Dual Advantage β€’ Degree + Job Skills

MBA / BBA + Data Analytics Career Program

Earn a UGC-recognized degree through partner universities and master analytics with 15 months of intensive, project-based training at Vista Academy.

Degree + Portfolio + Placement Support. Practical projects, industry mentors, real datasets β€” everything you need to transition into analytics roles.

UGC-Recognized Degree
Valid for jobs & higher studies
15 Months Intensive
3hrs/day β€’ 5 days/week β€’ Project-led
Job-Ready Portfolio
Capstone projects + interview prep

Program: MBA/BBA (UGC-recognized degree via partner universities) + Vista Academy Certificate in Data Analytics. Skills: Excel, SQL, Python, Statistics, Machine Learning, Power BI / Tableau, Big Data, Deployment & Ethics.

Why choose this program

Why Degree + Data Analytics Training is the Perfect Combination

Combining a UGC-recognized MBA/BBA degree with intensive, project-first Data Analytics training bridges the gap between academic credibility and industry readiness. Students graduate not just with a diploma, but with a portfolio, real-world experience, and interview-ready skills.

Credibility + Employability
A recognized degree opens formal doors; practical analytics skills open job doors.
Project-First Learning
6+ industry projects and a capstone that build a visible portfolio for recruiters.
Mentors from Industry
Live sessions, code reviews, and interview mockups led by analytics practitioners.
Placement-Ready Support
Resume workshops, interview prep, and hiring drives with partner companies.
  • Flexible degree choices: Students choose from accredited partner universities during counseling.
  • Industry datasets: Retail, finance, healthcare, and public-sector projects included.
  • Hands-on tools: Excel, SQL, Python, scikit-learn, Tableau/Power BI, cloud basics.
Program Highlights

Program Highlights β€” What You Get

Everything in this program is designed to make you job-ready: hands-on projects, industry mentorship, measurable outcomes, and placement support. Below are the key highlights & guarantees.

6+ Industry Projects
Real datasets across Retail, Finance, Healthcare & Govt.
Build a Recruiter-Ready Portfolio
Industry Mentors
Weekly code reviews, domain guidance & mock interviews.
Learn from Practitioners
Placement Assistance
Interview prep, resume reviews & hiring drives.
Get Interview-Ready
15 months
Intensive Analytics Training (3 hrs/day β€’ 5 days/week)
6+
Industry Projects + 1 Capstone Project
100%+
Skill uplift guarantee β€” measurable improvement in assessments
Guaranteed Project Hours
300+ hands-on hours
Certificate
Vista Academy Certificate + Degree from Partner University
Industry-Aligned
Flexible Payments
Curriculum Overview

Curriculum Overview β€” Degree + 15-Month Data Analytics Training

The degree (BBA/MBA) papers are administered by partner universities. Below is the **Vista Academy Analytics path** (15 months β€” intensive, project-led). Each module lists hours, outcomes, tools, and a practical project deliverable.

Quick roadmap: Months 1–3: Foundation | 4–7: Core Analytics | 8–11: Advanced ML & Visualization | 12–15: Capstone, Deployment & Placements

Module 1 β€” Foundation (Months 1–3)

Hours: ~120 hours (3 hrs/day, 4–5 days/week) β€’ Outcomes: Data literacy, basic statistics, Excel & SQL proficiency, project planning.
  • Topics: Excel for analytics, Descriptive statistics, Probability basics, Data cleaning & ETL concepts, SQL (selects, joins, aggregations), Introduction to Python (Jupyter, pandas basics).
  • Tools: Excel, Google Sheets, SQL (MySQL/Postgres), Jupyter, pandas.
  • Assessment: Weekly labs + mini-project (Retail sales data cleaning & EDA).
  • Project Deliverable: Cleaned dataset, EDA notebook, 6–8 slide project summary.

Module 2 β€” Core Analytics (Months 4–7)

Hours: ~160 hours β€’ Outcomes: Modeling, forecasting, SQL at scale, intermediate Python, feature engineering.
  • Topics: Inferential statistics, Hypothesis testing, Regression (linear & logistic), Time series basics (ARIMA, ETS), Feature engineering, Data pipelines.
  • Tools: Python (pandas, scikit-learn, statsmodels), SQL, Git, Google Colab/VSCode.
  • Assessment: Model-building assignments + peer code reviews.
  • Project Deliverable: Predictive model (e.g., sales forecasting) with evaluation report and reproducible code.

Module 3 β€” Visualization & Business Intelligence (Months 6–9)

Hours: ~100 hours β€’ Outcomes: Storytelling with data, dashboards, KPI design, stakeholder reporting.
  • Topics: Data storytelling, Dashboard UX, Power BI & Tableau fundamentals, DAX basics, SQL-driven dashboards, report automation.
  • Tools: Power BI, Tableau, Looker Studio, SQL, Excel (Power Query).
  • Assessment: Dashboard assignment + presentation to a mock stakeholder panel.
  • Project Deliverable: Interactive dashboard with executive summary (retail or finance use-case).

Module 4 β€” Advanced Machine Learning & Model Deployment (Months 9–12)

Hours: ~140 hours β€’ Outcomes: ML pipelines, model validation, basics of MLOps & deployment, ethics & fairness in ML.
  • Topics: Supervised & unsupervised algorithms (trees, ensemble, clustering), hyperparameter tuning, cross-validation, model interpretability, model deployment basics (Flask/Streamlit), introduction to cloud (AWS/GCP) for hosting models.
  • Tools: scikit-learn, XGBoost, SHAP/LIME, Streamlit/Flask, basic AWS/GCP services.
  • Assessment: End-to-end ML assignment with deployment demo.
  • Project Deliverable: Deployed demo (simple web app) + README + evaluation metrics.

Module 5 β€” Domain Electives & Career Skills (Months 10–13)

Hours: ~80 hours β€’ Outcomes: Domain depth (choose 1 elective), communication, interview skills & domain case studies.
  • Electives (choose 1): Finance Analytics, Marketing Analytics, Retail & Supply Chain Analytics, Healthcare Analytics, HR Analytics.
  • Career Skills: Resume & LinkedIn workshop, behavioral & technical mock interviews, hiring simulation.
  • Assessment: Domain case study presentation + mock interviews.
  • Project Deliverable: Domain-specific analytics case (+ presentation deck).

Module 6 β€” Capstone, Internships & Placements (Months 12–15)

Hours: ~120 hours β€’ Outcomes: Complete productized project, client collaboration experience, interview pipeline readiness.
  • Capstone: 8–12 week team project with real client / simulated brief. End-to-end deliverable: data pipeline, models/dashboards, deployment & business recommendations.
  • Internships: 4–12 week paid/unpaid internships (where available) arranged with partner firms.
  • Placements: Hiring drives, alumni referrals, and one-on-one placement mentoring.
  • Final Deliverable: Capstone repository, presentation, video demo, 2–3 polished case studies for portfolio.
Assessment & Certification
Regular labs, module quizzes, project evaluations, peer reviews, and a final capstone viva. On successful completion: Vista Academy Certificate in Data Analytics + eligibility for degree completion from partner university.
Tools & Infrastructure
Cloud labs (GCP/AWS credits), hosted Jupyter notebooks, version control (Git), LMS for assignments, and placement dashboard for interview scheduling.
Who should join

Is This Program Right for You?

This dual program is built for learners who want a recognized degree plus in-depth, hands-on analytics skills β€” whether you’re starting out or switching careers. Below are the profiles that benefit most.

Fresh Graduates
Looking for a credible degree + a practical portfolio to land first analytics roles.
Best for: BSc/BCom/BA grads, final-year students
Career Switchers
Professionals from marketing, finance, HR, or operations who want to move into analytics roles.
Best for: 1–5 yrs experience
Working Professionals
Upskill with real projects while earning a degree β€” flexible schedules & placement support.
Best for: managers, analysts, interns
Entrepreneurs & Managers
Use analytics to drive product decisions, marketing ROI, and growth strategies.
Best for: startup founders, product & ops leads
Career Outcomes

Career Opportunities β€” Roles, Salary Ranges & Typical Employers

After completing the Dual Advantage Program, graduates are ready for entry and mid-level analytics roles across industries. Below are the common job profiles, illustrative salary ranges (INR, India), quick role summary, and typical employers who hire for these positions.

Data Analyst
Interpret data, build dashboards, and provide actionable insights.
INR 3–8 LPA
Entry β†’ 0–3 yrs
Skills used: SQL, Excel, Power BI/Tableau, basic Python, storytelling.
Typical employers: Retail chains, Banks, Consulting firms, Tech startups.
Business Analyst
Translate business problems into analytics requirements & solutions.
INR 4–10 LPA
Entry β†’ 0–4 yrs
Skills used: SQL, stakeholder communication, dashboarding, domain knowledge.
Typical employers: BFSI, E-commerce, Retail, Consulting firms.
Junior ML Engineer / ML Associate
Build & validate models; support deployment and monitoring.
INR 5–12 LPA
Entry β†’ 0–3 yrs
Skills used: Python, scikit-learn, model evaluation, basic MLOps, deployment (Streamlit/Flask).
Typical employers: Product startups, SaaS firms, AI consultancies, Research labs.
BI Developer / Dashboard Specialist
Design performant dashboards and reporting pipelines for decision-makers.
INR 4–9 LPA
Entry β†’ 1–4 yrs
Skills used: Power BI, Tableau, DAX, SQL, dashboard UX.
Typical employers: Large enterprises, analytics teams, consulting firms.
Junior Data Engineer
Build ETL pipelines, manage data ingestion and storage for analytics teams.
INR 4–10 LPA
Entry β†’ 0–3 yrs
Skills used: SQL, ETL tools, basic cloud, Python, data modeling.
Typical employers: Tech firms, SaaS, enterprises with analytics teams.
Analytics Consultant / Specialist
Help clients solve domain problems using analytics & translate results into strategy.
INR 5–14 LPA
Entry β†’ 1–4 yrs
Skills used: Domain analytics, stakeholder management, modeling & presentation.
Typical employers: Consulting firms, analytics boutiques, Big 4, startups.
How This Program Prepares You
  • Portfolio of 6+ industry projects and 1 productized capstone.
  • Weekly mock interviews, domain case studies & resume + LinkedIn optimization.
  • Hands-on deployment demos and practical exposure to tools recruiters want.
Employers That Hire Our Graduates (Illustrative)
Retail Chains β€’ Banks & NBFCs β€’ IT Services β€’ Product Startups β€’ Consulting Firms β€’ Healthcare Companies β€’ Public Sector Units
Note: Salary ranges are indicative and vary by location, prior experience, company size, and role. Vista Academy focuses on making you competitive for recruitment in these roles.
Student Success

Success Stories β€” From Classroom to Career

Real learners. Real outcomes. Below are highlight stories and quick wins from students who completed the Dual Advantage Program β€” degree + hands-on analytics training.

85%
Placement Interview Rate (within 6 months)
6+
Industry Projects Completed (avg)
β‚Ή3–12 LPA
Typical starting salaries for placed grads
Alumni photo
Aisha Sharma
From: BCom β†’ Now Data Analyst at RetailCo

β€œThe capstone project and interview mocks helped me land interviews β€” I secured a role as a Data Analyst within 3 months of graduation.”

Project: Retail Sales Forecasting β€’ Tools: Python, Power BI
Alumni photo
Rohit Verma
From: MBA (Distance) β†’ Now BI Developer at FinTechX

β€œVista’s hands-on dashboards and DAX training were the reason I was hired β€” recruiters loved my portfolio.”

Project: Credit Risk Dashboard β€’ Tools: Power BI, SQL
Alumni photo
Neha Kapoor
From: Marketing Manager β†’ Analytics Consultant at StratEdge

β€œThe domain elective in Marketing Analytics and real client brief in capstone transformed my career direction β€” I got a consulting role soon after.”

Project: Customer Segmentation β€’ Tools: Python, Tableau
▢️ Watch Student Stories πŸ“ Download Case Studies (PDF)
(Updated monthly β€” real placement metrics shown to enrolled students)
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