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

We know that the objective of Data Science as a discipline is to extract insights and meaning from data. To achieve this goal, data scientists follow a process that is known as the **Data Science Lifecycle.** 
## The Data Science lifecycle
The **Data Science lifecycle** involves $5$ steps as shown in the following figure:


We know that the objective of Data Science as a discipline is to extract insights and meaning from data. To achieve this goal, data scientists follow a process that is known as the **Data Science Lifecycle.** 
# The Data Science lifecycle
The **Data Science lifecycle** involves $5$ steps as shown in the following figure:


This lesson will introduce learners to the Data Science lifecycle, i.e., the process of extracting insights from data.

What is Data Science

Python Basics

Handling Tabular Data in Python

Data Cleaning

Exploratory Data Analysis

Statistical Inference

Predictive Models

Machine Learning

Data Science Lifecycle

The Data Science lifecycle