Data Analytics & AI Orchestration — Check Your Eligibility

Indian School of Skills

Question 1 of 4

What best describes your current working context?

We use this to understand whether you'll apply the programme for hiring, internal growth, or a founder use case.

Question 2 of 4

How comfortable are you with data tools today?

No perfection needed. This only helps us pace your onboarding correctly.

Question 3 of 4

What's your primary goal with this programme?

We'll use this to understand which projects and portfolio path will matter most to you.

Question 4 of 4

The programme runs Saturdays & Sundays, 6:00–8:00 PM IST, with a Wednesday office hour.

Can you commit to this weekly rhythm for 6 months?

Why We Built This

Most data courses end with dashboards.
Ours ends with a decision system you can ship.

Most analytics programmes still train people for a world where dashboards were enough. Modern teams need analysts who can scope problems, automate data work, audit AI outputs, and explain decisions. So we built the programme around that reality.

🎯

Built for business-minded learners

You do not need a CS degree. We use AI-first tools to help you move from business question to analytical system without getting stuck on syntax.

🔴

Live labs, not passive tutorials

Every concept is taught live, then applied to a realistic analytics workflow: SQL, cleaning, forecasting, dashboards, and RAG.

🌐

Your capstone solves a real business problem

You finish with a company-brain style analytics agent or decision-support system that proves you can go from raw data to action.

👥

Capped at 25 for actual feedback

Small enough that your dashboards, data logic, prompts, and capstone narrative actually get reviewed.

Chirag

Founder · ISS

"Most teams aren't short on dashboards. They're short on people who can turn messy data into a trustworthy decision. That's the gap this programme closes."

📉

Reporting work is being compressed fast. Work that used to mean exporting CSVs, cleaning sheets, and summarising trends manually is exactly the kind of cognitive routine AI is now taking over first.

🧠

Analysts are moving from operators to orchestrators. The role is no longer just writing SQL or building charts. It now includes prompting, auditing outputs, semantic modeling, and building lightweight decision agents.

⚠️

Exposure is highest in business, finance, office, and computer-heavy work. That means analysts who stop at dashboards face the most pressure, while analysts who can work with AI capture the upside.

🚀

The winner is the analyst who can ship answers. Cleaning, modeling, forecasting, RAG, and executive storytelling now belong in one modern portfolio.

The analyst who only exports reports gets squeezed. The analyst who scopes, automates, audits, and explains becomes indispensable.

AI exposure is highest in analytical and office-heavy work

Source: Anthropic Labor Market Research, 2026

Theoretical coverage

Observed coverage

Data from: Anthropic — Labor Market Impacts of AI (March 2026)

Why It Matters Now

The AI-Native Analyst vs The Old Reporting Loop

Same business question. Radically different speed, depth, and value.

😵 The Old Way

⚡ AI-Native Analytics

📊 Weekly reporting

Export CSVs, clean in Excel, rebuild charts, and write commentary by hand every single week.

Manual repetition

📊 Weekly reporting

Use AI-assisted SQL, semantic definitions, and narrative generation to publish a decision-ready report in minutes.

Automated insight loop

🧹 Data cleaning

Spend hours fixing typos, nulls, outliers, and schema mismatches before you can even start thinking.

Boring and fragile

🧹 Data cleaning

Let AI suggest fixes, track lineage, generate synthetic data, and produce a gold-standard dataset with human review.

90% automated

🔮 Forecasting

One spreadsheet model, low trust, and no real visibility into bias, drift, or alternative models.

Guess-heavy

🔮 Forecasting

Run AutoML, audit the model, compare alternatives, and deploy a living forecasting or churn system.

Model-backed decisions

🗣️ Stakeholder Q&A

Someone asks a follow-up question in the meeting and you promise to "circle back" tomorrow.

Slow decision cycle

🗣️ Stakeholder Q&A

Build dashboards and RAG systems stakeholders can talk to directly, with narrative summaries and supporting evidence.

Interactive decision support

Who is this for

Different starting points. Same destination: the ability to turn messy data into decisions with AI in the loop.

*(Images are illustrative. Alumni-style personas below show the kinds of learners this programme is designed for.)*

The Ambitious Graduate

0–2 Yrs Experience · Student / Fresher

"I don't want to compete on generic resumes. I want proof that I can actually query data, automate analysis, build dashboards, and explain a business decision end to end."

Month 6 Outcome:
A portfolio with dashboards, SQL workflows, an ML project, and a capstone analytics agent.

The Corporate Upgrader

2–10 Yrs Experience · Ops / Marketing / Finance / Product

"My team still spends too much time making reports and not enough time making decisions. I want to become the person who automates the reporting layer and brings sharper insights to the room."

Month 6 Outcome:
An automated clean-to-insight workflow and a dashboard stakeholders can actually use.

The Founder or Builder

Any Experience · Founder / Consultant / Independent Operator

"I don't need another vanity dashboard. I need churn warnings, revenue forecasts, customer insights, and one daily message that tells me what actually matters in my business."

Month 6 Outcome:
A 'CEO's Personal Analyst' style capstone wired to a real business problem.

Not sure if you qualify? Our 2-minute eligibility check tells you honestly before you speak to anyone.

Programme Outcomes

What you'll actually be able to do.

Five portfolio-grade outputs that prove you can think like a modern analyst, not just operate a dashboard tool.

Level 1

Problem Scoping, Prompted SQL & Data Foundations

Deployed Output

A business-question-to-query workflow that turns vague stakeholder asks into KPIs, SQL, and auditable raw data pulls.

Cursor

BigQuery

Snowflake

Level 2

Clean-to-Insight Pipelines & Semantic Modeling

Deployed Output

A system that takes a dirty dataset and produces a gold-standard table, lineage notes, and an executive-ready summary with 90% AI assistance.

Databricks

BigQuery

Mixpanel

Level 3

Forecasting, AutoML & Model Auditing

Deployed Output

A churn, revenue, demand, or fraud model with audit notes, bias checks, and a deployment plan for real-world monitoring.

Databricks

Hugging Face Vercel

Vercel

Level 4

Dashboards, Narrative Generation & Causal Thinking

Deployed Output

A stakeholder dashboard with AI-generated executive summaries, drill-down logic, and an explanation of what changed, why it mattered, and what to do next.

Qlik

NotebookLM

Mixpanel

Level 5

Capstone: The "Company Brain" or "CEO's Personal Analyst"

Deployed Output

A RAG-powered analytics agent that answers questions from company data, surfaces the most important insight, and explains the decision in plain English.

BigQuery

Hugging Face

Supabase

Vercel

Program curriculum

The 2026 data landscape: why classical data science is shifting toward AI orchestration.

Problem scoping with LLMs: turning a business vibe into a mathematical objective.

Python for people who hate syntax with Cursor and Copilot-style workflows.

Understanding JSON, CSV, and SQL through the eyes of an LLM.

The new SQL: prompt-to-query workflows and text-to-query agents.

Statistical intuition without formulas: distributions, p-values, and simulations.

Data ethics and the hallucination trap: learning when AI is lying about your data.

Milestone Project 1: define a business problem and pull the raw data with AI-assisted SQL.

AI-powered cleaning for missing values, outliers, and messy business data.

Semantic modeling: teaching the system what revenue, churn, and margin really mean.

Feature engineering 2.0: using AI agents to suggest variables you would have missed.

Exploratory data analysis with interactive notebook-native interfaces.

Signal vs noise: isolating seasonality, trend, and real growth.

Data lineage: tracing where every metric came from.

Synthetic data generation when privacy blocks access to real user data.

Milestone Project 2: turn a dirty dataset into a gold-standard dataset with 90% AI automation.

Prediction vs classification: the big two explained simply and applied to business data.

AutoML foundations with enterprise-grade tooling to test many models fast.

Fine-tuning small language models when you do not need GPT-scale costs.

RAG systems that read your company's internal data and answer questions reliably.

Model auditing: using AI to find the bias or failure mode in another AI.

Beginner-friendly deployment with Vercel or Streamlit-style flows.

MLOps essentials: drift, monitoring, and keeping models alive after launch.

Milestone Project 3: build a company-brain style RAG system for a specific dataset.

AI dashboards that stakeholders can talk to, not just view passively.

Narrative generation: writing executive summaries people actually want to read.

Causal inference and what happens if we change X, not just what correlates with Y.

Using AI-generated visuals and infographics to explain complex decision logic.

The AI-proof resume: proving your human-in-the-loop judgment.

Live coding with AI assistants for the 2026 interview environment.

Final capstone presentation to mock stakeholders.

Graduation and future-proofing in a world where models update every week.

Foundation: E-commerce market pulse dashboard, clean-to-insight pipeline, and a dine-in revenue predictor.

Intermediate: legal-bot contract auditor, churn early warning system, and fraud detection for digital payments.

Advanced: style-match recommendation engine, synthetic healthcare twin, interview AI performance scorer, and the CEO's personal analyst agent.

Every learner chooses business-problem-led projects that demonstrate proof, not just notebook completion.

🏆

Explore the full programme syllabus

Get the session-by-session breakdown, tools, project ideas, and capstone expectations for the full 6-month journey.

Download includes: all 32 sessions, AI-first tool stack, portfolio blueprints, milestone projects, and capstone expectations.

📚 4 phases · 32 live sessions

🧪 10 project blueprints across foundation to advanced

🎓 PG Certificate on completion

Instant download · No spam

Weekly Schedule

A Cadence Built for Working Analysts

Live weekend depth, a mid-week unblock session, and structured build time for projects, datasets, and capstones.

Live Class · Saturday

Concept & Strategy Intensive

New frameworks, business cases, metric design, model thinking, and live walkthroughs of the week's core ideas.

📅 Saturday, 6:00 – 8:00 PM IST

Sat

Live Class · Sunday

Implementation Lab

We build the workflow live: AI-assisted SQL, cleaning, dashboard logic, modeling, or RAG implementation depending on the phase.

📅 Sunday, 6:00 – 8:00 PM IST

Sun

🛠️ The Analysis Sprints

Asynchronous Build Days

Use the week to clean your dataset, improve your prompts, test features, refine dashboards, and move your milestone project forward. Community support stays active while you build.

Mon Tue Thu Fri

💬 Mid-week Sync

Office Hours & Doubt Clearing

Bring blockers on SQL, data cleaning, modeling, dashboard design, capstone framing, or interview prep and get unblocked fast.

🕘 Wed, 9:00 – 10:00 PM IST

Wed

📚 Total Commitment: ~10–12 hours/week · All live sessions are recorded and uploaded to your dashboard.

What They Say

From the people building with us.

★★★★★

"I had done SQL tutorials before, but this was the first time someone showed me how to go from a vague business question to a trustworthy answer. My capstone became the strongest thing on my resume."

Nisha Verma

Recent Graduate, Delhi

★★★★★

"The biggest shift for me was learning how to automate the boring layer. I stopped spending Monday mornings patching spreadsheets and started showing up with sharper insights and better stakeholder conversations."

Karan Malhotra

Operations Manager, Bangalore

★★★★★

"The RAG and forecasting modules completely changed how I think about analytics. Instead of asking for reports, I now think in systems: what should the business know, when, and how do we deliver it automatically?"

Rahul Menon

Founder, Consumer Brand, Chennai

Your AI-native analytics toolstack

Learn the modern stack for analytics, modeling, automation, and decision support, from AI-first coding environments to warehouse and dashboard tooling.

Cursor

BigQuery

Databricks

Snowflake

Qlik

Mixpanel

Hugging Face

NotebookLM

Vercel

n8n

Make

Postman

Supabase

Postgres AI Guide

Your Credential

A certificate that proves what you can do with data.

The real signal is the body of work you finish: dashboards, cleaned datasets, predictive systems, and a capstone analytics agent. The certificate is the formal proof that those outcomes were completed to standard.

✓

Issued on completionOnly after completing the capstone and final stakeholder-style presentation.

✓

Verifiable onlineEvery certificate includes a unique ID for employer verification.

✓

LinkedIn-readyPerfect for your profile, resume, and portfolio alongside your project links.

Credential of Excellence

Post Graduate Certificate

Data Analytics & AI Orchestration

This is to certify that

Sample Student

has successfully completed the 6-month intensive programme, demonstrating proficiency in AI-assisted analytics, predictive systems, dashboard storytelling, and decision-support agents.

Verification ID: ISS-DA-2026-XXXX

Bonus Inclusions

Professional Upskilling Toolkit

Every participant receives extra support to translate project work into hiring, internal advancement, and stronger portfolio positioning.

🧭

1:1 Portfolio Strategy Call

A private call to choose the right projects for your background, career target, and desired analytical niche.

📄

LinkedIn & Resume Review

We help you frame your dashboards, forecasting work, and capstone agent as outcomes recruiters and hiring managers understand.

🎤

Capstone Presentation Rehearsal

Practice presenting your analysis to mock stakeholders so you can defend your assumptions and tell the story clearly.

👥

Lifetime Alumni Access

Stay connected to future projects, peer feedback, job postings, and free community sessions after graduation.

💬

5 Mock AI-Assisted Interviews

Prepare for the new style of analytics interview where using AI tools responsibly is expected, not forbidden.

📚

Session Recordings Forever

Every class is recorded and stays accessible, so you can revisit SQL, modeling, RAG, dashboards, and capstone material anytime.

The Difference

What sets ISS apart.

This is not just a BI course, not just a data science course, and not just an AI course. It's the operating layer between all three.

Feature	YouTube / Udemy	Big-name Bootcamps	ISS — Data Analytics & AI Orchestration
Live instruction	✗ Mostly self-paced	~ Mixed	✓ Live weekend sessions + office hours
AI-native analytics workflow	✗ Rarely integrated end to end	~ Usually tool-specific modules	✓ Core curriculum focus
Covers SQL, cleaning, dashboards, ML, and RAG	✗ Fragmented courses	~ Sometimes split into separate tracks	✓ All in one learning arc
Business-problem-led portfolio	✗ Practice exercises only	~ Mostly guided case studies	✓ 10 project blueprints + capstone
Cohort size	– Thousands	– 100–300 students	✓ Max 25 students
Resume, interview, and executive storytelling prep	✗ Usually absent	~ Generic career services	✓ Built into Phase 4
Price	Free – ₹10,000	₹1–4 Lakhs	₹69,000 (Next Cohort)

FAQ

Common Questions

Do I need a technical or engineering background?

No. This programme is built for intelligent, motivated learners coming from business, operations, finance, marketing, product, and fresh graduate contexts. We teach the technical layer through AI-first workflows so you can focus on logic and decision-making, not memorising syntax.

Is this a data science course or a data analytics course?

It starts from analytics and business intelligence, then extends into modern machine learning and agentic systems. You learn dashboards and SQL, but you also learn AutoML, RAG, model auditing, and how to build decision-support systems. So it is broader than a traditional analytics course and more applied than a pure data science course.

Will I actually learn SQL and Python if I am starting from zero?

Yes. We intentionally teach SQL and Python through AI-assisted workflows. That means you still learn the logic, but you are not stuck memorising everything from scratch before you can start solving real problems.

What kind of projects will I leave with?

Your work can include a clean-to-insight pipeline, revenue or churn predictor, dashboard with narrative generation, fraud or anomaly detector, legal document RAG bot, and a capstone like a company-brain or CEO-personal-analyst agent. We help you choose projects that fit your goals.

What happens if I miss a live session?

Every session is recorded and uploaded to your dashboard. You get permanent access. That said, the programme is designed to be most valuable when you attend live and ask questions as you build.

Can I pay in instalments?

Yes. No-cost EMI is available, and the fee can be spread over monthly payments so the programme remains accessible to students and working professionals.

Will this help me get hired?

We do not make job guarantees. What we do provide is stronger proof than most applicants have: portfolio projects, a capstone system, interview prep, resume guidance, and the ability to speak credibly about AI-native analytics workflows in front of recruiters or managers.

Still have questions? Check your eligibility first and our admissions team will help you think through fit, schedule, and goals.

Get the Full Programme Brochure

Downloading now…

What best describes your current working context?

How comfortable are you with data tools today?

What's your primary goal with this programme?

The programme runs Saturdays & Sundays, 6:00–8:00 PM IST, with a Wednesday office hour.

Data Analytics Course in Hyderabad

Most data courses end with dashboards. Ours ends with a decision system you can ship.

Dashboards are no longer enough.

The AI-Native Analyst vs The Old Reporting Loop

Who is this for

The Ambitious Graduate

The Corporate Upgrader

The Founder or Builder

What you'll actually be able to do.

Problem Scoping, Prompted SQL & Data Foundations

Clean-to-Insight Pipelines & Semantic Modeling

Forecasting, AutoML & Model Auditing

Dashboards, Narrative Generation & Causal Thinking

Capstone: The "Company Brain" or "CEO's Personal Analyst"

Program curriculum

A Cadence Built for Working Analysts

Concept & Strategy Intensive

Implementation Lab

Asynchronous Build Days

Office Hours & Doubt Clearing

From the people building with us.

Your AI-native analytics toolstack

A certificate that proves what you can do with data.

Post Graduate Certificate

Professional Upskilling Toolkit

1:1 Portfolio Strategy Call

LinkedIn & Resume Review

Capstone Presentation Rehearsal

Lifetime Alumni Access

5 Mock AI-Assisted Interviews

Session Recordings Forever

₹69,000. 25 seats. Built for real analytical work.

What sets ISS apart.

Common Questions

Do I need a technical or engineering background?

Is this a data science course or a data analytics course?

Will I actually learn SQL and Python if I am starting from zero?

What kind of projects will I leave with?

What happens if I miss a live session?

Can I pay in instalments?

Will this help me get hired?

Still have queries? Let's Connect

Request a Callback

Most data courses end with dashboards.
Ours ends with a decision system you can ship.