Uncodemy offers an Agentic AI certification in Bengaluru that spans three to four months and is taught by live instructors. The curriculum walks you through the basics of large language models, how to enable tool and function calling, the design of AI agent frameworks, plus hands-on work with LangChain, LangGraph, multi-agent setups, and deploying agents in real environments. Learners in Bengaluru attend sessions through live online classes, while those willing to commute can join in-person batches at Uncodemy's Delhi and Noida campuses. The course is priced at ₹19,500 plus GST, bringing the total to ₹23,010.
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5/5Career and placement assistance through our growing network of companies, recruiters and hiring organizations across India.
6 × ₹3,835 = ₹23,010 — matches the total fee.
Learners who complete this program leave with working skills in LLM fundamentals, tool and function calling, agent architecture, LangChain, LangGraph, multi-agent systems, RAG-augmented agents, evaluation, security, guardrails and agent deployment, supported by a portfolio of projects and an Agentic AI capstone. These skills align with roles such as AI Agent Developer, Agentic AI Engineer and AI Automation Engineer.
Placement records for Bengaluru learners are updated regularly — view verified outcomes at uncodemy.com/placement.
Placed at: Allsoft Solutions
Placed at: SmartStudy
Placed at: Allsoft Solutions
Placed at: SmartStudy
Agentic AI describes AI systems constructed around large language models capable of planning tasks, reasoning through steps, invoking tools or functions, and carrying out multiple actions toward a set objective. Rather than a single-turn chatbot that mainly answers a prompt, an agentic system can coordinate actions, pull in external information, retain context, and run a workflow across multiple stages.
An Agentic AI engineer builds and develops systems able to handle multi-step tasks with controlled autonomy. Day-to-day work may involve 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 dependable agents into production environments.
Here is how Uncodemy's Agentic AI program sits next to its other specialisations.
| Aspect | Agentic AI | LLM Engineering | RAG Engineering |
|---|---|---|---|
| Core focus | Building autonomous AI agents with tool calling, multi-agent workflows & deployment | Building, fine-tuning & deploying LLM-powered applications | Building retrieval-grounded AI systems on enterprise knowledge |
| Coding depth | High | High | High |
| Typical entry salary | ₹6–10 LPA (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 |
The Agentic AI program follows a three-to-four-month instructor-led path featuring over 100 live sessions, more than 160 learning hours and 13 modules. Learners advance from agent basics and Python into LLM fundamentals, API integration, prompt engineering, tool and function calling, agent architecture, memory and context handling, RAG-augmented agents, LangChain and LangGraph, multi-agent systems, evaluation, security, guardrails, deployment and the closing capstone. Practical tools and projects are part of the curriculum, delivered live online for Bengaluru 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. Irshadi | 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.
The Agentic AI program follows a three-to-four-month instructor-led path featuring over 100 live sessions, more than 160 learning hours and 13 modules. Learners advance from agent basics and Python into LLM fundamentals, API integration, prompt engineering, tool and function calling, agent architecture, memory and context handling, RAG-augmented agents, LangChain and LangGraph, multi-agent systems, evaluation, security, guardrails, deployment and the closing capstone. Practical tools and projects are part of the curriculum, delivered live online for Bengaluru learners, while classroom learning stays open at Uncodemy's Delhi and Noida centres.
| Module | Hours | Tools |
|---|---|---|
| 1. Agentic AI Fundamentals | 10 | Jupyter Notebook |
| 2. Python for Agentic AI | 12 | Python, Requests, Jupyter Notebook |
| 3. Large Language Models (LLMs) | 15 | OpenAI APIs, Hugging Face |
| 4. API Integration & LLM Calls | 10 | OpenAI APIs, Hugging Face |
| 5. Prompt Engineering for Agents | 10 | OpenAI APIs, Python |
| 6. Agent Architecture | 15 | Python, OpenAI APIs |
| 7. Tool & Function Calling | 15 | Python, OpenAI APIs |
| 8. Memory & Context Handling | 10 | Vector DB, Python |
| 9. RAG-Augmented Agents | 12 | LangChain, Vector DB, Hugging Face |
| 10. LangChain & LangGraph | 15 | LangChain, LangGraph, LangSmith |
| 11. Multi-Agent Systems | 12 | LangGraph, Python |
| 12. Evaluation, Security & Deployment | 15 | FastAPI, OpenAI APIs, Guardrails |
| 13. Agentic AI Capstone | 25 | Full stack of course tools |
| Total | 160+ Hours | |
Each project comes straight from a curriculum module, ending with the industry 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 successfully finishing the Uncodemy Agentic AI program, learners are awarded the Uncodemy Agentic AI Program Certificate. The certificate mentions the program name, duration, tools covered and completion date, along with a verification reference wherever the applicable verification mechanism is available.
The certification is linked to the practical learning completed during the program, covering hands-on agent-building projects, multi-agent system workflows and the Agentic AI capstone project. This gives learners documented evidence of finishing the prescribed training and practical work.
The Agentic AI course for Bengaluru 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. runs a career-focused IT training institute that provides structured technology education. Backed by 14+ years of training experience, Uncodemy delivers classroom programs via its Delhi and Noida centres, while live online classes let learners across India, including Delhi, take part remotely.
Within this Agentic AI program, learners aim to build AI agents capable of tool calling, multi-agent workflows and RAG-augmented interactions. The learning path further covers production-oriented agent deployment and wraps up with an Agentic AI capstone project that unites the major concepts in practical work.
Instructor-led sessions are combined with assignments, practical projects, interview preparation and career support. Career-support processes, applicable policies and eligibility conditions are shared before enrolment so learners understand what assistance is included, without treating it as a guarantee of employment.
Other courses for Bengaluru learners: LLM Engineering, RAG Engineering, AI Security, and Generative AI & Agentic AI courses for Bengaluru learners
The people who actually teach this course
Uncodemy's trainer team conducts every live session. The institute collaborates with 30+ Industry Trainers & Mentors carrying 10+ Years of Corporate Training Experience* on average, ensuring lessons mirror how AI is practised inside real companies.
Two roles stay separate at Uncodemy: trainers handle session delivery, while domain reviewers verify that the curriculum remains technically accurate and current. For this Agentic AI program, the curriculum and technical content are reviewed by Mr. Irshad, with additional review by Mr. Upendra Kumar Tiwari, giving learners an independent check on what gets taught.
Each trainer and reviewer is published by name with a profile link, letting you verify their background before joining.
Senior Data Science 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 · Tableau · Artificial Intelligence · Deep Learning · Power BI · MLOps
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 · Power BI · Tableau · SPSS · SAS · MS-Excel · SQL · HTML · CSS
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 · Excel · Power BI · Tableau · ML · DL · NLP · Time Series · IoT Devices · 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 Bengaluru and learn LLM fundamentals, tool calling, LangChain, LangGraph, multi-agent systems and deployment 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.
Bengaluru offers strong and steady scope for Agentic AI engineers, because the city combines a large IT services base with a deep startup and product ecosystem. Both sectors are adding autonomous agents, multi-agent workflows and generative AI to their products and internal operations.
Most technology hiring is concentrated around the Whitefield, Electronic City and Koramangala tech clusters, where services firms, global capability centres and product teams build AI and agentic practices. Alongside IT, Bengaluru's long-standing strength in SaaS, fintech and e-commerce creates demand for AI agents in areas such as customer engagement, workflow automation, document processing and intelligent assistants.
When hiring freshers and career switchers, interviewers usually weigh three things above all. First, a firm grasp of LLM fundamentals and agent architecture — planning, tool calling, memory and multi-agent orchestration. 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 chose an agent architecture, how they implemented tool calling and how they deployed with guardrails 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 calling, LangChain, LangGraph, multi-agent systems, RAG-augmented agents, 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, OpenAI APIs, LangChain |
| Agentic AI Engineer | LangGraph, LangChain, OpenAI APIs |
| AI Automation Engineer | Python, LangChain, FastAPI |
| Multi-Agent Systems Engineer | LangGraph, OpenAI APIs, Python |
| RAG-Augmented AI Engineer | LangChain, Vector DB, Hugging Face |
| AI Solutions Engineer | FastAPI, OpenAI APIs, Guardrails |
Over two to four years, growth usually comes from depth and ownership. Engineers who start with agent building often move into owning complete agentic workflows, from tool integration to deployment and monitoring. Many then specialise in areas such as multi-agent orchestration, RAG-augmented agents or agent security, and progress towards senior Agentic AI engineer roles. With broader system design experience, some later move into AI solution architecture or technical leadership positions.
Agentic AI salaries in Bengaluru depend heavily on the role you target, your practical skills and the type of employer. IT services companies, product firms and AI-first startups all hire Agentic 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 |
|---|---|
| AI Agent Developer | ₹5–9 LPA |
| Agentic AI Engineer | ₹6–10 LPA |
| AI Automation Engineer | ₹6–12 LPA |
| Senior Agentic AI Engineer | ₹12–22 LPA |
| AI Systems Architect | ₹18–30 LPA |
| 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 Bengaluru 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 Bengaluru spans several industries, and Uncodemy's network of 850+ hiring partners reaches across many of them. The sectors below are where Bengaluru-based Agentic AI skills are most commonly applied today:
Because every sector relies on the same core foundation of LLMs, tool calling, agent architecture and deployment, 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 | 15+ |
| Capstone | 25-hour Industry project |
| Career support | Dedicated Career & Placement Assistance |
Within Uncodemy's own catalogue, this Agentic AI course is the specialised program for building autonomous AI agents. LLM Engineering focuses on building and deploying applications powered by large language models, RAG Engineering specialises in retrieval-grounded systems built on enterprise knowledge, and AI Security concentrates on protecting AI systems. Those courses suit learners who already know which niche they want. If you want to build agents that can plan, use tools and work autonomously, this program is the right fit.
Uncodemy does not have a classroom in Bengaluru, so Bengaluru 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 projects 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 Whitefield, Electronic City or Koramangala. 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 AI agents with tool calling | This program |
| To add multi-agent orchestration and RAG to your LLM skills | This program |
| Narrow LLM application development only | Consider the LLM Engineering course |
| A narrow retrieval-system specialisation | Consider the RAG Engineering course |
Bengaluru learners move through this Artificial Intelligence course in 5–6 months. The structure covers 110+ live online sessions over 13 modules and ends with a 25-hour industry capstone. Both weekday and weekend batches are available in Bengaluru, letting you choose a pace that suits your work or study schedule.
Bengaluru participants do not need prior machine learning experience — Python begins from Module 2. Knowing programming fundamentals and being comfortable with basic maths and statistics helps Bengaluru learners advance faster; Module 3 builds up the mathematics and statistics required.
Bengaluru learners explore 15 tools: Python, NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, TensorFlow, Keras, PyTorch, OpenCV, Hugging Face, OpenAI APIs, Jupyter Notebook, Git/GitHub and FastAPI. Each is applied in hands-on assignments and projects rather than only shown in theory.
Yes. Bengaluru learners study Deep Learning & Neural Networks in Module 8, Natural Language Processing (NLP) in Module 9, and Computer Vision & Image AI in Module 10. Practical work in each module uses frameworks such as TensorFlow, PyTorch, Hugging Face and OpenCV.
Bengaluru learners complete Module 13, AI Projects & Industry Capstone, a 25-hour project. You scope an industry-style problem, prepare data, build and evaluate a model, deploy it through FastAPI and document it on GitHub as a portfolio piece you can discuss in interviews.
For Bengaluru learners, classes are live. The program includes 110+ 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 could not attend.
Bengaluru learners pay ₹24,500 + 18% GST, making a total of ₹28,910. The same fee applies in all modes and cities, whether you learn live online from Bengaluru or in a classroom at Delhi or Noida, and there are no hidden charges.
Yes, Bengaluru learners can access EMI starting at ₹4,818/month for 6 months.* This spreads the total fee of ₹28,910 across monthly payments. *EMI amount, tenure and eligibility may vary depending on the applicable payment or financing option.
Bengaluru 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, Bengaluru 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 Bengaluru learners to apply for entry-level 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 Bengaluru, indicative ranges run from ₹4–8 LPA for Entry-Level AI Engineers to ₹15–28 LPA for Senior AI Engineers and ₹20–35 LPA for AI Solutions Architects. These are market ranges, not guaranteed outcomes; actual offers vary by role, skills, experience, employer and market conditions.
Bengaluru learners can apply for AI Engineer, Machine Learning Engineer, Deep Learning Engineer, Computer Vision Engineer, NLP Engineer (Junior) and Generative AI Engineer roles. The broad curriculum lets you choose the direction that best matches your projects and interests.
Bengaluru learners from any discipline are eligible — graduates, working professionals, aspiring AI engineers and career changers. You need a laptop and a stable internet connection; programming fundamentals and basic maths comfort are helpful but are built up during the course.
No. For Bengaluru 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. Bengaluru 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 Bengaluru 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 Bengaluru, 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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