I  ·  Pillar One

The Analytical Canon.

Proven knowledge. Elite delivery.

Analytical work in complex organisations is not about speed. It is about trust. The Canon teaches professionals to build systems that produce defensible outputs — outputs that pass audit, survive scrutiny, and earn confidence from stakeholders who do not understand the method but must trust the result.

What "Canon" means
Not a syllabus. A point of view.
The Canon is the structured, rigorous foundation every serious analytical professional needs before applying AI to real organisational problems — the WHY and the WHAT. Pillar II is the HOW and BUILD.
In practice
From foundation to leadership — in four tracks.
The Canon is structured as four progressive tracks: the Foundational Track, the Applied Track, the Engineering Track, and the Leadership Track. Foundational and Leadership can each be taken independently; Engineering builds directly on Applied — from AI fluency, to applied systems, to shipping and running them, to leading AI adoption responsibly.
Analytics — what's proven → Applied Intelligence — what's emerging → Authority — what validates either

The Tracks

Four tracks from fluency to leadership.

Foundational and Leadership each stand on their own. Engineering builds directly on Applied. Every track is delivered as live online classes, 90–120 minutes each, with demonstrations, role-based examples, exercises, recordings, and downloadable concept guides.

Start with the track most relevant to your current role and goals. Foundational and Leadership can be taken independently; Applied and Engineering are best taken in sequence.

1
Foundational Track
"Understand and use modern AI confidently in daily work — without a technical background."
AI Fluency for Professionals · 12 live classes
2
Applied Track
"Understand how modern AI systems retrieve knowledge, take actions, and become dependable business workflows."
Applied AI Systems · 18 live classes
3
Engineering Track
"Know what it actually takes to ship, deploy, and run AI systems in production."
AI Infrastructure & Deployment · 11 live classes
4
Leadership Track
"Lead AI adoption responsibly, evaluate opportunities and vendors, and turn AI experimentation into measurable business value."
AI Strategy, Governance & Transformation · 9 live classes
1
Track 1 — Foundational Track

AI Fluency for Professionals

Build the confidence to understand, use, and evaluate modern AI in everyday professional work — without a technical background.

Approx. delivery12 live online classes × 90–120 minutes
ModeLive online via Microsoft Teams
Suggested learner profileWorking professionals, managers, consultants, students, career-transitioning professionals, and business owners.
View the full syllabus — 12 classes
  1. 1.AI, Machine Learning, and Deep Learning
  2. 2.Neural Networks, Supervised Learning, Unsupervised Learning, and Reinforcement Learning
  3. 3.Generative AI, Foundation Models, Transformers & Attention, Model Weights, and Open vs. Proprietary Models
  4. 4.Large Language Models, Small Language Models, and Multimodal AI
  5. 5.Tokens, Tokenization, Context Windows, AI Inference, and AI Reasoning
  6. 6.Context Engineering, Conversation State, Memory, Prompt Engineering, and System Prompts
  7. 7.Temperature, Top-P, Structured Outputs, Function Calling, and Tool Calling
  8. 8.Hallucinations, Grounding, Jailbreaking, Prompt Injection, and AI Guardrails
  9. 9.AI Training, Fine-Tuning, Distillation, Synthetic Data, and Zero-/Few-Shot Learning
  10. 10.AI Benchmarks, Model Cards, and RLHF
  11. 11.Voice AI, Text-to-Speech, Speech-to-Text, AI Image/Video Generation, Diffusion Models, Deepfakes, and Watermarking
  12. 12.Practical AI Workflows and Individual AI Work Plan
Enrol
2
Track 2 — Applied Track

Applied AI Systems

Understand how modern AI systems retrieve knowledge, take actions, connect to tools, and become dependable business workflows.

Approx. delivery18 live online classes × 90–120 minutes
ModeLive online via Microsoft Teams
Suggested learner profileGraduates of the Foundational Track, professionals working with AI projects, business analysts, operations leaders, consultants, and aspiring AI product builders.
View the full syllabus — 18 classes
  1. 1.RAG: why AI needs trusted external knowledge, and RAG vs. fine-tuning
  2. 2.Embeddings and semantic search
  3. 3.Chunking, vector databases, vector indexing, hybrid search, and re-ranking
  4. 4.Knowledge bases, enterprise search, structured/unstructured data, and metadata
  5. 5.Knowledge graphs, graph databases, graph neural networks, and GraphRAG
  6. 6.Chatbots vs. AI agents, agentic AI, and autonomous workflows
  7. 7.Agent architecture, single-agent, multi-agent systems, orchestration, and sandboxing
  8. 8.Agent planning, routing, prompt chaining, and ReAct
  9. 9.Agent reflection, self-correction, and evaluation loops
  10. 10.Agent memory, human-in-the-loop, approvals, and safe tool use
  11. 11.Multi-agent collaboration, context caching, test-time compute, and quantization
  12. 12.APIs, REST, GraphQL, OpenAPI, JSON Schema, and MCP vs. API
  13. 13.MCP, A2A, function calling, OAuth, rate limits, and latency
  14. 14.Webhooks, SDKs, and event-driven workflows
  15. 15.Data quality, master data, pipelines, and ETL/ELT
  16. 16.AI framework patterns: LangChain, LangGraph, LlamaIndex, and others
  17. 17.Multi-agent frameworks: CrewAI, AutoGen, and Semantic Kernel
  18. 18.Capstone: design an AI workflow for a real business problem
Enrol
3
Track 3 — Engineering Track

AI Infrastructure & Deployment

Know what it actually takes to ship, deploy, secure, and run AI systems in production — the engineering layer underneath the systems built in the Applied Track.

Approx. delivery11 live online classes × 90–120 minutes
ModeLive online via Microsoft Teams
Suggested learner profileGraduates of the Applied Track, engineers, technical leads, and anyone responsible for deploying, scaling, or operating AI systems in production.
View the full syllabus — 11 classes
  1. 1.Data lakes, data warehouses, and lakehouses
  2. 2.Cloud computing, GPUs, TPUs, and cloud vs. on-premises AI
  3. 3.SaaS vs. PaaS vs. IaaS, edge AI, and inference endpoints
  4. 4.Microservices, version control, and Git
  5. 5.CI/CD and DevOps for AI systems
  6. 6.Containers, Docker, Kubernetes, serverless, and AI infrastructure
  7. 7.MLOps and LLMOps
  8. 8.Observability, monitoring, and tracing
  9. 9.Workflow automation, orchestration, and business process automation
  10. 10.No-code/low-code platforms and AI pricing models
  11. 11.Capstone: map the deployment path for a real AI workflow
Enrol
4
Track 4 — Leadership Track

AI Strategy, Governance & Transformation

Lead AI adoption responsibly, evaluate opportunities and vendors, and turn AI experimentation into measurable business value.

Approx. delivery9 live online classes × 90–120 minutes
ModeLive online via Microsoft Teams
Suggested learner profileManagers, functional leaders, founders, transformation teams, risk/compliance professionals, and AI project sponsors.
View the full syllabus — 9 classes
  1. 1.Responsible AI, governance, safety, and AI risk
  2. 2.AI security, privacy, shadow AI, federated learning, and differential privacy
  3. 3.Explainability, AI bias & fairness, and human oversight
  4. 4.Compliance, audit, regulations, data privacy basics, and copyright & IP
  5. 5.AI strategy, transformation, and AI operating models
  6. 6.AI ROI, build vs. buy, and vendor evaluation
  7. 7.AI product management, AI architecture, and project management
  8. 8.Change management, Agile fundamentals, and project management for AI teams
  9. 9.Capstone: create an AI adoption roadmap for a team or organisation
Enrol

Investment

Take one, or the complete Pillar.

Each track can be taken on its own, in sequence, or as the complete Pillar I bundle. All prices are in Indian Rupees and exclude Goods and Services Tax. GST is added at the applicable rate on purchases within India; the exact tax, or that none applies, is shown before payment is confirmed. Access to each track is for a 90-day period, which begins from the date access is granted and does not renew automatically. The student rate requires a valid student identity card or an institutional email address, verified before the discount applies; where it cannot be verified, the Institute may ask for the difference or withdraw the discount.

Foundational Track
AI Fluency for Professionals
₹7,999+ GST
90 days’ access
Students save 25% — ₹5,999 + GST, with valid student ID
Applied Track
Applied AI Systems
₹10,999+ GST
90 days’ access
Students save 25% — ₹8,249 + GST, with valid student ID
Engineering Track
AI Infrastructure & Deployment
₹9,999+ GST
90 days’ access
Students save 25% — ₹7,499 + GST, with valid student ID
Leadership Track
AI Strategy, Governance & Transformation
₹8,499+ GST
90 days’ access
Pillar I Complete
All four tracks, including future releases within this pillar.
₹26,999+ GST
90 days’ access per track · saves ₹10,497 against the four tracks separately
Enrol
Student Path Students Only
Foundational, Applied, and Engineering — the complete path from AI fluency to shipped systems. Valid student ID required.
₹14,999+ GST
90 days’ access per track · saves ₹6,748 against the three student rates separately
Enrol

How the Canon is taught

Story. Principle. Tool.

Every subtopic in the Canon is delivered through the same three-part structure — because that is the only format that turns experience into transferable knowledge.

I.
A real case from practice
Every theme opens with a real case drawn from lived professional practice. Not hypothetical. Not simplified. Real situations, real failure modes, real decisions under pressure.
II.
One principle statement
The lesson the case teaches, distilled to a single sentence. This is the principle that belongs in the Canon — not the story, not the tool, but the transferable truth underneath them.
III.
One practical tool
A simple diagram, checklist, or framework that makes the principle actionable. Not software. Not a platform. A thinking tool — something you can apply on Monday morning with whatever systems you have today.

The foundation comes first.

Before you multiply your capability with AI, you must master the systems that capability runs on. The Analytical Canon is where that mastery begins.

Enter the Canon