Gain insights into conducting meaningful data analysis in Python without prior programming experience. Discover Python fundamentals, data preprocessing, EDA, and predictive analytics for solving business problems.

env.tar.gz

Python3

Ready to move past Excel for complex business analysis? Then you’ll find this course very helpful.

This hands-on introductory Data Science course is aimed at professionals and students who don't have any experience with programming. It will help you advance your career by preparing you to conduct meaningful data analysis in Python on any dataset — large or small.

You’ll begin with the fundamentals of Python, with focus on CSV files in Python, covering concepts like data preprocessing and Exploratory Data Analysis (EDA). In the second half, you'll focus on predictive and inferential analysis using statistical and machine learning techniques, and learn how these techniques can help solve business problems.

Data Science for Non-Programmers

## Conditional statements in Python
A **conditional statement** controls the flow of execution in a program based on a Boolean expression. If the expression evaluates to `True`, then a different piece of code might execute, If it is `False`, then some other piece of code will execute. This is also explained in the following illustration.  



# Conditional statements in Python
A **conditional statement** controls the flow of execution in a program based on a Boolean expression. If the expression evaluates to `True`, then a different piece of code might execute, If it is `False`, then some other piece of code will execute. This is also explained in the following illustration.  



This lesson will introduce conditional statements and focus on how to use them.

What is Data Science

Python Basics

Handling Tabular Data in Python

Data Cleaning

Exploratory Data Analysis

Statistical Inference

Predictive Models

Machine Learning

Conditional Statements

Conditional statements in Python