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Course features

  • 35+ Hours of Learning Content

  • Real World Projects

  • Verified Certificate

  • Internship & Job Opportunities

  • Life time access

  • Free Mentorship

Key Highlights of Data Science Career

A Data scientist is the top ranking professional in any analytics organization. Glassdoor ranks Data Scientists first in the 25 Best Jobs for 2019. In today’s market, Data Scientists are scarce and in demand. As a Data Scientist, you are required to understand the business problem, design a data analysis strategy, collect and format the required data, apply algorithms or techniques using the correct tools, and make recommendations backed by data.




Companies that hire Data Scientists


Course curriculum

  • 1

    Course Overview

    • Program Overview

  • 2

    COURSE INTRODUCTION

    • Data Science Intro Video
  • 3

    MODULE 1 : Introduction to Machine learning

    • Overview of Machine Learning

    • Introduction to Machine Learning

    • Roadmap for learning Machine Learning

    • How to Learn Machine Learning

    • Evaluate Your Skill
  • 4

    MODULE 2 : Supervised Learning And Linear Regression

    • What is Supervised learning and Linear Regression?

    • How Supervised Learning Works

    • Supervised Learning And Linear Regression Part 1

    • Evaluate your Skill

    • Supervised Learning And Linear Regression Part 2

    • Evaluate your Skill

    • Supervised Learning And Linear Regression Part 3

    • Test Yourself

    • Supervised Learning And Linear Regression Part 4

    • Supervised Learning And Linear Regression Part 5

    • Test Yourself
  • 5

    MODULE 3 : Regression

    • What is Regression?

    • Types of Regression

    • How To Choose Correct Regression Model?

    • Regression Part 1

    • Regression Part 2

    • Linear Model

    • Test Yourself
  • 6

    MODULE 4 : Logistic Regression

    • What is logistic regression?

    • Logistic regression assumptions

    • Logistic Regression Part 1

    • What is logistic regression used for?

    • What are the different types of logistic regression?

    • Logistic Regression Part 2

    • What are the advantages and disadvantages of using logistic regression?

    • Test Yourself
  • 7

    MODULE 5 : Model Evaluation

    • What is Model Evaluation?

    • Model Evaluation Part 1

    • Model Evaluation Techniques

    • Model Evaluation Part 2

    • Test Yourself
  • 8

    MODULE 6 : Tree Based Model

    • What is Tree Based Model?

    • What is a Decision Tree ? How does it work ?

    • Important Terminology related to Tree based Algorithms

    • Tree Based Models Part 1

    • Advantages and Disadvantages of Tree Based Model

    • Tree Based Models Part 2

    • Regression Trees vs Classification Trees

    • Test Yourself
  • 9

    MODULE 7 : Random Forest, SVM and Naive Bays

    • What is Random forest ?

    • How does it work?

    • Random Forest Part 1

    • Random Forest Part 2

    • Pros and Cons of Random Forest

    • Test Yourself

    • What is Support Vector Machine?

    • Types of SVM

    • Hyperplane and Support Vectors in SVM

    • How does SVM work?

    • Support Vector Machine

    • Pros and Cons associated with SVM

    • Test Yourself

    • What is Naive Bayes Classifier Algorithm ?

    • Bayes' Theorem

    • Working of Naïve Bayes' Classifier

    • Naive Bayes Classifier

    • What are the Pros and Cons of Naive Bayes?

    • Navie Bayes classifier

    • Test Yourself
  • 10

    MODULE 8 : Clustering

    • What is Clustering?

    • Types of Clustering

    • Clustering Part 1

    • Clustering Part 2

    • Types of Clustering Algorithm

    • Applications of Clustering

    • Test Yourself
  • 11

    MODULE 9 : Association Rules

    • Introduction

    • Association Rules Part 1

    • Association Rules Part 2

    • Rule Evaluation Metrics

    • Test Yourself
  • 12

    MODULE 10 : Time Series Forecasting

    • What is Time Series data?

    • What is a time series problem?

    • Components of TIme Series

    • Time Series Forecasting Part 1

    • Time series analysis vs time series forecasting

    • Test Yourself

    • Time Series Forecasting Part 2

    • What are time series forecasting methods?

    • Test Yourself

    • Time Series Forecasting Part 3

    • Developing your own time series model

    • Test yourself
  • 13

    MODULE 11 : Natural Language Processing

    • What is natural language processing?

    • Natural Language Processing Part 1

    • Natural Language Processing Part 2

    • Natural Language Processing Part 3

    • What is NLP used for?

    • How does Natural Language Processing Works?

    • What are the techniques used in NLP?

    • Test Yourself

Program Mentor

We bring you the powerful industry experts

Data Scientist

Debraj Roy

Debraj Roy is Data Scientist and Mentor, he has 10+ years of Experience in Data Science Field

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