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Data Science & AI

Data Science with Python

Master statistics, Python, machine learning, and data visualization to become a job-ready data scientist.

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Duration
16 Weeks
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Mode
Live Online
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Projects
4 Real Projects
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Certificate
Course Completion
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EMI from
₹3,199/mo
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Who This Course Is For

  • Freshers with a quantitative background (engineering, statistics, commerce)
  • Working professionals moving into analytics/data roles
  • Python developers wanting to specialize in data

Prerequisites

  • Basic Python or willingness to learn it in the first module
  • Comfort with basic mathematics/statistics

Full Curriculum

7 modules · 110 hours of live instruction

1Python for Data Science~16 hrs
  • NumPy and pandas fundamentals
  • Data cleaning and wrangling
  • Working with CSV/Excel/SQL data sources
2Statistics & Probability~18 hrs
  • Descriptive and inferential statistics
  • Probability distributions
  • Hypothesis testing and A/B testing
3Data Visualization~10 hrs
  • Matplotlib and Seaborn
  • Building interactive dashboards
  • Storytelling with data
4SQL for Analysis~8 hrs
  • Joins, window functions, aggregations
  • Query optimization for analytics
  • Connecting SQL to Python workflows
5Machine Learning Fundamentals~24 hrs
  • Regression and classification algorithms
  • Model evaluation metrics
  • Feature engineering and selection
6Advanced ML & Model Deployment~16 hrs
  • Ensemble methods (Random Forest, XGBoost)
  • Cross-validation and hyperparameter tuning
  • Deploying models with Flask/FastAPI
7Capstone Projects~18 hrs
  • End-to-end business analytics case study
  • Predictive modeling project
  • Portfolio and interview preparation

Tools & Technologies Covered

PyPython
Pdpandas
NuNumPy
Skscikit-learn
MpMatplotlib
SQLSQL
JnJupyter
TaTableau (intro)
GiGit

Hands-On Projects

Capstone

Customer Churn Prediction

End-to-end classification pipeline predicting subscription churn with business recommendations.

pandasscikit-learn
Intermediate

Sales Forecasting Dashboard

Regression-based forecasting model paired with an interactive visualization dashboard.

pandasMatplotlib
Intermediate

A/B Test Analysis

Statistical analysis of a simulated product experiment with significance testing and reporting.

StatisticsPython
Learning Outcomes

What You'll Be Able to Do

Clean, analyze, and visualize real-world datasets using Python
Apply statistical methods to draw valid conclusions from data
Build and evaluate machine learning models for classification/regression
Present data-driven insights through dashboards and reports

Frequently Asked Questions

Do I need a math/statistics background to join?

A basic quantitative background helps, but the Statistics & Probability module is taught from fundamentals within the course.

Is Python taught from scratch here too?

The Python for Data Science module covers what you need for this course; if you have zero programming background, we recommend our standalone Python Programming course first.

What is the batch schedule?

Weekday batches run 7-9 PM IST; weekend batches run Saturday-Sunday 10 AM-1 PM IST, recorded for lifetime access.

Data Science vs Machine Learning course — what is the difference?

This course covers the full data science workflow (stats, analysis, visualization, and applied ML); our Machine Learning course goes deeper into algorithms, deep learning, and model optimization for those specializing further.

Is placement support included?

Yes — resume building, mock interviews, and referrals to our hiring partner network are included.

What salary can I expect after this course?

Freshers with strong project portfolios typically start at ₹5-8 LPA in analyst/junior data scientist roles; experienced professionals switching from adjacent roles often see larger jumps.

Ready to Start Data Science with Python?

Next batch enrolling now — live online, with placement support included.

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