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.

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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

In the previous chapters of this course, we have looked at data cleaning, data exploration, and statistical inference. Now it is time to move to the last stage of the data science lifecycle, which is making predictions that help us in decision making. Until now, we have discovered interesting patterns in the data that we know were significant, but how do we use these patterns to predict future events? With this objective, we make predictions using *models*. 

This lesson will introduce predictive modeling and will focus on how to construct a simple model with loss functions. 

What is Data Science

Python Basics

Handling Tabular Data in Python

Data Cleaning

Exploratory Data Analysis

Statistical Inference

Predictive Models

Machine Learning

A Simple Model