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Data Science Course – Turn Data Into Decisions

What Is This Data Science Course About?

 Every company sits on a mountain of data — sales numbers, customer behaviour, website clicks. Most of them don’t know what to do with it. This course trains you to be the person who does.

Somewhere right now, a company is trying to figure out why sales dropped last quarter, or which customers are about to leave, or what product to launch next. The answer is buried in their data — someone just needs to dig it out.

That’s what a data scientist does. This course takes you from the basics of Python and statistics all the way to machine learning models that actually predict outcomes. You won’t just learn formulas — you’ll work on real datasets, build real models, and learn to explain what the numbers mean to people who aren’t data experts.

By the end, you’ll be able to walk into a business problem, pull the right data, build a model, and hand over an answer that helps someone make a decision.

Benefits

What You'll Learn

Course Details:

Course Price:

$1500

Lesson Duration

12 Weeks

Places for Students

12

Language:

English, Spanish, French

Certifications

Digital, Physical

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Career Outcomes

Where This Course Can Take You

Every industry now runs on data-driven decisions. Once you complete this course, you can move into roles like:

Average Salary of
Data Scientists

₹5L – ₹9L ₹10L – ₹18L ₹16L – ₹28L Fresher 3+ Years 5+ Years

In-Demand Roles

Data Scientist Machine Learning Engineer Data Analyst Business Intelligence Analyst Data Science Consultant

Upcoming Batches

Your next batch is almost here

Pick the mode that fits your schedule — same curriculum, same mentors, same outcomes.

Weekday 18 seats left

Full Stack Development

Starts Aug 3 7:00 – 9:00 AM

Mon – Fri  ·  Live Interactive Classes

Reserve This Batch
Weekend 9 seats left

Full Stack Development

Starts Aug 8 10:00 AM – 1:00 PM

Sat – Sun  ·  Live Interactive Classes

Reserve This Batch
Weekday 12 seats left

Full Stack Development

Starts Aug 5 9:00 AM – 12:00 PM

Mon – Fri  ·  Chennai Campus

Reserve This Batch
Weekend 6 seats left

Full Stack Development

Starts Aug 10 2:00 – 5:00 PM

Sat – Sun  ·  Chennai Campus

Reserve This Batch

Tools You'll Use

Not just tool names — real, working skills

Explore what you'll actually do with each tool in your data science stack.

Python
PythonWrite data pipelines and analysis scripts
Jupyter
Jupyter NotebookExplore data and prototype models interactively
Pandas
PandasClean, transform & analyze structured data
Scikit-learn
Scikit-learnBuild & evaluate machine learning models
TensorFlow
TensorFlowTrain deep learning & neural network models
PyTorch
PyTorchBuild flexible deep learning architectures
Power BI
Power BIBuild dashboards to present your findings
Tableau
TableauCreate interactive, shareable data visuals
Plotly
PlotlyBuild interactive charts directly in Python
AWS
AWSDeploy and host trained models
Docker
DockerPackage models for consistent deployment
Generative AI
GenAI ToolsUse LLMs for analysis, code & RAG pipelines

Admissions Open

Your Next Career Starts With
One Decision.

Seats for the next batch are limited. If you've been thinking about a career in digital marketing, this is the moment to stop thinking and start learning.

Learners already building new careers

Seats filled 10/15

Only 5 seats left for this batch

Reserve My Seat Download Curriculum

Zero-cost EMI  ·  7-day refund policy

Course Curriculum

Master Data Science, module by module

From Python and statistics to Generative AI and MLOps — a curriculum built for how data teams work in 2026.

7Modules
14Weeks
55+Practical Lessons
  • Python basics — variables, loops, functions, OOP
  • NumPy & Pandas for data handling
  • Probability theory & distributions
  • Hypothesis testing, correlation & regression basics
  • Data cleaning & exploratory data analysis
  • Power BI & Tableau for storytelling with data
  • Data wrangling with Pandas
  • Regression, classification & clustering algorithms
  • Model evaluation — accuracy, precision, recall, F1, ROC-AUC
  • Cross-validation & hyperparameter tuning
  • Scikit-learn hands-on practice
  • Neural network fundamentals
  • TensorFlow, Keras & PyTorch basics
  • CNNs for image data, RNNs for sequential data
  • Introduction to Large Language Models (LLMs)
  • Prompt engineering fundamentals
  • Retrieval-Augmented Generation (RAG) basics
  • Using GenAI tools for code generation & analysis
  • Model deployment basics (Flask/FastAPI)
  • Model monitoring & drift detection
  • CI/CD concepts for ML pipelines
  • AutoML tools for automated model selection
  • End-to-end project — data collection to deployed model
  • Model building, evaluation & deployment
  • Presenting insights to a non-technical audience

Career Outcomes

Placement Partners

Our learners get placed at these companies — real hiring partners, not a wishlist.

TCSTCS InfosysInfosys WiproWipro AccentureAccenture CognizantCognizant CapgeminiCapgemini HCLTechHCLTech Tech MahindraTech Mahindra IBMIBM OracleOracle DeloitteDeloitte AmazonAmazon MicrosoftMicrosoft GoogleGoogle

Delivery Framework

How the Programme Works

  1. Step 1

    Explore an interactive step-by-step journey.

  2. Step 2

    Guided onboarding and basics

  3. Step 3

    Expert-Led Structured modules

  4. Step 4

    Hands-On Practice

  5. Step 5

    Industry Tool Mastery

  6. Step 6

    Portfolio and interview prep

Career Journeys — Success Stories
Real Outcomes

Every ticket tells a career transformation

From where they started to where they landed — mentored, upskilled, and placed with confidence.

Got Questions?

Everything you need to know

Course details, career outcomes, market demand, and placement support — all in one place.

You'll cover SEO, GEO/AEO (AI search optimization), Google & Meta Ads, social media marketing, email marketing, analytics, and a full capstone campaign — 12 modules in total, from fundamentals to execution.

Yes. Module 1 starts from the basics of how digital marketing works — no prior marketing or technical background is assumed.

The full program runs 16 weeks across 12 modules, with both weekday and weekend batch options, online or offline.

Yes — every module includes practical exercises, and the course ends with a capstone project: a real multi-channel campaign you plan, execute, and report on end-to-end.

Roles like SEO Executive, Performance Marketing Executive, Social Media Marketer, Content Marketer, and Digital Marketing Associate are all realistic starting points.

Yes — many learners join from non-marketing backgrounds. The curriculum is built to take you from zero to job-ready without assuming prior experience.

No coding required. Basic familiarity with tools like Google Analytics or spreadsheets helps, but you'll pick that up naturally during the course.

Most start as an Executive/Associate, move to Senior Executive within 1–2 years, then into Team Lead or Specialist roles (SEO Lead, Paid Media Manager) as experience builds.

Yes — the channels are evolving (AI search, privacy-first targeting), but the function itself isn't going away. Businesses of every size still need people who can plan, run, and measure marketing.

AI is automating repetitive execution work, which is exactly why this course includes GEO/AEO and AI-assisted workflows — so you're trained on the skills AI can't easily replace, like strategy, judgment, and campaign oversight.

Practically every industry — e-commerce, healthcare, education, SaaS, real estate, and agencies serving all of the above. It's one of the more portable skill sets across sectors.

Yes — many learners freelance or join agencies right after, since the skills (SEO, ads, content, analytics) are exactly what small businesses hire freelancers for.

Yes — resume reviews, mock interviews, and direct referrals into our hiring partner network are included as part of the program.

We provide active placement support, not a guaranteed offer — outcomes depend on your portfolio, interview performance, and market conditions at the time you complete the course.

Resume and interview prep begin around Module 9, so you're ready to start applying as soon as you finish the capstone project — not months afterward.

Placement support isn't a one-time referral — you continue to get access to new openings, mentor check-ins, and mock interview practice until you land a role.

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