10,000+Skillsbiz learners trained
Data Analytics + Gen AI · Enrolments open
Build the skills to analyse data and communicate clear decisions.
Learn to clean, query and analyse structured data with Excel, SQL and Python; create dashboards in Power BI and Tableau; and use GenAI responsibly across the analytical workflow.
✓Live online✓Weekly 1:1 mentorship✓Maximum 20 learners
Program fee
₹1,10,000+ GST · EMI options availableApplied learning
8 projectsincluding a final capstoneProgram duration
6 months
The complete journey includes teaching, practice, assessments, projects and career preparation.
Structured curriculum
18 weeks · 6 modules
From analytics foundations through capstone and portfolio development.
Applied learning
8 projects
Realistic Indian business contexts using public or synthetic datasets.
Program fee
₹1,10,000 + GST
Pay through up to 12 zero-interest EMIs, subject to final provider terms.
4.8/5Skillsbiz learner rating
8Projects in every program
20Maximum learners per cohort
Small live cohorts
Every cohort is limited to 20 learners to support interaction, questions and individual attention.
Flexible batch options
Choose from monthly weekday or weekend cohorts delivered live online.
Eight portfolio projects
Apply the curriculum through realistic briefs, documented case studies and a final capstone.
Weekly 1:1 mentorship
Review concepts, project decisions and your learning progress in recurring individual sessions.
90-day career support
Prepare your resume, LinkedIn profile, portfolio and interviews with structured support after completion.
Long-term learning access
Keep lifetime access to learning materials and revisit class recordings for 12 months after completion.
From enrolment to career preparation
A structured path from foundations to portfolio-ready work.
The pace varies by program, but every pathway follows the same sequence: establish direction, build core skills, complete reviewed work and prepare to present it professionally.
Program start
01Establish your direction
Assess & Plan
Review your starting point, target roles and program expectations before beginning the core curriculum.
BaselineRole directionLearning plan
Core curriculum
02Build the fundamentals
Learn & Practise
Develop technical and analytical fluency through live classes, guided exercises and regular mentor reviews.
Live classesGuided practiceMentor reviews
Project phase
03Apply what you learn
Build & Review
Complete eight realistic projects, strengthen them through feedback and document the clearest work for your portfolio.
Case studiesWritten feedbackPortfolio
Final phase + 90 days
04Prepare for opportunities
Present & Apply
Refine your resume and LinkedIn profile, complete three mock interview rounds and receive 90 days of placement assistance.
ATS resumeMock interviewsPlacement support
Who this pathway is for
Designed for people moving into practical analytical work.
This program suits learners who want to work with structured data, answer recurring business questions, build dashboards and present evidence-based recommendations.
Deciding between Data Analytics and Data Science?
Choose Data Analytics + Gen AI when analysis, reporting and insight communication are central to your goal. Choose Data Science & AI when advanced modelling, machine learning and deeper mathematics are essential to the work you want to pursue.
Students and recent graduates
Turn academic knowledge into reviewed analytical projects you can present in applications and interviews.
Career startWorking professionals expanding their toolkit
Add SQL, Python and modern reporting capability to experience in operations, MIS, finance, sales or business teams.
UpskillCareer switchers entering analytics
Build technical confidence through a sequence that begins with analytical thinking before progressing into SQL and Python.
Career switchBusiness professionals strengthening decision support
Learn to connect metrics, analysis and visual evidence to a clear recommendation for stakeholders.
Decision supportWhat you will learn
Develop capability across the complete analyst workflow.
By completing the curriculum and project work, you will learn how to frame questions, prepare data, conduct analysis, build reports and communicate defensible conclusions.
01 / FRAME
Turn vague business questions into analytical questions.
Clarify the metric, grain, comparison, assumptions and data required before touching a dashboard.
Proof: analysis brief + metric logic
02 / WORK
Prepare and interrogate structured data with confidence.
Use spreadsheets, SQL and Python to clean, combine, inspect and transform data into analysis-ready form.
Proof: reproducible data workflow
03 / SEE
Choose visuals that reveal the decision, not decorate it.
Build reports and dashboards where hierarchy, comparison and context make the important signal obvious.
Proof: dashboard + reporting narrative
04 / EXPLAIN
Defend an insight with statistics and a clear business story.
Separate observation from inference, communicate uncertainty and connect evidence to a practical recommendation.
Proof: executive-ready analysis story
Understand what data analytics can answer, distinguish common data types and convert a business problem into a structured analytical investigation.
Key topics
Introduction to Data AnalyticsStatistical FundamentalsData Types and StructuresBusiness Problem Framing
Applied work: write an analysis brief defining the decision, metrics, data grain and questions before analysis begins.
Develop reliable spreadsheet and query habits for cleaning, validating, summarising, joining and extracting structured data.
Key topics
Advanced ExcelPivotTablesPower QuerySQL queryingJoins & aggregationsDatabase design fundamentals
Applied work: transform a raw operational dataset into a clean, queryable analytical table and produce a concise findings summary.
Use Python to load data, inspect quality, transform columns, calculate metrics, explore patterns and reproduce analytical work.
Key topics
Python foundationspandas workflowsNumPy essentialsData cleaningExploratory analysisReusable notebooks
Applied work: create a readable notebook that takes a dataset from raw import through exploration to documented findings.
Design charts, dashboards and reports that help stakeholders understand what changed, why it matters and where to investigate next.
Key topics
TableauPower BIChart selectionVisual hierarchyVisual storytellingExecutive reporting
Applied work: create an interactive reporting view with clear metric hierarchy, drill-down logic and a stakeholder walkthrough.
Use inferential methods to compare groups, test assumptions and communicate findings without overstating what the data proves.
Key topics
Inferential statisticsHypothesis testingA/B testingSampling & uncertaintyStakeholder communicationBusiness storytelling
Applied work: prepare a decision memo combining statistical evidence, caveats, visual context and a practical recommendation.
Complete an end-to-end capstone that brings together problem framing, data preparation, analysis, reporting and business communication.
Key topics
Capstone scopingCase-study writingGitHub & portfolio developmentProject presentationDocumentationCareer preparation
Applied work: present a portfolio-ready capstone package with documented analysis, final recommendations and an interview walkthrough.
GenAI
Analytics Layerassist the workflow
without replacing judgement
Analytics Layerassist the workflow
without replacing judgement
Explore fasterGenerate starting questions, query drafts and alternative analytical angles.
Document betterTurn notebook logic and dashboard decisions into clearer explanations.
Challenge findingsUse AI to surface counter-questions, edge cases and assumptions worth checking.
Communicate efficientlyDraft stakeholder summaries while keeping the analyst responsible for factual validation.
Where GenAI fits
Use GenAI to support analysis without outsourcing judgement.
Learn where AI can help with exploration, code drafts, documentation and communication while you remain responsible for data quality, query logic, validation and the final recommendation.
Prompt with sufficient context
Provide the schema, constraints, metric definitions and intent so generated SQL, Python or commentary begins from a useful frame.
Validate every generated analytical step
Check joins, filters, assumptions, calculations and citations before anything becomes part of a report or recommendation.
Use GenAI to improve explanation quality
Refine structure, simplify technical language and generate alternative narratives — while preserving the facts your analysis actually supports.
Eight portfolio projects
Apply the curriculum to realistic analytical briefs.
Work with public or synthetic datasets in realistic Indian business contexts. Each project develops a specific part of the analyst workflow, culminating in an end-to-end capstone.
RetailPROJECT 01
Store & Category Performance Dashboard
Analyse revenue, category mix, store performance and seasonal patterns in a multi-location retail dataset.
Decision focus: identify the stores and categories that require management attention and explain the evidence.
ExcelSQLPower BI
Digital ProductPROJECT 02
User Activation & Cohort Analysis
Track how new users move through onboarding and compare conversion and retention across acquisition cohorts.
Decision focus: locate the strongest evidence of friction and propose the first intervention to test.
SQLPythonTableau
OperationsPROJECT 03
Service Queue & Resolution Analysis
Examine ticket volumes, ageing, categories and resolution patterns to separate workload pressure from process bottlenecks.
Decision focus: determine where capacity, workflow changes or deeper diagnosis are required.
ExcelPythonPower BI
People AnalyticsPROJECT 04
Workforce Retention Indicators
Investigate tenure, role, location and engagement patterns while distinguishing correlation from causation.
Decision focus: identify signals that merit attention and communicate the limits of the analysis.
SQLPythonStatistics
MarketingPROJECT 05
Campaign & A/B Test Evaluation
Compare campaign segments and experiment results using conversion, cost and statistical-significance measures.
Decision focus: decide whether the observed improvement is meaningful enough to support rollout.
ExcelPythonStatistics
Supply ChainPROJECT 06
Inventory & Fulfilment Review
Analyse stock levels, demand patterns, fulfilment time and regional performance across an operations dataset.
Decision focus: highlight stock risks and service issues that require operational action.
SQLPower BIExcel
FinancePROJECT 07
Budget & Variance Analysis
Compare planned and actual performance across business units, cost categories and reporting periods.
Decision focus: explain material variances and prioritise the questions management should investigate.
ExcelSQLTableau
CapstonePROJECT 08
End-to-End Business Analytics Case Study
Frame a business problem, prepare the data, complete the analysis and present a dashboard with documented recommendations.
Decision focus: defend your analytical choices, limitations and final recommendation in a portfolio presentation.
SQLPythonBI
Program toolkit
Build fluency across the analyst’s core tools.
Learn each tool in the context of a practical analytical task—from preparing and querying data to building dashboards, testing conclusions and documenting your work.
Excel
SQL / PostgreSQL
Python
Pandas
NumPy
Jupyter
Power BI
Tableau
GenAI toolsLearning & career support
Structured support throughout and beyond the program.
Receive individual guidance while you learn, written feedback as you build and practical career preparation as you begin presenting your work to employers.
Live learning support
Stay connected to the curriculum through live teaching, recordings and long-term access to learning support.
Weekday and weekend live batchesRecordings for 12 months after completionLifetime learning-material accessFive years of structured doubt support
Mentorship & project review
Work directly with a mentor to strengthen your understanding, analytical reasoning and portfolio presentation.
Weekly one-to-one mentorshipWritten feedback on portfolio workReviewed capstone and case studiesRepeat-batch access for up to five years
Career preparation
Prepare to present your background and project work clearly during applications and interviews.
Resume, LinkedIn and portfolio guidanceThree mock interview roundsOne-year internship pathway and LOR90 days of active placement assistance
Career direction
Roles where analytical clarity matters.
These are role directions the curriculum can prepare you toward — not guaranteed job outcomes. Your eligibility depends on prior experience, portfolio quality, interview performance and the hiring market.
Data Analyst
Query, analyse and communicate performance data for product, operations, growth or business teams.
Business Intelligence Analyst
Build recurring reporting layers, dashboards and metric systems that improve visibility for decision-makers.
Reporting / MIS Analyst
Own structured reporting processes, data preparation and recurring operational analysis with stronger automation capability.
Analytics Associate
Support analysis, experimentation, dashboards and insight generation while continuing to build domain and technical depth.
SDSSchool of Data Science · Skillsbiz Education
Certificate of Completion
Data Analytics + Gen AI
Issued and digitally verifiable by Skillsbiz Education after the program completion requirements have been met.
Skillsbiz Education certificate
Receive a digitally verifiable program certificate.
After meeting the completion requirements, you will receive a Certificate of Completion in Data Analytics + Gen AI, issued and digitally verifiable by Skillsbiz Education.
✓Records the specific program completed.✓Issued by Skillsbiz Education.✓Verifiable through the official Skillsbiz certificate portal.
Certificate verification: Use the official Skillsbiz Education portal to verify certificates issued by the company. Open verification portal ↗
Program FAQs
Questions before choosing Data Analytics + Gen AI.
Review the starting requirements, duration, fees, learning format and career support before you apply.
Compare all four programsThe pathway starts with analytics foundations and spreadsheet/SQL work before Python becomes a major part of the sequence. That makes it a more approachable technical entry point than Data Science & AI. You will still need consistent practice when the curriculum reaches SQL and Python.
The program runs across six months, with 18 weeks of structured curriculum delivered through six sequential modules. The wider journey includes scheduled teaching, guided practice, assessments, eight projects, capstone work and career preparation.
Data Analytics puts more emphasis on hands-on querying, data preparation, analysis and reporting. Business Analytics is better suited to learners who want the centre of gravity closer to business metrics, KPI design, commercial context and strategy-oriented recommendations.
The core curriculum focuses on data analysis rather than advanced machine learning. If your target work requires predictive modelling, deep learning, computer vision or MLOps, compare the Data Science & AI program.
The program fee is ₹1,10,000 + GST, with up to 12 zero-interest EMIs available. New live online cohorts begin monthly, with weekday and weekend batch options. Admissions will confirm the current timetable and payment-provider terms before enrolment.
Career support includes resume, LinkedIn and portfolio guidance, three mock interview rounds, job-portal access, referrals and placement drives, followed by 90 days of active placement assistance. These services support your job search but do not guarantee employment.
Yes. After meeting the completion requirements, you will receive a Certificate of Completion in Data Analytics + Gen AI, issued and digitally verifiable by Skillsbiz Education.
Ready to build practical data analytics capability?
Apply now, book a free counselling session or request the detailed brochure to review the curriculum, projects, fee and next available batches.
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Tell us about your background and target role.
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