Download Brochure
Apply Now
-
Program Fee
INR 11,800/ month
(Six-month interest-free EMI)
Application deadline
8th June, 2026
Duration
~30 Weeks
Type of program
Certificate
Program introduction
AI Is moving from prompts to autonomous systems
Learn to build Agentic AI and RAG systems that can reason, retrieve, automate, and perform reliably in real-world environments.
Agentic AI is the next big shift. Gartner expects that by 2028, over half of enterprises will move beyond assistive AI and favor platforms built for workflow results. And Microsoft reports that 57% of Indian business leaders expect teams to build multi-agent systems to automate complex tasks. The shift is no longer about using AI to assist work. It is about designing AI systems that can execute it.
Why choose this program
Most Generative AI programs stop at concepts, prompts, or tool demos. This program goes further, helping you build real AI systems, not just experiment.
Master agentic AI, RAG, workflows, and evaluation for production-ready implementation.
Many AI courses treat Agentic AI as an add-on topic after covering basic GenAI and prompting. Learners may understand what an AI agent is, but they rarely learn how to design agentic systems that can plan, use tools, manage context, coordinate actions, and handle failure.
Learn deeper,
rise higher
as this program puts Agentic AI at the centre of the learning journey. You will learn how intelligent systems are structured, how agents reason, how tasks are decomposed, how tools are called, and how workflows are orchestrated for real-world use cases.
Passive lectures can create familiarity, but they rarely create capability. Many learners finish AI courses with theoretical understanding but struggle when asked to build, debug, or integrate an AI system independently.
Learn deeper,
rise higher
with practice-first learning model. From the early stages of the program, concepts are translated into hands-on labs, guided implementation, production-style demos, and real problem-solving exercises. You do not just learn how AI systems work, you build them.
In many program, the capstone is a short final assignment or a polished demo that does not reflect the complexity of real AI implementation. It may look good on paper but rarely proves end-to-end system-building ability.
Learn deeper,
rise higher
with an industry-aligned AI systems project. You will work through the complete journey of building a solution: identifying the problem, designing the architecture, building the RAG or agentic workflow, integrating tools, evaluating performance, and presenting a working outcome.
Traditional assessments test memory. But AI engineering is not about remembering definitions, it is about making systems work under constraints. Multiple-choice tests cannot measure whether someone can build a reliable AI application.
Learn deeper,
rise higher
as this program uses project-based evaluation to assess what truly matters: your ability to apply concepts, build working artifacts, solve technical problems, evaluate outputs, and improve system performance. Your progress is measured through execution, not just theory.
Purely academic program can lack implementation depth. Purely practitioner-led program can miss conceptual rigour. Learners often need both: strong foundations and real-world execution guidance.
Learn deeper,
rise higher
as the program brings together BITS Pilani Digital faculty and industry mentors. Faculty help you build conceptual clarity and technical depth, while industry practitioners guide you on implementation patterns, trade-offs, tools, and real-world AI system design.
Many AI courses rely on generic examples and toy datasets. Learners build small exercises but do not experience the ambiguity, constraints, and decision-making involved in solving real technology problems.
Learn deeper,
rise higher
with industry-oriented AI challenges that mirror how AI is applied in business environments. The focus is not just on making a model respond, but on solving problems where data, workflows, users, reliability, and outcomes all matter.
Most GenAI courses stop once the model generates an answer. But in production, that is only the beginning. AI systems must be tested for hallucinations, retrieval quality, consistency, safety, and failure modes before they can be trusted.
Learn deeper,
rise higher
with evaluation built into the learning experience as a core engineering skill. You will learn how to test and improve AI systems using evaluation frameworks, regression testing, retrieval checks, prompt quality assessment, and reliability-focused workflows.
A certificate alone is no longer enough. Employers and teams want evidence of what you can actually build. Many learners complete program but are left without strong project artifacts that demonstrate real ability.
Learn deeper,
rise higher
as the program is designed to help you create portfolio-ready proof of work. Through labs, projects, and the capstone, you will build artifacts that showcase your ability to design AI applications, RAG systems, agent workflows, and evaluation-backed solutions.
Some program teach agent frameworks in isolation. Others teach workflow automation without deep AI reasoning. But real enterprise AI systems need both: intelligent agents that can reason, and workflow layers that can execute actions across tools.
Learn deeper,
rise higher
by learning how to connect agent orchestration with workflow orchestration. This includes working with AI agents, RAG systems, APIs, Model Context Protocol, n8n, Zapier, Slack, Flask, Streamlit, and other layers required to move from intelligence to real-world action.
Many program compete by listing dozens of tools. But tool overload often leads to shallow familiarity. Learners may recognize many logos but lack depth in how to choose, connect, and apply the right tools in an AI system.
Learn deeper,
rise higher
as this program focuses on tool depth across the AI systems stack. For each category, you work with carefully selected tools that are relevant for real implementation, from LLMs and RAG infrastructure to agent frameworks, workflow automation, application layers, and evaluation systems.
Career support in many programs is limited to resume templates or generic interview preparation. But professionals moving into AI systems roles need help communicating a very specific capability: the ability to build and explain real AI architecture.
Learn deeper,
rise higher
with the program supporting your transition into AI-focused roles by helping you position your skills, projects, and capstone work around high-impact capabilities such as Agentic AI engineering, RAG system design, AI workflow integration, and production-ready AI application development.
What you will build
Across the program, you will work on hands-on labs, applied projects, and a capstone designed to demonstrate real AI system-building capability.
You will build practical artifacts such as
Systems stack you’ll master
Learn how modern AI systems are architected across LLMs, RAG, agents, workflows, and evaluation layers.
Understand how each component connects to build systems that go beyond responses.
Create AI solutions that can reason, retrieve, act, and perform reliably in real-world environments.
Intelligence & Reasoning Layer
Where AI understands, reasons, and generates outputs
- OpenAI
- Anthropic
Use leading LLMs as the reasoning engine behind AI applications, agents, structured outputs, and intelligent workflows.
Agent Orchestration Layer
Where intelligence becomes multi-step execution
- CrewAI
Design AI agents that can plan, divide tasks, use tools, coordinate roles, and execute complex workflows.
AI Application Layer
Where AI systems become usable products.
- Flask
- Streamlit
Build user-facing AI applications that turn LLM, RAG, and agent workflows into working proof-of-concept products.
Integration & Protocol Layer
Where AI connects with tools, context, and external systems
- Model Context Protocol (MCP)
Understand how modern AI systems standardise context sharing, tool access, and external actions.
Knowledge & Retrieval Layer
Where AI grounds itself in trusted data
- Qdrant
- PDFs
- Google Drive
Build RAG pipelines that retrieve relevant context, reduce hallucinations, and improve the reliability of AI-generated responses.
Workflow Automation Layer
Where AI moves from response generation to business execution
- n8n
- Zapier
Automate multi-step workflows across tools, approvals, notifications, and business processes.
Action Layer
Where AI agents interact with real work environments
- Slack
Build AI systems that can send updates, trigger actions, support users, and operate within team communication workflows
Evaluation & Reliability Layer
Where AI systems are tested before they are trusted
- Pytest
- Evaluation Harnesses
- Regression Testing
- Hallucination Checks
Measure output quality, test retrieval performance, catch regressions, and improve AI system reliability before deployment.
From Tool Familiarity to AI Systems Thinking
Most AI programmes teach tools in isolation.
This programme teaches how they work together as a complete AI system:
LLMs → RAG → Agents → Applications → Workflows → Actions → Evaluation
You will not just learn what each tool does.
You will learn how to connect them into systems that solve real problems.
From Tools to Systems Thinking
Most programs teach tools in isolation
This program teaches how they work together as a system:
Intelligence → Retrieval → Reasoning → Action → Evaluation → Deployment
To ensure depth over tool overload, the program focuses on carefully selected tools with strong industry relevance. Tool choices may be updated based on adoption, availability, and curriculum fit.
Some labs may require learners to access third-party platforms. While several tools are free or open-source, select tools may involve additional subscription or usage-based costs.
Who should apply?
For professionals ready to move beyond AI experimentation and start building production-grade Agentic AI and RAG systems. It is built for professionals who want to work with LLMs, AI agents, RAG pipelines, Python, workflow automation, evaluation frameworks, and modern AI orchestration tools to solve practical technology and business problems.
Data, AI & Software Engineering Professionals
For software engineers, AI/ML engineers, data engineers, backend developers, and solution architects who want to move beyond model experimentation into designing multi-agent systems, advanced RAG pipelines, and deployable AI services.
Product & Technical Leaders
For technical product managers, platform leads, engineering managers, and innovation heads responsible for bringing AI into products, platforms, and enterprise workflows.
Learn how Agentic AI systems are architected, evaluated, integrated, and governed — so you can lead AI initiatives with both technical confidence and business clarity.
Mid-Career Technology Professionals
For professionals with prior exposure to programming, APIs, backend systems, data workflows, or software delivery who want to transition into high-impact AI roles.
This program helps you build the capabilities needed for Agentic AI engineering, RAG application development, AI solution architecture, and AI systems design.
Note
- Working knowledge of Python is required.
- Prior exposure to software development, APIs, backend systems, or data workflows is recommended.
- Learners without working knowledge of Python will be required to enrol in a Python Bridge Course.
- The Python Bridge Course will run parallel to the Professional Certificate in Generative & Agentic AI program.
- Python Bridge Course Duration & Fee: 4 months | ₹8,500
Learning methodology
Learn AI the way it is built in the real world through systems, workflows, and hands-on implementation.
Move beyond passive learning with labs, projects, and real problem-solving across Agentic AI and RAG.
A structured model combining self-paced learning, live sessions, and continuous mentorship to help you build as you learn.
Learn foundations at your own pace
Build conceptual clarity through rich videos, insightful reading, and structured self-paced content before live sessions.
This ensures your live sessions are focused on application, discussion, and implementation not repetition.
Weekly live faculty & mentor sessions
Join live sessions led by BITS Pilani Digital faculty and/or industry mentors for deeper explanations, hands-on demos, and live problem-solving.
These sessions help you bridge the gap between learning concepts and applying them in real AI systems.
Start building from week One
From the beginning of the program, you will work on AI challenges that connect theory with hands-on implementation.
Every module is designed to help you apply what you learn immediately across Agentic AI, RAG, workflows, applications, and evaluation.
Hands-on labs every week
Spend dedicated time each week building, testing, and improving AI systems through guided labs and project work.
These labs help you gain practical fluency with LLMs, RAG pipelines, AI agents, application frameworks, workflow automation, and evaluation practices.
Continuous technical support
Learning continues beyond live sessions through discussion forums, TA support, mentor guidance, technical feedback, and clarifications.
You get support while you build, debug, and apply concepts, not just while attending class
Structured for working professionals
Expect a weekly commitment of approximately to 8-10hrs, designed to help technology professionals pursue the program alongside their jobs.
The structure balances self-paced learning, live instruction, and hands-on project work so you can progress consistently without pausing your career.
Weekly learning commitment
Designed to fit alongside your work schedule, the program combines guided and self-paced learning:
- ~1 hour of self-paced videos and readings
- ~2 hours for additional learning and concept reinforcement
- ~2 hours of live instructor-led sessions
- ~4–6 hours of hands-on labs and project work
Overall, expect ~8–10 hours of weekly commitment, balanced for working professionals.
Regular live sessions are typically scheduled on Saturday evenings. Session days and timings may vary depending on instructor’s availability. Additional supplementary sessions may be scheduled on weekends.
Master 20+ industry tools that will power your AI career
AI adoption is accelerating, and skills must evolve with it.
increase in overall AI adoption with 65% of organizations using generative AI.
(Source: McKinsey)
of leaders expect AI agents to play a key role in company strategy within 12–18 months.
(Source: Microsoft Work Trend Index)
current skill sets expected to become outdated by 2025–2030.
(Source: World Economic Forum – Future of Jobs Report)
Where opportunity meetsoutcomes
It’s time to learn agentic AI in-depth and rise higher in your professional journey.
Tools built into the curriculum.
Of immersive hands-on lab experience.
That's all it takes to master Agentic AI.
Turn skills into careers
*Source: 6figr, buildfastwithai, Glassdoor
BITS Pilani Digital equips learners with industry-relevant skills and career support to enhance employability. However, job placement or advancement is not guaranteed. Opportunities depend on market conditions, learner performance, and individual goals.
Curriculum snapshot
Project | Brief Description |
| Foundations (bridge) |
|
Module Name | Brief Description |
| LLM application engineering |
|
Module Name | Brief Description |
| RAG systems (production-minded) |
|
Module Name | Brief Description |
| LLM evaluation & quality: A major differentiator |
|
Module Name | Brief Description |
| Agentic AI core |
|
Module Name | Brief Description |
| Concepts in Deployment, integration, and MLOps-for-LLM apps |
|
Module Name | Brief Description |
| Capstone (enterprise-grade) | Reference GenAI + RAG Capstone Projects
Reference Agentic AI Capstone Projects
|
Please note: Changes to the Program curriculum, calendar, faculty and any other part of the program can be made by the Institute at any time at their discretion
Learn from architects behind production-grade AI solutions.
Dr. Janapati Naga Muneiah
Expertise: Applied Machine Learning | AI Systems Design | Customer Analytics | Fraud Detection
- Data Scientist at QXimpact with a Ph.D. in Machine Learning, focused on delivering business impact through applied AI
- Built high-accuracy demand forecasting systems using H2O and XGBoost for enterprise use cases
- Designed customer and product segmentation frameworks to drive targeted growth and decision-making
- Developed fuel fraud detection solutions, achieving ~20% cost reduction through data-driven insights
- Published multiple research papers in machine learning, with a focus on profit-driven modeling and decision tree optimization
Ashish Prasad
Expertise: AI Systems Architecture | Applied Machine Learning | Enterprise AI Integration
- Senior Software Engineering Lead, Microsoft with 12+ years of experience at the intersection of AI and software engineering.
- Builds large-scale AI systems integrating C#, .NET, TypeScript, SQL, Azure ML.
- Works on AI-driven productivity and contextual intelligence for global enterprise users.
- Contributes to Microsoft’s Project Turing, advancing AI research and real-world deployment.
Sample Certificate
Fee structure
Total program fee
INR 72,000 +GST
Includes booking fee of INR 12,000
(Non-refundable)
Interest free EMI
INR 11,800 / month
(Six-month easy EMI)
The most asked questions
It is a 30-week online certificate from BITS Pilani Digital that takes working technology professionals from using Gen AI and Agentic AI tools to building production-grade applications. You learn to design, build, evaluate and deploy applications powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and agentic workflows, the same stack that engineering teams at top product companies are hiring for in 2026.
Generative AI is about creating content with models like LLMs, text, code, images, summaries. Agentic AI is the next step: AI systems that reason, plan, use tools, call APIs, and complete multi-step tasks on their own. Most short courses stop at Gen AI. We cover both because real-world enterprise problems are moving from “ChatGPT-style chat” to autonomous agents that actually do the work. You finish the program able to ship both.
At a high level, the curriculum is built around four pillars:
- Foundations of Generative AI and Large Language Models, how they work, prompting techniques, fine-tuning, and responsible-AI considerations.
- Retrieval-Augmented Generation (RAG), grounding LLMs in your own data with vector stores and embeddings.
- Agentic AI, designing autonomous agents, multi-agent orchestration, tool use, planning, memory and workflow automation.
- Production readiness, evaluation frameworks, observability, guardrails & security, cost and latency optimisation, and deployment patterns.
Every module is paired with hands-on labs and projects so you build a portfolio of working systems alongside the theory.
It is built for intermediate technical learners, typically engineers with 3 to 7 years of experience who already write code and now want to add Generative AI Application building to their toolkit. We start at the conceptual level for each topic, then quickly move to implementation. If you have never written Python, take the optional Python Bridge Course alongside the main program. If you are already a senior AI/ML engineer building LLM apps in production, the agentic, evaluation and orchestration modules will be the highest-value parts for you.
Short courses teach you to use Gen AI as a user. This program teaches you to build applications using Generative AI, as an engineer would. You learn the architecture behind LLMs, how to ground them in your own data, how to wrap them in agents that perform reliable multi-step tasks, and how to evaluate, monitor and deploy these systems in production-like environments. The capstone, mentor reviews and 30-week depth mean you walk out with portfolio-grade work, not a slide-deck certificate.
The program is designed for working technology professionals, including:
- Software engineers and backend developers who want to add Gen AI & Agentic AI Application development capabilities to their stack.
- Data engineers, data scientists and AI/ML engineers moving from classical ML to Gen AI and agents.
- Solution architects, platform engineers and tech leads designing Gen AI capabilities for their teams.
- Technical product managers who need to ship Agentic AI features and want to speak the language of the engineers building them.
- Mid-career professionals (typically 3–7 years of experience) looking to make a credible move into AI roles.
You need a bachelor’s degree (any discipline) and working familiarity with code, ideally Python. Prior exposure to software development, APIs, backend systems or data workflows is recommended. You do not need a prior background in machine learning. Learners who need a Python refresh can enrol in the optional Python Bridge Course that runs alongside the main program.
Yes. We offer an optional 4-month Python Bridge Course at ₹8,500 that runs parallel to the main program. It is built specifically to get you to the Python proficiency the certificate assumes, functions, classes, libraries, basic data handling, working with APIs. You can complete it before or alongside the certificate.>
It can be, if you are willing to code. The program assumes hands-on building, not just conceptual learning. If you are a product manager or analyst who wants to lead AI initiatives end to end, you will get enormous value, but expect to write code in the labs and capstone. There is an AI Assisted Code Generation segment, but you still need to be comfortable with coding. If your goal is purely strategic or non-technical, a business-focused AI program may suit you better.
Applications are submitted online at the program page. Admissions are based on academic background, professional experience and a short statement of purpose. There is no GATE / GMAT-style entrance exam. Once shortlisted, you complete enrolment and joining formalities, and you are added to your cohort and learner platform.
The program runs for 30 weeks. Plan for roughly 8–10 hours per week, a mix of self-paced learning, live sessions, labs and project work. Most learners hit a comfortable rhythm of 2 short weekday touchpoints (videos, reading, lab time) and a longer weekend block for live sessions and project work.
Yes, it is fully online and built around three layers: rich self-paced video, reading and labs to build conceptual clarity before each live session; live online sessions led by BITS Pilani Digital faculty and industry mentors focused on application, demos and live problem-solving; and continuous mentorship across projects and the capstone. You do not have to travel to campus.
Yes. Live sessions are scheduled at working-professional-friendly times, typically weekends and select evenings. All sessions are recorded and available on the learner platform, so if you miss one because of travel or work, you can catch up the same week. Mentor office hours and discussion forums are available throughout the program for follow-up.
You can watch the recording at your convenience, post questions in the cohort forum, and bring them to the next mentor office-hours session. If you fall behind for genuine reasons, work emergencies, family situations, medical, the program team will help you plan a catch-up path. The 30-week structure is designed with a working professional’s realities in mind.>
You will build incremental, real-world projects through every module, LLM-powered applications, RAG systems grounded in your own document corpus, agentic workflows that automate multi-step tasks, evaluation harnesses, and a deployment-ready system in the capstone. Each project is reviewed against rubrics covering correctness, design, code quality and production readiness, with mentor feedback you can act on.
The capstone is the final, integrative project of the program. You scope a real problem (often from your own domain or workplace), design and build an end-to-end Generative or Agentic AI solution, evaluate it rigorously, and present it to faculty and industry reviewers. It becomes the centrepiece of your portfolio when you interview for AI roles, a working system you designed, not just a notebook.
Yes. To receive the “Professional Certificate in Generative & Agentic AI” you must complete all quizzes and the capstone project with a minimum “fair” grade. This standard exists so that the certificate carries real signal to employers, every graduate has shipped a graded, reviewed system.
You receive the “Professional Certificate in Generative AI & Agentic AI” from BITS Pilani Digital. It is issued in your name on successful completion of all quizzes and the capstone at the required grade level. You can add it to LinkedIn, your résumé, and your professional profile.
BITS Pilani is one of India’s most established institutions and is widely recognised by Indian and global employers. The certificate carries the BITS Pilani Digital identity, and the curriculum is built around the skills hiring managers are actively screening for in 2026, LLMs, RAG, agents, evaluation and production deployment. The strongest signal you carry to interviews, however, is the portfolio of work you build during the program.
No, this is a non-degree, non-credit professional certificate program, not a Bachelor’s or Master’s degree. It is designed for skilling and career acceleration, not academic credit transfer. If you are looking for a degree, BITS Pilani Digital offers separate UGC-approved online degree programs you can explore.
The total program fee is ₹72,000 + applicable GST. This includes a non-refundable booking fee of ₹12,000. The fee covers 30 weeks of structured learning, all live sessions with BITS Pilani Digital faculty and industry mentors, the self-paced content library, labs and project infrastructure, capstone mentorship and review, and the final certificate of completion. The optional Python Bridge Course is billed separately at ₹8,500.
Yes. EMI and no-cost EMI options are available through our financing partners so you can spread the fee over 6 months. You can review the available plans on the application page or speak to an admissions counsellor for the option that fits your situation.
You have a 7-day refund window from the date of your first class. If you decide within those 7 days that the program is not right for you, you can request a refund by writing to the admissions team, note that the ₹12,000 booking fee is non-refundable, so the refund applies to the balance of the program fee. After this 7-day window, the fee is non-refundable.
Graduates typically position themselves for roles such as:
- AI Engineer / Generative AI Engineer
- LLM Application Developer
- Agentic AI Engineer / Agent Developer
- Machine Learning Engineer (with Gen AI specialisation)
- AI Solution Architect / Platform Engineer
- Technical Product Manager, AI Products
The exact role you target depends on your existing experience and the seniority of your current title. The program is designed to make you credibly hireable for an AI-engineering line of work, not just “aware” of Gen AI.
Yes. You get access to career-readiness support including résumé and LinkedIn reviews, mock interviews for AI-engineering roles, portfolio guidance built around your capstone, and access to relevant openings through the BITS Pilani Digital network and partner ecosystem. Note: this is career support, not a guaranteed placement, we focus on getting you genuinely interview-ready.
Three things set this program apart:
- Depth, not just breadth, 30 weeks built around production-grade Generative and Agentic AI, not a 6 to 12-week tour of slides.
- Faculty + practitioners, every cohort blends BITS Pilani Digital faculty with industry mentors actively building these systems, so you get academic rigour and field experience in the same room.
- Portfolio-grade capstone, you graduate with a deployed, reviewed system you can demo in interviews, not a course-completion badge.
Combined with the BITS Pilani institutional name, this is what changes how hiring managers read your résumé after the program.
You can absolutely self-teach Gen AI, the materials exist online for free. What you cannot replicate alone are the structure that gets you to the finish line on a working professional’s schedule, the mentor feedback that turns a clever notebook into a production-like system, the cohort of peers you learn faster with, and the BITS Pilani Digital signal on your résumé that opens doors before the first interview. If you value time, accountability and a credible signal, a structured certificate compounds well.
A dedicated learner support team is available throughout the program for platform, scheduling and administrative queries. For learning questions, you have weekly live contact sessions of 2 hours with Industry Mentors, and a cohort discussion forum. You are not learning alone.
If you are a working technology professional who is comfortable writing code, sees Gen AI engineering as the next 5-year direction of your career, and wants a credible certificate and portfolio without taking a career break, this program is built for you. The fastest way to be sure is to book a free counselling call from the program page, you can walk through your profile, your goals and the cohort timeline with an admissions counsellor before you commit.