Uncodemy's Agentic AI course for Hubballi-Dharwad is an instructor-led program running three to four months. It covers LLM fundamentals, tool and function calling, AI agent architecture, and hands-on exposure to LangChain, LangGraph, multi-agent systems, and agent deployment. Hubballi-Dharwad learners attend live online classes; classroom batches are available at the Delhi and Noida centres for travellers. Pricing is ₹19,500 + GST, i.e., ₹23,010 in total.
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Career and placement assistance through our growing network of companies, recruiters and hiring organizations across India.
6 × ₹3,835 = ₹23,010 — matches the ₹23,010 total.
This program gives finishing learners hands-on capabilities in AI agent development, tool calling, workflows, LLM applications and automation. These skills assist applications for designations like AI Agent Developer, Agentic AI Engineer and AI Automation Engineer.
Placement information for Hubballi-Dharwad learners is refreshed regularly — check verified outcomes at uncodemy.com/placement.
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Placed at: Hexalog
Placed at: SmartStudy
Agentic AI refers to AI systems built around large language models that can plan tasks, reason through steps, call tools or functions, and perform multiple actions toward a defined goal. Unlike a single-turn chatbot that usually replies to a prompt, an agentic system can coordinate actions, employ external information, maintain context, and execute a workflow across several stages.
An Agentic AI engineer is absorbed in designing and developing systems that can complete multi-step tasks with controlled autonomy. Daily work can include designing agent architectures, implementing tool and function calling, managing memory and context, creating multi-agent workflows with LangChain or LangGraph, evaluating responses, applying security and guardrails, and deploying resilient agents into production environments.
Here is how Uncodemy's Agentic AI program sits next to its two related specialisations.
| Aspect | Agentic AI | LLM Engineering | RAG Engineering |
|---|---|---|---|
| Core focus | Building autonomous agents with tool calling, workflows and multi-agent systems | Building, fine-tuning & deploying LLM-powered applications | Building retrieval-grounded AI systems on enterprise knowledge |
| Coding depth | High | High | High |
| Typical entry salary | ₹4–8 LPA (Entry-Level Agentic AI Engineer, per this sheet) | ₹6–10 LPA (per LLM Engineering course sheet) | ₹5–9 LPA (per RAG Engineering course sheet) |
| Uncodemy program duration | 3–4 months | 5–6 months | 5–6 months |
This Agentic AI program follows an instructor-led structure across three to four months, offering 100+ live sessions, 160+ hours of learning and 13 modules. Learners advance from agent fundamentals and Python through LLM fundamentals, API integration, prompt engineering, tool and function calling, agent architecture, memory and context management, RAG-augmented agents, LangChain and LangGraph, multi-agent systems, evaluation, security, guardrails, deployment and the final capstone. Practical tools and projects are part of the offering, delivered live online for Hubballi-Dharwad learners, while classroom learning stays open at Uncodemy's Delhi and Noida centres.
Programming fundamentals are helpful but the program builds the required Python foundation from Module 2 onward. Basic LLM or API familiarity is useful but not mandatory for understanding the course progression because these concepts are developed in Module 3. Learners should have a laptop and stable internet connection for live online classes, coding exercises, projects and assignments.
Pick the weekday or weekend track that suits your schedule; seats are confirmed on enrolment.
| Date | Time | Trainer | Seats Left |
|---|---|---|---|
| 16 Oct | 07:30 PM – 08:30 PM | Mr. Irshad | 01 Seat |
| 22 Oct | 02:00 PM – 03:00 PM | Mr. Upendra Kumar Tiwari | 02 Seat |
| 26 Oct | 10:30 AM – 11:30 AM | Mr. Irshad | 01 Seat |
| 28 Oct | 12:00 PM – 01:00 PM | Mr. Upendra Kumar Tiwari | 02 Seat |
| Date | Time | Trainer | Seats Left |
|---|---|---|---|
| 27Oct | 03:00 PM – 05:00 PM | Mr. Irshad | 02 Seat |
Illustrative example only — your exact weekday or weekend timetable (IST) is shared when you enrol.
This Agentic AI program follows an instructor-led structure across three to four months, offering 100+ live sessions, 160+ hours of learning and 13 modules. Learners advance from agent fundamentals and Python through LLM fundamentals, API integration, prompt engineering, tool and function calling, agent architecture, memory and context management, RAG-augmented agents, LangChain and LangGraph, multi-agent systems, evaluation, security, guardrails, deployment and the final capstone. Practical tools and projects are part of the offering, delivered live online for Hubballi-Dharwad learners, while classroom learning stays open at Uncodemy's Delhi and Noida centres.
| Module | Hours | Tools |
|---|---|---|
| 1. Agent Fundamentals | 10 | Jupyter Notebook |
| 2. Python for Agentic AI | 15 | Python, Jupyter Notebook |
| 3. LLM Fundamentals | 12 | OpenAI APIs, Hugging Face |
| 4. API Integration | 12 | Python, OpenAI APIs, REST |
| 5. Prompt Engineering | 12 | OpenAI APIs, Hugging Face |
| 6. Tool & Function Calling | 12 | OpenAI APIs, Python |
| 7. Agent Architecture | 12 | LangChain, Python |
| 8. Memory & Context Management | 10 | Vector stores, LangChain |
| 9. RAG-Augmented Agents | 12 | LangChain, vector databases |
| 10. LangChain & LangGraph | 12 | LangChain, LangGraph |
| 11. Multi-Agent Systems | 12 | LangGraph, LangChain |
| 12. Evaluation, Security & Guardrails | 10 | Python, LangChain |
| 13. Deployment & Agentic AI Capstone | 20 | FastAPI, Git/GitHub, LangChain |
| Total | 160+ Hours | |
Each project comes straight from a curriculum module, ending with the Agentic AI capstone.
Curriculum & Technical Reviewer · AI Trainer
8+ years across AI, ML and analytics delivery. Reviews and signs off the curriculum on this page so content stays technically accurate and current.
The curriculum has been designed and technically reviewed by expert industry professional Mr. Irshad Khan, with additional review by Mr. Upendra Kumar Tiwari.
After the Uncodemy Agentic AI program is successfully completed by learners, the Uncodemy Agentic AI Program Certificate is given to them. The certificate reflects the program name, duration, tools covered and completion date, together with a verification reference where the applicable verification mechanism is accessible.
Bound with the practical learning completed during the program — hands-on agent-building projects, multi-agent system workflows and the Agentic AI capstone project — is the certification. This provides learners with documented evidence of completing the prescribed training and practical work.
The Agentic AI course for Hubballi-Dharwad learners provided by Uncodemy includes a verified Uncodemy Agentic AI Program Certificate that can be verified online through the official Uncodemy Certificate Portal.
Uncodemy Certificate VerificationOnline Certificate Verification & Download certificate.uncodemy.com_2.webp)
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Uncodemy Edutech Pvt. Ltd. is a career-focused IT training institute that delivers structured technology education. Its 14+ years of training experience back classroom programs at the Delhi and Noida centres, while live online classes enable learners across India, including Hubballi-Dharwad, to join remotely.
In this Agentic AI program, learners work toward AI agents capable of tool calling, multi-agent workflows and RAG-augmented interactions. Production-oriented agent deployment is part of the learning path as well, which ends with an Agentic AI capstone project that assembles the major concepts into practical work.
Alongside instructor-led sessions are assignments, practical projects, interview preparation and career support. Career-support processes, applicable policies and eligibility conditions are explained before enrolment so learners understand what assistance is included rather than taking it as a guarantee of employment.
Other courses for Hubballi-Dharwad learners: Artificial Intelligence, LLM Engineering, RAG Engineering, AI Security, and Generative AI courses for Hubballi-Dharwad learners
The people who actually teach this course
Uncodemy's trainer team conducts every live session. The institute engages 30+ Industry Trainers & Mentors bringing 10+ Years of Corporate Training Experience* on average, so lessons mirror how AI is practised in real companies.
Uncodemy separates two roles: trainers deliver the sessions, and domain reviewers confirm that the curriculum is technically accurate and current. For this Agentic AI program, Mr. Irshad reviews the curriculum and technical content, with additional review by Mr. Upendra Kumar Tiwari, offering learners an independent check on what is taught.
To let you check their background before you join, every trainer and reviewer is published by name with a profile link.
Senior Data Science & AI Trainer
Expertise15+ years of industry experience building production machine learning systems for retail, telecom and consulting teams.
Modelling security breaches in iOS apps, dormant customer prediction and factor analysis, last-mile delivery optimisation, and credit card fraud detection.
Data Analytics & AI Trainer
ExpertisePython · SQL · Machine Learning · LangChain · Artificial Intelligence · Deep Learning · Power BI · Agentic AI
8+ years across consulting and public-sector analytics, with deep hands-on work in AI and MLOps delivery.
Built an OCR model, a disease-prediction model, and a fraud-control model deployed across every Indian state under the Ministry of Health & Welfare.
Data Analytics & AI Trainer
ExpertisePython · ML · DL · NLP · Agentic AI · LangChain · Tableau · SQL
7+ years turning aviation and enterprise data into forecasting models, dashboards and AI assistants.
AI agent chat/voice bot, AI-driven data analysis, a sales-forecasting ML model, NPS data model evaluation, and a face-recognition model for biometrics.
Data Analytics Trainer
ExpertisePython · SQL · Agentic AI · Power BI · Tableau · ML · DL · NLP · Time Series · Prompt Engineering · Chatbots
5+ years in logistics and consumer-brand analytics, with a strong focus on time series, NLP and applied automation.
Speech-to-text using core NLP (T2S), talent acquisition research, and product launch & CMS work on keventers.com using Sparktech.
Data Analytics Trainer
ExpertiseAdvanced Excel · SQL · Power BI · Tableau · Python · Data Visualisation · Statistics
Trainer for the analytics and business intelligence track at Uncodemy, working with learners on Excel, SQL and BI tooling from first principles to interview-ready projects.
Guides classroom capstones on sales and customer dashboards, KPI reporting and end-to-end data cleaning workflows.
Data Analytics Trainer
Expertise
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
CEO & Founder
ExpertiseCEO & Founder of GvCloud Secure and Uncodemy with 14+ years of professional experience building scalable web, mobile and AI-driven solutions for clients across India, USA, UK, Canada, Australia and Singapore.
Leads technology strategy, scalable web and mobile solutions, AI-driven products and EdTech initiatives across Uncodemy and GvCloud Secure.
Join a live online batch from anywhere in Hubballi-Dharwad and learn LLM fundamentals, tool calling, agent architecture, LangChain, LangGraph and multi-agent systems across 3–4 months. Talk to our counsellors about batch timings, EMI options and career support before you commit.
A step-by-step view of the role-wise salary ranges on this page, from first agentic AI role to architect.
Hubballi-Dharwad offers growing scope for Agentic AI engineers, because the twin city combines a strong industrial and manufacturing base with an emerging IT services and startup ecosystem, alongside Dharwad's established educational institutions. 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 Gokul Road and Tarihal industrial areas, where engineering, automotive and manufacturing firms are exploring AI for predictive maintenance, quality inspection and workflow automation. Alongside industry, Hubballi-Dharwad's IT services, agri-tech, manufacturing-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.
| Role | Core Tools |
|---|---|
| AI Agent Developer | Python, LangChain, OpenAI APIs, FastAPI |
| Agentic AI Engineer | Python, LangGraph, LangChain, vector databases |
| AI Automation Engineer | Python, LangChain, OpenAI APIs, REST APIs |
| LLM Application Developer | Python, OpenAI APIs, Hugging Face, FastAPI |
| Multi-Agent Systems Engineer | LangGraph, LangChain, Python |
| Agentic AI Solutions Engineer | LangChain, LangGraph, FastAPI, Git/GitHub |
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 Hubballi-Dharwad 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.
| Role | Salary Range |
|---|---|
| Entry-Level Agentic AI Engineer | ₹4–8 LPA |
| AI Agent Developer | ₹6–12 LPA |
| Agentic AI Engineer | ₹8–16 LPA |
| AI Automation Engineer | ₹7–18 LPA |
| Senior Agentic AI Engineer | ₹15–28 LPA |
| Agentic AI Solutions Architect | ₹20–35 LPA |
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 Hubballi-Dharwad 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 Hubballi-Dharwad spans several industries, and Uncodemy's network of 850+ hiring partners reaches across many of them. The sectors below are where Hubballi-Dharwad-based Agentic AI skills are most commonly applied today:
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.
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.
| Factor | This Program |
|---|---|
| Duration | 3–4 months |
| Learning hours | 160+ hours |
| Live sessions | 100+ |
| Tools | 10+ |
| Capstone | 20-hour Industry project |
| Career support | Dedicated Career & Placement Assistance |
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 Hubballi-Dharwad, so Hubballi-Dharwad 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 twin city, which matters for working professionals commuting to Gokul Road, Tarihal or Vidyanagar. 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.
| If you want... | Recommend |
|---|---|
| To build autonomous, tool-using AI agents | This program |
| To specialise in multi-agent workflows and agent deployment | This program |
| A broad AI/ML foundation instead | Consider the Artificial Intelligence course |
| Narrow LLM application development only | Consider the LLM Engineering course |
| A narrow retrieval-system specialisation | Consider the RAG Engineering course |
Hubballi-Dharwad learners complete this Agentic AI course within 3–4 months. It carries 100+ live online sessions spread across 13 modules and finishes with a 20-hour industry capstone. Weekday and weekend batches are both open for Hubballi-Dharwad learners, letting you choose a pace that suits your work or study schedule.
Hubballi-Dharwad participants do not need prior agentic AI experience, and Python begins from Module 2. Familiarity with programming basics plus comfort in basic maths and statistics help Hubballi-Dharwad learners progress faster; Module 3 builds the LLM fundamentals required.
Hubballi-Dharwad learners study 10+ Agentic AI tools: Python, LangChain, LangGraph, OpenAI APIs, Hugging Face, FastAPI, vector databases, Jupyter Notebook, Git/GitHub and REST APIs. Each tool is applied through hands-on assignments and projects rather than being only demonstrated.
Yes. Hubballi-Dharwad learners find LangChain and LangGraph in Module 10, covering stateful agent graphs, conditional routing and cycles, and Multi-Agent Systems in Module 11, covering supervisor/worker patterns, agent-to-agent communication and shared state coordination. Each module includes practical work using LangChain and LangGraph.
Hubballi-Dharwad learners take on Module 13, Deployment & Agentic AI Capstone, a 20-hour project. You scope an industry-style problem, plan and build an agentic system, apply security and guardrails, deploy it via FastAPI and document it on GitHub as a portfolio piece you can discuss in interviews.
For Hubballi-Dharwad learners, sessions run live. The program delivers 100+ instructor-led live sessions where you can ask questions in real time, and recordings are provided so you can revise topics or catch up on a session you missed.
Hubballi-Dharwad learners pay ₹19,500 + 18% GST, bringing the total to ₹23,010. The same fee holds across all modes and cities, whether you learn live online from Hubballi-Dharwad or join a classroom at Delhi or Noida, with no hidden charges.
Yes, Hubballi-Dharwad learners can begin EMI from ₹3,835/month for 6 months.* This splits the ₹23,010 total into monthly instalments. *EMI amount, tenure and eligibility may vary depending on the applicable payment or financing option.
Hubballi-Dharwad learners may request a demo 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 sample the live teaching style before enrolling.
Yes, Hubballi-Dharwad learners receive Dedicated Career & Placement Assistance. It covers 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 Hubballi-Dharwad 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 Hubballi-Dharwad, 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.
Hubballi-Dharwad 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.
Hubballi-Dharwad 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 Hubballi-Dharwad 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. Hubballi-Dharwad 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 Hubballi-Dharwad 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.
The Agentic AI course is delivered fully live online to learners in Hubballi-Dharwad, so no travel is needed to attend. If you would like to visit Uncodemy in person or prefer classroom training, our two physical training centres are located in Delhi and Noida.
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