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

# Variables
A **variable** is a name to which a value can be assigned. It is basically a placeholder to store information. We can store information in a variable and refer to it later by using the variable name. Variables are assigned values using the `=` operator. 

When you run the above code, you will see **EDUCATIVE** printed on the screen. In **line 1**, we created a variable which we named `x` and assigned it the value `EDUCATIVE`. In the next line, when we said to Python to `print(x)`, it printed what was assigned to the variable `x`. 

As the name suggests, the value of a variable can be changed. Let's see an example of that below.

x = 'EDUCATIVE'
print(x)

# Change value of x
x = 99
print(x)

We have extended the code of the above example. When **line 1** runs the variable `x` is assigned the value `EDUCATIVE`. The value of x is printed in **line 2**. But in **line 5**, we assign the value `99` to `x`. Now when we print `x` in **line 6**, the changed value of `x`, i.e., `99`, is printed on the screen.

## Naming rules
There are some naming rules and conventions that need to be kept in mind for naming variables. If these rules are not followed, Python will give an error.

* The name can start with an upper- or lower-case alphabet.

* A number can appear in the name, but not at the beginning.

* The `_ `character can appear anywhere in the name.

* Spaces are not allowed. Instead, we must use [snake_case](https://en.wikipedia.org/wiki/Snake_case) to make variable names readable.

* The name of the variable should be something meaningful that describes the value it holds, instead of being random characters.



This lesson will focus on variables and the different data types in Python.

What is Data Science

Python Basics

Handling Tabular Data in Python

Data Cleaning

Exploratory Data Analysis

Statistical Inference

Predictive Models

Machine Learning

Variables and Data Types

Variables

Naming rules