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

## Support Vector Machine
A **Support Vector Machine (SVM)** is a supervised machine learning algorithm that can be used for both classification and regression problems. In this algorithm, we plot each data item as a point in n-dimensional space (where n is the number of features we have) with the value of each feature being the value of a particular coordinate. Then, we perform classification by finding the hyper-plane/line that differentiates the two classes. A **hyper-plane** is the higher dimensional version of a line. As a line can separate classes on two-dimensional data, a hyper-plane can separate on higher dimensions.  

# Support Vector Machine
A **Support Vector Machine (SVM)** is a supervised machine learning algorithm that can be used for both classification and regression problems. In this algorithm, we plot each data item as a point in n-dimensional space (where n is the number of features we have) with the value of each feature being the value of a particular coordinate. Then, we perform classification by finding the hyper-plane/line that differentiates the two classes. A **hyper-plane** is the higher dimensional version of a line. As a line can separate classes on two-dimensional data, a hyper-plane can separate on higher dimensions.  

This lesson will focus on training Support Vector Machines.

What is Data Science

Python Basics

Handling Tabular Data in Python

Data Cleaning

Exploratory Data Analysis

Statistical Inference

Predictive Models

Machine Learning

Support Vector Machines

Support Vector Machine