Data Science Approach from Scratch: An Easy Explanation


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Course overview

Course type
Paid course
15 lessons
Available on completion
Course author
Nizamuddin Siddiqui
  • Data Science explanation in layman language and it's need
  • 8 Mistakes made by people who want to start their career in Data Science
  • 3 Myths about Data Science
  • Data Types and Variables
  • Definition of Data Cleaning and the errors that results in the need of Data Cleaning
  • Feature Engineering
  • Data Thinking Development
  • Use of many Algorithms
  • Example to select the best model in case of a classification problem
  • Types of Learning Methods


Understand the Complete Data Science use through a Real Life problem - The Easiest Way to Understand Data Science

Welcome to the ultimate course on Data Science Approach from Scratch!!!

This course is your Best Resource for learning the use of Data Science.

We will be understanding the use of:

1. Data Science from a layman's perspective

2. Regression Algorithms

3. Classification Algorithms

4. Clustering Algorithms

5. Boosting Algorithms

6. Dimensionality Reduction Algorithms

Specifically, we will cover:

  • Linear Regression

  • Stepwise Regression

  • Polynomial Regression

  • Logistic Regression

  • Naive Bayes

  • Decision Trees

  • Random Forest

  • Support Vector Machine

  • Gradient Boosting

  • Principal Component Analysis and Linear Discriminant Analysis

  • K-means Clustering and Hierarchical Clustering

  • and much more!

Feel free to message me on Udemy if you have any questions about the course!

Thanks for checking out the course page, and I hope to see you inside the course!


Course Instructor

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