In the 5 Day Data Science Workshop, you will attend LIVE sessions with your mentor. The structure will be code-along, a mix of hands-on coding, concept onboarding, and walkthroughs. By the end of 5th Day you will have a social presence among your recruiters. You can join at any time and get instant access to the upcoming batch and receive timely invites to attend sessions.

What we offer:

  • 8.5 hours of online training across 5 live mentor sessions
  • 1 Industry-relevant Capstone project on Kaggle
  • Certificate of Completion
  • Bonuses for free
  • Cohort learning & networking - collaborative learning along individuals with similar ambitions & interests


We will not leave you just with the 5 Days of LIVE learning. By the end of this workshop we will give you a Toolkit for your journey in Data Science.

  • Get 10 Jupyter Notebooks consisting of industry relevant models based on available datasets, delivered in your inbox - Delivered 1 per week. Beginner friendly yet an in-depth level of execution.
  • Access to Data Science Toolkit - 30+ course modules to keep you on track after course completion.
  • Community access - Experience the motivation around you on our channel. After all, we learn the most through our peers.
  • 30 Day Data Science Study Plan. What are you going to do over the next 30 days? Day by Day plan. Daily Goals. Stretch Goals and revision plans..
  • Step-by step direction on how you should spend the first 20 hrs learning this new skill DIY.

Capstone Project in a nutshell:

Predict house prices and trends based on real-life features and parameters for a real-estate agency.


Day 2 - Data Cleaning, Preprocessing & Exploration

  • Load and Prepare dataset
  • Check Numeric & Categorical Features
  • Check Missing Data
  • Fill null values in continuous features
  • Check for Class Imbalance
  • Detect & treat outliers
  • Univariate & Bivariate analysis of Categorical & continuous columns

Day 3 - Model Building and Insights

  • Applying models on the data
  • Function to Label Encode Categorical variables
  • Fit Regression models
  • Linear Regression
  • Decision Tree Regressor
  • Random Forest Regressor
  • Feature Selection
  • Grid-Search | Hyperparameter Tuning
  • Prediction on the test data

Day 4 - Kaggle Showcase, Blogging and Presentation

  • Presentation to the stakeholders
  • Creating your first Project on Kaggle
  • How to choose and build your portfolio projects?
  • What are the ideal qualities of a portfolio project?
  • How to showcase your portfolio projects to the world (and potential recruiters)?
  • Live Q&A on Data Science

Day 5 - Interview Guides and Career Preparation

  • Careers in Data Science
  • Success Recipe for Data Science
  • What does a Data Science Interview look like?
  • Set you up for Data Science Learning beyond the 5 day workshop
  • Recommended Books
  • Tools to help you
  • Build your Learning kit