Post Graduate Certificate Programme in Building AI-Powered Business Applications

Module 3: AI for Strategic Research & Decision Intelligence

• Multi-source research synthesis,

• Business insight generation,

• When AI should retrieve information vs. Generate responses,

• Human review checkpoints

Skills Acquired: Run multi-source research synthesis with AI, identify when to retrieve vs generate, design human review checkpoints, extract business insights from AI-processed data.

Learning Outcome: Compress hours of research into minutes — and know exactly where to apply your own judgement before acting on AI-generated insight.

Module 4: AI for Executive Communication & Stakeholder Reporting

• AI-generated reports & summaries,

• Automated stakeholder communication workflows,

• Audience-specific reporting,

• Output quality evaluation

Skills Acquired: Build automated AI reporting pipelines, generate audience-specific summaries and updates, design stakeholder communication workflows, evaluate output quality.

Learning Outcome: Produce first drafts of weekly reports, board updates and stakeholder communications in minutes and know how to review and improve AI output before it is sent.

Module 5: AI for Enterprise Automation & Operational Efficiency

• Intelligent email & request classification,

• Workflow enrichment,

• SLA-based prioritisation,

• Owner-routing logic

Skills Acquired: Classify and route business requests using AI, apply SLA-based prioritisation logic, enrich workflows with relevant data, reduce manual triage effort.

Learning Outcome: Eliminate the manual sorting, labelling and routing that slows your team down and replace it with an AI workflow that handles it automatically.

Module 6: AI for Cross-Functional Collaboration & Team Productivity

• Workflow synchronisation across teams & systems,

• Integration models,

• Workflow conflict resolution,

• Meeting-to-action workflows

Skills Acquired: Synchronise workflows across teams and systems, automate meeting-to-action workflows, build integration models between functions, design conflict resolution logic.

Learning Outcome: Stop losing decisions and action items in meeting notes. Build AI workflows that capture, assign and track them automatically across your teams.

Module 7: AI for Monitoring, Escalation & Business Risk Management

• Exception detection,

• Escalation workflows,

• Alert management,

• Governance controls & human override mechanisms

Skills Acquired: Build exception detection workflows, design automated escalation logic, set up alert management, implement governance controls and human override mechanisms.

Learning Outcome: Catch problems before they reach your customer or your leadership. Build AI systems that monitor, escalate and alert while keeping humans in the loop.

Module 8: Enterprise AI Strategy, ROI & Organisational Adoption

• Logging, AI opportunity identification,

• ROI frameworks,

• Build vs. Buy vs. API decisions,

• Organisational adoption challenges,

• AI operating models & Centre of Excellence (CoE) structures,

• Executive stakeholder alignment

Skills Acquired: Identify AI opportunities, build ROI frameworks, evaluate build vs buy vs API decisions, design AI Centre of Excellence (CoE) structures, align executive stakeholders.

Learning Outcome: Present a credible AI business case to your leadership with ROI framing, operating model design and a realistic adoption roadmap.

Module 9: Responsible AI, Explainability & Trust Frameworks

• DPDP act 2023,

• GDPR overlap,

• Data minimisation principles,

• Cloud vs. On-Premise AI,

• Vendor governance,

• Prompt injection risks,

• Shadow ai controls,

• AI bias & fairness risks,

• Explainability frameworks,

• Human oversight systems,

• Enterprise AI ethics policy design

Skills Acquired: Apply DPDP Act 2023 and GDPR to AI decisions, design data minimisation practices, implement prompt injection controls, assess AI bias and fairness, build an AI ethics policy.

Learning Outcome: Lead your organisation's AI governance conversation with a practical framework covering compliance, risk, explainability and human oversight.

Module 10: AI Agents & Intelligent Automation

• Agentic AI fundamentals,

• Agent vs. Chatbot vs. Workflow systems,

• Decision loops,

• Tool usage,

• Single-agent & multi-agent workflows

Skills Acquired: Distinguish agents from chatbots and basic automation, map decision loops, identify tool-use scenarios, plan multi-agent workflow structures.

Learning Outcome: Confidently scope and design an AI agent workflow and explain to your team or leadership why an agent is (or is not) the right approach for a given problem.

Module 11: No-Code AI Agent Builder

• Workflow design,

• AI agent setup,

• Integrations with email/whatsapp/Slack,

• Trigger-based execution,

• Testing, optimisation & workflow reliability

Skills Acquired: Build trigger-based AI agent workflows (no code), connect agents to email, WhatsApp and Slack, test and debug workflow reliability, optimise agent performance.

Learning Outcome: Deploy a live, working AI agent that handles a real business process end-to-end connected to your communication tools and running on real triggers.

Module 12: AI Memory, Context & Personalisation

• Short-term & long-term memory,

• Multi-turn interactions,

• SOP integration,

• Personalised experiences using customer & business data

Skills Acquired: Design short-term and long-term AI memory, manage multi-turn conversations, integrate SOPs into AI systems, personalise AI responses using business data.

Learning Outcome:

Build AI systems that remember context across sessions and give answers tailored to your business — not generic responses from a public AI tool.

Module 13: Building Enterprise AI Knowledge Assistants (RAG)

• Why public AI tools lack business context,

• Connecting company documents to AI,

• Document organisation strategies,

• AI-powered enterprise knowledge systems

Skills Acquired: Connect company documents to an AI system, structure documents for AI retrieval, build a no-code enterprise knowledge assistant, understand when RAG is the right approach.

Learning Outcome: Deploy an AI assistant that answers questions from your company's own documents — accurately, without making things up.

Module 14: Deploying Context-Aware AI in the Enterprise

• Intelligent enterprise search techniques,

• Improving answer accuracy,

• Structured data integration,

• Retrieval optimisation,

• Context-aware information access,

• Response quality evaluation,

• Diagnosing inaccurate or low-confidence AI responses,

• Deployment readiness,

• Monitoring & continuous improvement

Skills Acquired: Improve AI answer accuracy, integrate structured data sources, evaluate response quality, diagnose why AI gives wrong answers, set up monitoring for live deployment.

Learning Outcome: Take your AI knowledge system from prototype to production with quality checks, monitoring, and a plan for ongoing improvement.

• Business problem identification

• AI solution architecture

• Compliance & security assessment

• Deployment planning

Skills Acquired:

Identify a business problem, design an AI solution architecture, assess compliance and security, plan deployment.

Learning Outcome:

Graduate with a portfolio-ready AI solution design — something you can walk into your next leadership conversation and present with confidence.

Learners in the Post Graduate Programme in Building AI-Powered Business Applications gain skills in Generative AI, Agentic AI, prompt design, AI reasoning, no-code AI application building, AI agent design, enterprise knowledge assistants, workflow automation, AI governance, and AI solution architecture. The programme also helps learners evaluate AI response quality, identify AI use cases, apply AI across business functions, and design AI-powered solution architectures through a capstone project.

No, coding experience is not required for this programme. The programme is designed around a no-code learning approach, which means learners are introduced to tools and platforms that can help them build AI-powered applications, agents, knowledge assistants, and workflow automations without writing lines of code. The focus is on identifying business use cases, designing workflows, applying AI tools, and understanding how AI solutions can be built and governed in a business context.

The programme is delivered over 4 months in a live online format. It is designed for working professionals and includes weekend live sessions, with sessions scheduled on Saturday and Sunday for 3 hours each. The live online format allows learners to engage with faculty, participate in guided learning, and complete practical exercises while continuing with their professional responsibilities.

This programme helps learners build AI-powered business applications by combining no-code tools, workflow design, prompt frameworks, AI agents, enterprise knowledge assistants, and governance thinking. Learners explore how to identify business problems, map where AI fits, design AI-enabled workflows, build no-code agents and assistants, and create AI solution architectures that can support practical business use cases across operations, research, collaboration, risk management, and executive reporting.

This programme is right for you if you are a business professional who wants to move beyond using AI tools for writing, summarising, research, and ideation. It is designed for professionals who want to build AI-powered workflows, no-code AI agents, enterprise knowledge assistants, and workflow automation solutions without writing code. The programme is especially relevant for operations, product, strategy, analytics, consulting, programme management, transformation, and business leadership professionals.

Yes, Post Graduate Programme in Building AI-Powered Business Applications is suitable for non-technical professionals because it follows a no-code AI application-building approach. Learners do not need coding experience to participate. The programme is designed to help business professionals understand where AI fits, how workflows should be designed, how AI agents and knowledge assistants can be created, and how AI-powered business solutions can be governed and applied responsibly.

The Post Graduate Programme in Building AI-Powered Business Applications goes beyond generic AI awareness and prompt engineering. While prompt design is covered, the programme also focuses on building AI-powered business applications, AI agents, enterprise knowledge assistants, workflow automations, and governance-ready AI solution designs. The emphasis is on applying Generative AI and Agentic AI to business use cases, not just learning how to prompt AI tools.

This Post graduate programme by iHUB DivyaSampark, IIT Roorkee is a strong choice for business professionals because it focuses on practical AI application-building without coding. Learners gain exposure to 15+ AI and automation tools, hands-on exercises, no-code AI agents, enterprise knowledge assistants, business workflow automation, responsible AI, governance, ROI thinking, and capstone-based solution design. The programme is structured for professionals who want to apply AI to real business problems rather than only understand AI conceptually.

Learners gain hands-on exposure to 15+ AI and automation tools used for building AI-powered applications, agents, enterprise knowledge assistants, workflow automations, and evaluation-ready systems. Tools may include ChatGPT, Gemini, Perplexity, Dify, Flowise, n8n, NotebookLM, Make.com, AnythingLLM, Open WebUI, LangSmith, Airtable, NocoDB, Tavily, and more. Tool coverage may be updated based on programme requirements and evolving industry practices.

The programme fee for the Post Graduate Programme in Building AI-Powered Business Applications is INR 1,09,000 + GST. This fee covers the 4-month live online learning experience, hands-on exercises, curriculum access, no-code AI tool exposure, select IIT faculty masterclasses, and the capstone project experience. Learners should check the official programme page or speak with an admissions advisor for payment plans, instalments, or applicable offers.

This programme can help learners build capabilities relevant to AI-related business roles, but it does not guarantee a role transition, job, promotion, or salary increase. The programme strengthens skills relevant to roles such as AI Product Manager, AI Solutions Analyst, Operations Excellence Manager, Business Transformation Manager, and other roles involving AI-powered business applications, workflow automation, AI adoption, and solution design.