+91 8423662366
Apply Now
-
Program Fee
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 system.
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.
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.
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
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 Professional Certificate in Generative & Agentic AI is designed to make advanced AI learning accessible while offering flexible payment options.
The most asked questions
BITS Pilani Digital is the digital learning division of BITS Pilani that offers rigorous, industry-aligned upskilling programs designed for working professionals to stay current with evolving technology.
It is systems-and-practice first: heavy hands-on labs (120+ hours) plus an end-to-end capstone focused on building practical GenAI and agentic AI solutions, not just theory or prompting.
Early-to-mid career tech professionals, founders/consultants, and senior professionals moving into AI product/technology leadership roles.
Any graduate (any stream); 2 years of coding experience with basic Python knowledge is recommended.
7 months (26 weeks + 4 weeks Capstone), delivered online through pre-recorded videos weekend live instructor sessions (2 hours), and self-paced labs, culminating in one capstone project (GenAI and/or agentic AI system).
- AI models & chat: Gemini, Llama, Qwen
- Services (AI apps / interfaces): Claude, ChatGPT, Perplexity, OpenWebUI, Ollama (acts as a local LLM runner)
- Agents & orchestration: CrewAI, LangChain
- Workflow automation: n8n
- RAG / knowledge stack: Qdrant, Pinecone, Weaviate
- Build (vibe coding): Python, Flask, Streamlit, Jupyter, Visual Studio Express (VS Code)
- Work apps & integrations: HubSpot
- Infra & configuration: Cloud accounts (learner-funded);
You will build a complete GenAI and/or agentic AI system as a capstone with extensive labs; It may not be “deployment from scratch” as a guaranteed outcome, but it is designed to produce an end-to-end working system.
Yes—Generative AI is a core focus, including GenAI + RAG project types (e.g., knowledge bot with citations, contract clause copilot, meeting-to-action studio).
Applicants should have a bachelor’s degree, relevant professional experience, and working knowledge of Python. Prior exposure to
software development, APIs, backend systems, or data workflows is recommended.
No mandatory coding prerequisites; foundation modules are available (Python for AI & Automation, Maths/ML concepts for GenAI, Cloud foundations, DevOps).
Blended online learning: weekly pre-reads, live mentor-led sessions, and extensive hands-on labs; non-developers get starter notebooks while advanced learners can code.
Break is possible and allowed only once as part of this program. If you take a break, you will be moved to the next available cohort at no extra cost. The program is structured and the workload is designed to enable you to complete the program at one stretch without taking breaks and continuity is encouraged to match the modular schedule. Please note: that your continuity after break is subject to availability of the next cohort which is decided as per the discretion of the institute.
Programs at BITS Pilani Digital are taught by a distinguished pool of experts from both academia and industry. Faculty members may include:
Professors from BITS Pilani’s campuses who bring deep academic rigor and research-driven insight.
Dedicated faculty from the Digital Learning Division, focused on delivering engaging, practice-oriented learning experiences.
Guest faculty and mentors carefully selected and rigorously onboarded from the industry and other prestigious academic institutions, ensuring every course is current, applied, and industry-relevant.
In each program, you will often learn from a blend of academia-driven scholars and industry practitioners — experts who not only teach but actively build, research, and solve problems in their respective domains.
No traditional exams. Evaluation is through module labs and projects, hands-on labs, and a final capstone.
Successful learners will receive a certificate of completion titled: “Professional Certificate in Generative AI & Agentic AI.”
Successful completion of the certificate program would require participation in all quizzes and completion of the capstone project with a minimum “fair” grade
The Transcript will contain the list of modules and the Capstone project title with non letter grades.
The primary focus of BITS Pilani Digital is to make every learner industry-ready through a combination of rigorous, industry-aligned curriculum, hands-on projects, and mentorship from experienced professionals and faculty. This learning methodology is designed to build deep, career-relevant skills that empower professionals to progress confidently in their chosen domain.
To complement this, BITS Pilani Digital offers career enablement support including resume guidance, career mentorship, and curated opportunities from its industry partner network. These opportunities, however, are not guaranteed and depend on several factors such as market conditions, learner performance, and individual career aspirations.
Learners are encouraged to take ownership of their career journey, actively leverage the program’s learning experiences, and pursue roles aligned with their skills and goals.
This certificate is a shorter, outcome-oriented route (6 months) focused on practical GenAI + agent skills and portfolio projects, whereas our degree is broader and longer; the best choice depends on whether the learner needs a credentialed academic pathway or faster job-relevant capability building.
Experiential learning is at the heart of every program at BITS Pilani Digital. All labs are mandatory and project-based, designed to help learners translate concepts into real-world applications using industry-grade datasets, tools, and cloud environments.
You’ll gain hands-on experience across every stage, from deployment and monitoring to optimization and troubleshooting guided by faculty and industry mentors who ensure that every exercise reflects real professional challenges. This immersive, applied learning approach ensures that you don’t just learn the technology — you practice, implement, and master it.
While several of our labs leverage shared or open-source environments, the applied and enterprise-focused nature of this program necessitates the use of cloud infrastructure. As such, learners will be expected to fund and manage their own cloud and tool subscriptions where required.
In addition, learners are expected to maintain an active subscription to Claude Pro for the duration of the program, along with approximately USD $100–$150 worth of API credits from either Anthropic or OpenAI to support hands-on work and experimentation.
While we strive to prioritize open-source tools wherever possible, certain advanced use cases may require access to paid tools or platforms. In such instances, learners may need to procure relevant subscriptions to fully benefit from the program experience.
While many of our labs use shared or open-source environments, the nature of this program is such that enterprise cloud use is required and is learner-funded. Learners to use their own cloud/tool subscriptions where needed.
The program is specifically designed for technology professionals and follows a flexible, part-time learning structure that allows you to balance work and study effectively.
Each week includes:
~3+ hours of engaging, expert-led digital learning modules
~6 hours of hands-on projects and lab work in real-world environments
~1 hour of live instructor-led sessions for deeper insights and discussions
In total, you can expect around 9–10 hours of learning engagement per week, thoughtfully optimized for working professionals who wish to upskill without taking a career break.
In this program, we have placed strong emphasis on the deployment, implementation and full-lifecycle real-project component.
The program runs approximately 24-26 weeks (~ 6 months) with ~9-10 hours per week of learning engagement for working professionals.
Importantly: the program incorporates “significant practical learning”. Every module includes extensive hands-on labs.
Finally, you can focus your capstone project where an industry professional will provide mentorship.
Learners should plan for an additional investment of approximately USD 250-300 over the duration of the program to support hands-on learning. This covers essential AI tools and infrastructure, including subscriptions (such as Claude Pro USD 140), API usage USD 100-150(Anthropic/OpenAI), and limited cloud compute for practical labs and projects (USD 50).
This investment enables learners to work with industry-relevant tools and real-world environments, ensuring they derive maximum value from the program. Actual spend may vary slightly based on individual usage patterns and optional tool choices.