete agent workflows, from prompt design to tool integration, evaluation, security and deployment. Many then specialise in areas such as multi-agent systems or agentic AI solution design, and progress towards senior Agentic AI engineer roles. With broader system design experience, some later move into solution architecture or technical leadership positions.

Agentic AI salaries in Rajkot depend heavily on the role you target, your practical skills and the type of employer. IT services companies, product firms and industrial-technology teams all hire AI talent, but they structure pay differently. The ranges below are the same indicative market ranges Uncodemy uses across its course pages; they show how compensation typically widens as responsibility moves from agent building to system design.

Sources reviewed: AmbitionBox, Glassdoor, Indeed and Uncodemy placement records. Reviewed: September 2026. These ranges are compiled by comparing publicly reported salary data for each role with internal placement information, and they are reviewed periodically so that they stay broadly in line with the market. They describe typical bands rather than individual offers. Actual packages in Rajkot depend on the employer's size and sector, the interview performance of the candidate, prior experience and the specific responsibilities of the role, so treat the table as a planning guide.

Agentic AI demand in Rajkot spans several industries, and Uncodemy's network of 850+ hiring partners reaches across many of them. The sectors below are where Rajkot-based Agentic AI skills are most commonly applied today:

• IT services: Delivery teams build LLM, tool-calling and agentic workflow solutions for clients from Rajkot's growing IT parks.
• Automotive & manufacturing tech: Agentic AI for predictive maintenance, workflow automation and connected-vehicle data analysis.
• Agri-tech: Agentic workflows for crop advisory, supply-chain automation and document processing.
• Healthcare-tech: Clinical text processing, patient data analytics and agent-assisted workflows under strict privacy rules.
• Education technology: Personalised learning agents, content automation and student support assistants.

Because every sector relies on the same core foundation of LLMs, tools and agent workflows, a focused Agentic AI program lets you apply across industries instead of committing to one early in your career.

Becoming an Agentic AI engineer is a sequence of skills, each building on the previous one. The seven steps below follow the order of this program, so you always know what comes next and why it matters.

1. Python & agent fundamentals: Learn syntax, functions, data structures and the core concepts behind agents, tools, memory and planning.
2. LLM fundamentals & APIs: Understand how large language models work, how to call them through APIs, and how to manage prompts and responses.
3. Prompt engineering & tool calling: Design effective prompts and give agents the ability to call functions and external tools safely.
4. Agent architecture & memory: Build agent loops, handle planning and task decomposition, and manage short-term and long-term memory.
5. RAG, LangChain & LangGraph: Ground agents in external knowledge and build stateful, graph-based agent workflows.
6. Multi-agent systems, security & guardrails: Coordinate multiple agents, evaluate outputs, and apply security and guardrails for safe deployment.
7. Deployment & capstone: Package agents into APIs with FastAPI, deploy them, and complete a documented industry capstone.

Timeline: 3–4 months of consistent study, live sessions and project work is typically enough to become interview-ready for entry-level Agentic AI roles.

Before choosing an Agentic AI course, compare the facts that affect your outcome: duration, total learning time, live teaching, tool coverage, project depth and support after training. The table sets out these factors for this program so you can compare them with any alternative.

Within Uncodemy's own catalogue, this Agentic AI course is the specialised program for autonomous agent development. The Artificial Intelligence course provides a broad foundation across ML, DL, NLP, CV and GenAI. LLM Engineering focuses narrowly on building and deploying applications powered by large language models, and RAG Engineering specialises in retrieval-grounded systems built on enterprise knowledge. Those courses suit learners who want a broad base or a different niche. If you already know you want to build autonomous, tool-using agents and multi-agent workflows, this program goes deeper into exactly those areas.

Uncodemy does not have a classroom in Rajkot, so Rajkot learners join this Agentic AI program fully live online. This is not a reduced version of the course. You attend the same batches, learn from the same trainers and follow the same 13-module curriculum as learners in Uncodemy's classroom programs. Sessions run in real time, so you can ask questions, share your screen for debugging help and discuss agent workflows with the trainer while the class is in progress.

Studying online also removes daily travel across the city, which matters for working professionals commuting to Aji GIDC, Bhaktinagar or Metoda GIDC. You can pick a weekday or weekend batch around your job and revise with session recordings.

If you would rather learn in a physical classroom and are able to travel, in-person training remains available at Uncodemy's Delhi and Noida centres. The fee and curriculum are the same in both modes.

Rajkot learners complete this Agentic AI course in 3–4 months. The program features 100+ live online sessions across 13 modules and wraps up with a 20-hour industry capstone. Both weekday and weekend batches are offered in Rajkot, so you can settle into a pace that fits your job or studies.

Rajkot participants are not expected to have prior agentic AI experience, since Python is taught from Module 2. Programming fundamentals with basic LLM or API familiarity help Rajkot learners move ahead faster; Module 3 builds up the LLM fundamentals needed.

Rajkot learners explore 10+ tools: Python, LangChain, LangGraph, OpenAI APIs, Hugging Face, FastAPI, vector databases, Jupyter Notebook, Git/GitHub and REST APIs. Every tool is used in practical assignments and projects rather than only being demonstrated.

Yes. Rajkot learners address LangChain and LangGraph in Module 10, covering stateful agent graphs and conditional routing, and multi-agent systems in Module 11 with supervisor and worker patterns, agent-to-agent communication and shared state coordination.

Rajkot learners handle Module 13, Deployment & Agentic AI Capstone, a 20-hour project. You define an industry-style problem, plan and build an agentic system, use security and guardrails, deploy it through FastAPI and document it on GitHub as a portfolio piece you can discuss in interviews.

For Rajkot learners, classes are live. The program provides 100+ instructor-led live sessions where you can raise questions instantly, and recordings are provided so you can revise topics or catch up on a session you could not attend.

Rajkot learners pay ₹19,500 + 18% GST, making a total of ₹23,010. The same fee applies in all modes and cities, whether you learn live online from Rajkot or in a classroom at Delhi or Noida, and there are no hidden charges.

Yes, Rajkot learners can access EMI starting at ₹3,835/month for 6 months.* This spreads the total fee of ₹23,010 across monthly payments. *EMI amount, tenure and eligibility may vary depending on the applicable payment or financing option.

Rajkot learners can request a demo session by submitting the enquiry form or calling our counsellors. Demo availability depends on the current batch schedule, and the team will share upcoming slots so you can experience the live teaching style before enrolling.

Yes, Rajkot learners receive Dedicated Career & Placement Assistance. This includes resume and LinkedIn guidance, mock interviews and opportunity sharing through a hiring network of 850+ companies. Assistance does not guarantee employment; outcomes depend on your skills and interview performance.

The course prepares Rajkot learners to apply for entry-level Agentic AI Engineer roles, which carry an indicative range of ₹4–8 LPA. Getting hired depends on your projects, interview performance and market conditions, and Uncodemy does not guarantee any specific role or salary.

In Rajkot, indicative ranges run from ₹4–8 LPA for Entry-Level Agentic AI Engineers to ₹15–28 LPA for Senior Agentic AI Engineers and ₹20–35 LPA for Agentic AI Solutions Architects. These are market ranges, not guaranteed outcomes; actual offers vary by role, skills, experience, employer and market conditions.

Rajkot learners can apply for AI Agent Developer, Agentic AI Engineer, AI Automation Engineer, LLM Application Developer, Multi-Agent Systems Engineer and Agentic AI Solutions Engineer roles. The focused curriculum lets you choose the direction that best matches your projects and interests.

Rajkot learners from any discipline qualify — graduates, working professionals, aspiring AI engineers and career changers. You need a laptop and a stable internet connection; programming fundamentals and basic LLM familiarity are helpful but are built up during the course.

No. For Rajkot learners, salary ranges are indicative market figures, placement support does not guarantee employment, and review counts reflect publicly available platform information that may change over time. They are shared for transparency to help you make an informed decision.

No. Rajkot learners join the course live online. Uncodemy's classroom centres are in Delhi (Laxmi Nagar/Shakarpur) and Noida (Sector 1), and anyone able to travel can choose in-person training at either location.

No. For Rajkot learners, it is an independent Uncodemy certificate, verifiable at certificate.uncodemy.com. Tools from these companies are taught in the course, but the certificate is not a vendor credential and implies no partnership or endorsement.