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Data Science
Offline Session
intermediate Level

Applied Data Science & Predictive Analytics

Extract insights from real-world datasets using Pandas, NumPy, and Scikit-Learn models.

Date
Saturday, 01 Nov 2026
Duration
4 Hours Live
Enrolled
29 Students

Workshop Overview

Step into the shoes of a data analyst and ML engineer. Clean messy telemetry data, engineer features, evaluate statistical correlations, and deploy a predictive classification model that predicts user retention with explainable metrics.

What You Will Learn & Build

✓Clean, normalize, and visualize real-world tabular data using Pandas and Seaborn
✓Engineer domain-specific features and detect multicollinearity
✓Train, cross-validate, and tune gradient boosted decision trees
✓Generate actionable business insights with ROC-AUC and confusion matrices

Prerequisites & Requirements

  • Comfortable with Python syntax and Jupyter Notebooks
  • Basic high-school statistics knowledge

Session Delivery Format

In-Person Classroom Lab

Smart Skill Learning Lab, HSR Layout Sector 2, Bengaluru

Hands-on live project mentoring included

Meet Your Mentor

Dr
Dr. Elena Rostova
AI Research Lead & Engineer • Cognitive Synthetics

Former ML researcher turned applied AI engineer specializing in predictive analytics.

Workshop Fee
₹599Inclusive of all materials
Registered Learners29 / 35

Instant confirmation • In-app calendar update • Live room pass

Included in This Program
Live Interactive Session with Mentor Q&A
Hands-on Capstone Deliverable & Repo Review
Cohort Peer Discussion Channel

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