A Complete Python Tutorial to Learn Data Science from Scratch

Key Info
Description - a brief synopsis, abstract or summary of what the learning resource is about: 

In this tutorial, you will learn data science using python from scratch, and It will also help you to learn basic data analysis methods using python, and you will also be able to enhance your knowledge of machine learning algorithms.
Table of Contents
1-Basics of Python for Data Analysis

  • Why learn Python for data analysis?
  • Python 2.7 v/s 3.4
  • How to install Python?
  • Running a few simple programs in Python

2-Python libraries and data structures

  • Python Data Structures
  • Python Iteration and Conditional Constructs
  • Python Libraries

3-Exploratory analysis in Python using Pandas

  • Introduction to series and data frames
  • Analytics Vidhya dataset- Loan Prediction Problem

4-Data Munging in Python using Pandas
5-Building a Predictive Model in Python

  • Logistic Regression
  • Decision Tree
  • Random Forest
Authoring Person(s) Name: 
Kunal Jain
Access Cost: 
No fee
Primary language(s) in which the learning resource was originally published or made available: 
More info about
Keywords - short phrases describing what the learning resource is about: 
Data analysis
Data skills education
Machine learning
Publisher - organization credited with publishing or broadcasting the learning resource: 
Analytics Vidhya
Version - revision or edition number or date associated with a learning resource: 
2020 version
Media Type - designation of the form in which the content of the learning resource is represented, e.g., moving image: 
Interactive Resource - requires a user to take action or make a request in order for the content to be understood, executed or experienced.
Educational Info
Purpose - primary educational reason for which the learning resource was created: 
Instruction - detailed information about aspects or processes related to data management or data skills.
Learning Resource Type - category of the learning resource from the point of view of a professional educator: 
Course - series of units and lessons used to teach the skills and knowledge required by its curriculum.
Target Audience - intended audience for which the learning resource was created: 
Data professional
Early-career research scientist
Graduate student
Software engineer
Technology expert group
Intended time to complete - approximate amount of time the average student will take to complete the learning resource: 
More than 1 hour (but less than 1 day)