Introduction to Data Science

categories: Technology, Science & Productivity

Productivity

SDG 9: Industry, Innovation and Infrastructure

By the end of this course, you will be able to

By the end of this level, you will be able to: - Understand the stages of the data analytics lifecycle, including data, preparation, data exploration, and modeling.
Learn about the applications of prediction methods and clustering methods, and discover association rules.
Understand the basics of programming using the Python language, and implement a simple project using the main Python libraries.

Course details

1 h 49 m/18 lessons
Last updated: 27/10/2022
Course completion certificate

Course Content

Free lessons

Data Science Concept

10 Minutes

Data Analytics Life Cycle 1

11 Minutes

1. Introduction to Data Science

Data Science Concept

10 Minutes

Data Analytics Life Cycle 1

11 Minutes

Data Analytics Life Cycle 2

6 Minutes

Data Science Applications in Commerce

9 Minutes

Data Science Applications in Business

10 Minutes

Classficatin

9 Minutes

Clustring

11 Minutes

Careers in Data Science Fields

6 Minutes

Using Anaconda to Install Python

1 Minutes

10.

Python Programming Language

5 Minutes

11.

Loops in the Python Programming Language

3 Minutes

12.

Conditional Statements in the Python Programming Language

5 Minutes

13.

Installing Packages in Data Science

1 Minutes

14.

Jupyter Notebook Tool

15.

NumPy Library

5 Minutes

16.

Pandas Library

4 Minutes

17.

Matplotlib Library

3 Minutes

18.

The Required Project

1 Minutes

About this course

This level provides an introduction to the field of data science. This level covers the main stages of the data analytics lifecycle as well as examples of different applications of data science. It also introduces the basic concepts of Python programming with practical examples.