Overview

  • Key Learnings

    Gain holistic understanding of Python programming, state-of-the-art machine learning algorithms and their implementation in Python.

  • In-Class Kaggle Competition

    Participate in an in-class Kaggle Competition and get a chance to win exciting rewards by solving the problem using machine learning.

  • Certificate

    Earn a certificate after completion of training. With this comprehensive bootcamp, become a certified Data Scientist and take your career to new dimensions.

Rewards & Opportunities

  • Paid Summer Internship

    Top 5 winners of the Capstone Project will be guaranteed paid summer internships at our reputed hiring partners and top MNCs

  • Full Refund

    Top 10 winners will be given full refund of the charges incurred before training

  • Contribute & Earn

    Top 15 winners will be given the opportunity to contribute through interesting Data Science blogs and earn lucrative rewards

Top Hiring Partners

Curriculum

  • 1

    Data Science in Industrial Setup - Why, What, How?

  • 2

    Python - Essential Toolkit for a Data Scientist

    • Exploring Data Types in Python

    • Strings

    • Boolean Variables

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 3

    Basic Units of the Python Universe

    • Introduction to Lists

    • List Indexing & Slicing

    • List Functions & Methods

    • Tuples

    • Sets

    • Dictionary Objects

    • Indentation in Python

    • If elif else statements

    • For Loop

    • While Loop

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 4

    Introduction to Methods & Functions

    • Methods

    • Functions

    • Scope

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 5

    Writing Production Grade Code

    • What is Production Environment?

    • Object Oriented Programming

    • Methods

    • Error & Exception Handling

    • Real World Example

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 6

    Facing off with Linear Algebra

    • Linear Algebra & Its Applications

    • Vectors

    • Matrices

    • Reference files

    • Lecture Materials & Practise Assignment

    • Additional Reading Material

    • Practise Quiz
  • 7

    Calculus

    • Introduction to Calculus

    • Reference files (PDF)

    • Additional Reading Material

    • Practise Quiz
  • 8

    Probability Theory

    • Concepts in Probability

    • Random Variables and its Types

    • Probability Mass Function

    • Probability Density Function

    • Additional Reading Material

    • Practise Quiz
  • 9

    Statistics - Measures of Central Tendency & Spread

    • Measures of Central Tendency

    • Measures of Spread

    • Symmetry and Skewness

    • Reference files(ppt)

    • Mean, Median, Mode, Variance & IQR - Python Implementation

    • Additional Reading Material

    • Practise Quiz
  • 10

    Statistics - Hanging in with Statistical Distributions

    • Discrete Statistical Distributions

    • Continuous Statistical Distributions

    • Additional Reading Material

    • Practise Quiz
  • 11

    Statistics - Covariance, Correlation & Chi-Squared

    • Explanatory vs Response Variable

    • Covariance & Correlation

    • Chi - Squared

    • Reference files (PPT & Chi - Squared table)

    • Practise Quiz
  • 12

    Numpy - Operations on Arrays

    • Why Numpy

    • List vs Array

    • Array Inspection

    • Placeholders

    • Array Indexing and Slicing

    • Array Manipulation

    • Basic Operations

    • Real World problem: Operations on Image

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 13

    Pandas - Chug Data, Spit Frames

    • Pandas package - Introduction

    • Introduction to Series and Data Frame

    • Load csv, xlsx and json format

    • Saving file to location

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 14

    Pandas - Operations on Dataframes

    • Data Frame Inspection

    • Indexing and Slicing

    • Manipulating Columns

    • Merging dataframes

    • Unique and missing values

    • Groupby

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 15

    Matplotlib - Data Visualization

    • Matplotlib & Seaborn : Worth 1000 words

    • Line Plot

    • Bar Plot

    • Box Plot

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 16

    Seaborn - Data Visualization

    • Histogram

    • Understanding Correlation

    • Correlation Heatmap

    • Two-way plots

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 17

    Machine Learning Essentials

    • Machine Learning Overview

    • Supervised Learning

    • Unsupervised Learning

    • Reinforcement Learning

    • Steps for Supervised Machine Learning Modelling

    • Deep Dive in Supervised Machine Learning Modelling

    • Effective approach for training any Machine Learning algorirthm

    • Practise Quiz
  • 18

    Linear Regression

    • Linear Regression

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 19

    Multiple Linear Regression

    • Multiple Linear Regression

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 20

    Logistic Regression

    • Logistic Regression

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 21

    Naive Bayes Classifier

    • Naive Bayes Classifier

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 22

    Model Evaluation Metrics

    • Model Evaluation Metrics

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 23

    Bias-Variance Trade-off

    • Bias-Variance Trade-off

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 24

    Regularization Techniques

    • Regularization Techniques

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 25

    Support Vector Machines

    • Support Vector Machines

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 26

    Kernel Tricks

    • Kernel Tricks

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 27

    Neural Network Architecture

    • Neural Network Architecture

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 28

    Hyperparameter Tuning in Neural Networks

    • Hyperparameter Tuning in Neural Networks

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 29

    Introduction to Decision Trees

    • Introduction to Decision Trees

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 30

    Ensembles of Decision Trees

    • Ensembles of Decision Trees

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 31

    Random Forest

    • Random Forest

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 32

    Gradient Boosting Machine

    • Gradient Boosting Machine

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 33

    Hyperparameter Tuning in Tree Algorithms

    • Hyperparameter Tuning in Tree Algorithms

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 34

    Principal Component Analysis

    • Principal Component Analysis

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 35

    K-Means Algorithm

    • K-Means Algorithm

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 36

    Hierarchical Clustering

    • Hierarchical Clustering

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 37

    Anomaly Detection

    • Anomaly Detection

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 38

    Engineering relevant variables

    • Engineering relevant variables

    • Lecture Materials & Practise Assignment
  • 39

    Recommender Systems - Collaborative Filtering

    • Content-based Filtering

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 40

    Recommender Systems - Content-based Filtering

    • Collaborative Filtering

    • Lecture Materials & Practise Assignment

    • Practise Quiz
  • 41

    Loan Default Prediction (Benchmark Solution)

    • Loan Default Prediction - Kaggle Benchmark Score Solution