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Data & AI

Data Science — Python, ML & Statistics, Taught Project-First.

Industry-aligned curriculum. Three real projects. Job-ready in 16 weeks — taught by data scientists who ship models, not just slides.

16 weeks Online + Offline Beginner-friendly
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Data science neural network visualization
Avg Salary
₹5–10 LPA
Demand in India
+33% YoY
Hiring
Infosys · TCS · Wipro · Mu Sigma · Tiger Analytics
Curriculum

What You'll Learn

Eight modules, sixteen weeks — every concept reinforced by working code on a real dataset.

  • Setup: Jupyter, VS Code, virtualenvs
  • Syntax, control flow and functions
  • OOP basics — classes data scientists actually write
  • List/dict comprehensions for data transforms
  • Error handling and clean code patterns
  • Descriptive vs inferential statistics
  • Probability distributions: normal, binomial, Poisson
  • Hypothesis testing and p-values, demystified
  • Confidence intervals and effect size
  • A/B test design from the ground up
  • NumPy arrays, broadcasting and vectorization
  • Pandas Series and DataFrames in depth
  • Joins, group-bys and pivot tables
  • Handling missing values and outliers
  • Time-series basics and resampling
  • Matplotlib essentials and figure anatomy
  • Seaborn for statistical visualizations
  • Plotly for interactive dashboards
  • Choosing the right chart for the question
  • Publication-grade figure polish
  • Supervised vs unsupervised learning
  • Linear, logistic, tree-based models
  • Cross-validation and hyperparameter tuning
  • Feature engineering — the real edge
  • Model evaluation: ROC, PR, calibration
  • Perceptrons and backpropagation, intuitively
  • Building feed-forward nets in Keras
  • CNNs for image classification
  • Transfer learning with pretrained models
  • Training, regularization and overfitting
  • Tokenization, stemming, lemmatization
  • TF-IDF and word embeddings
  • Sentiment classification end-to-end
  • Named-entity recognition with spaCy
  • Intro to transformer-based models
  • Project 1: predictive analytics for a retail dataset
  • Project 2: customer-churn classifier with explainability
  • Project 3: NLP sentiment app, deployed
  • Resume rebuild and GitHub portfolio polish
  • Mock interviews with hiring panelists
Meet Your Trainer

Taught by someone who ships, not just speaks.

VS

Vikram S.

Lead Data Scientist · 9+ Years

Nine years shipping ML across e-commerce, fintech, and ad-tech. Has built recommendation systems for two unicorn startups and forecasting models for a Fortune 100 retailer. Trained 500+ data scientists now placed at TCS, Tiger Analytics, Mu Sigma and product companies.

in · View on LinkedIn →
Tools & Technologies

The full data science toolkit, hands on.

Logos shown as text-style placeholders pending official permissions.

Python
Jupyter
Pandas
NumPy
Scikit-learn
TensorFlow
SQL
Tableau
Where You'll Land

Roles our Data Science alumni step into.

Data Scientist

₹6–12 LPA

Build models that solve business problems — ideation to production, end to end.

ML Engineer

₹8–15 LPA

Productionise models — pipelines, deployment, monitoring, and the boring bits that keep ML alive.

Data Analyst

₹4–7 LPA

Surface insights from data, build dashboards, drive decisions across the business.

Research Analyst

₹5–9 LPA

Run experiments, analyse outcomes, write the reports leadership reads on Monday.

FAQ

Quick answers, no fluff.

No. We start from absolute Python basics in week one. By week three you'll be writing your own analysis scripts. Statistics is taught from first principles, no math degree assumed.
Yes — a Sunadh completion certificate after the three capstones, plus we prep you for the official Microsoft DP-100 (Azure Data Scientist Associate) certification.
We offer 100% placement assistance — interview prep, resume reviews, and intros to 500+ hiring partners. We don't promise a job, but we set you up to land one.
Course starts from ₹39,999. No-cost EMIs available across major banks. Talk to a counselor for the latest plan and any active discounts.
Yes. Every Data Science batch runs hybrid — attend in classroom one week, online the next. Switch as your schedule needs, no extra fee.
Every session is recorded and shared the same evening. You can also sit in any other ongoing batch to recover that topic in person.
Yes — three full portfolio projects by week sixteen, deployed and on GitHub, with code reviews from your trainer.
New weekday and weekend Data Science batches start every two weeks at both Ameerpet branches. Book a free demo and we'll share the next start date.