Agentic AI Training Course in Faridabad from Uncodemy

Faridabad is opening up substantial opportunities for Agentic AI engineers, as the city simultaneously nurtures a deep industrial and manufacturing foundation and a budding IT services and startup ecosystem. Both of these realms are progressively embedding AI agents, tool-calling pipelines and automation into their products and back-office operations.

Industrial recruitment is clustered around Sector 59, IMT Faridabad and the Neharpar belt, where engineering, automotive and manufacturing firms are experimenting with AI for predictive maintenance, quality inspection and workflow automation. Complementing this industrial activity, Faridabad's IT services, agri-tech, healthcare-tech and education technology companies are opening positions around LLM applications, tool-calling agents and workflow automation.

When evaluating freshers and career switchers, recruiters typically weigh three factors most heavily. First, a strong grip on LLM and agentic AI principles — how agents plan, invoke tools and maintain context. Second, how well you perform in coding rounds, which usually involve Python-based problem solving and API work. Third, the calibre of your project portfolio: applicants who can justify why they structured an agent in a particular way, how they resolved tool failures, and how they shipped it are the ones who stand out. This course is designed around those very priorities, using live sessions, assessed projects and a deployed capstone.

Because this program keeps a tight, purposeful focus, you can chase a whole range of Agentic AI positions instead of being bound to a single title. As the syllabus spans LLM fundamentals, tool and function calling, agent architecture, RAG-augmented agents, LangChain, LangGraph, multi-agent systems, evaluation, security and deployment, you can tailor your applications around the work you find most engaging and cite a matching project for each opening.

Over a two-to-four-year window, progress tends to flow from deepening expertise and taking ownership. Engineers who start by constructing individual agents often move into running whole agent workflows, from prompt design to tool integration, evaluation, security and deployment. Many then build specialist focus in areas such as multi-agent systems or agentic AI solution design, and step into senior Agentic AI engineer roles. With wider system design exposure, some later transition into solution architecture or technical leadership.

Agentic AI pay in Faridabad is influenced heavily by the role you target, your practical abilities and the nature of your employer. IT services firms, product organisations and industrial-technology teams all recruit AI talent, yet each one designs its salary structure differently. The bands listed below mirror the indicative market ranges Uncodemy publishes across its course pages; they show how remuneration typically expands as responsibility moves from agent building toward system design.

Sources consulted: AmbitionBox, Glassdoor, Indeed and Uncodemy placement records. Reviewed: October 2026. These bands are put together by cross-referencing publicly reported salary figures for each role with internal placement data, and they are refreshed periodically to stay broadly aligned with the market. They describe typical bands rather than specific offers. Actual packages in Faridabad hinge on the employer's size and sector, the candidate's interview performance, prior experience and the exact duties attached to the role, so treat the table as a planning aid.

Agentic AI demand in Faridabad reaches across a diverse range of industries, and Uncodemy's network of 850+ hiring partners covers many of them. The sectors listed below are where Faridabad-based Agentic AI skills are most commonly put to use today:

• IT services: Delivery teams develop LLM, tool-calling and agentic workflow solutions for clients from Faridabad's expanding 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.

Since every sector rests on the same core foundation of LLMs, tools and agent workflows, a focused Agentic AI program lets you apply your skills across industries instead of locking into one early in your career.

Becoming an Agentic AI engineer is a sequence of skills, each one building upon the previous. The seven stages 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 committing to an Agentic AI course, weigh the facts that shape your outcome: duration, total learning time, live teaching, tool coverage, project depth and post-training support. The table lays out these factors for this program so you can compare them against 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 operate a classroom in Faridabad, so learners from this city join the Agentic AI program wholly live online. This is not a slimmed-down 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 Sector 59, IMT Faridabad or Neharpar. 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.

Faridabad 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 Faridabad, so you can settle into a pace that fits your job or studies.

Faridabad 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 Faridabad learners move ahead faster; Module 3 builds up the LLM fundamentals needed.

Faridabad 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. Faridabad 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.

Faridabad 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 Faridabad 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.

Faridabad 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 Faridabad or in a classroom at Delhi or Noida, and there are no hidden charges.

Yes, Faridabad 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.

Faridabad 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, Faridabad 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 Faridabad 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 Faridabad, 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.

Faridabad 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.

Faridabad 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 Faridabad 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. Faridabad 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 Faridabad 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.