Intro to Data and Data Science

Working with data is an essential part of maintaining a healthy business. This course will introduce you to the field of data science and help you understand the various processes and distinguish between terms such as: ‘traditional data’, ‘big data’, ‘business intelligence’, ‘business analytics’, ‘data analytics’, ‘data science’, and ‘machine learning’.

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Section 1

The different data science fields

For a novice, the data science field can be rather confusing. It takes a while to make sense of all the buzz words and different areas of data science. In this section, you will learn how to distinguish between Business analytics, Data analytics, Business Intelligence, Machine Learning, and Artificial Intelligence. We will discuss all of this with the help of a specially designed infographic and by the end of the section you will know exactly where data science fits today.

FREE Welcome to Intro to Data and Data Science
FREE Why are there so many business and data science buzzwords?
FREE Analysis vs Analytics
FREE Intro to Business Analytics, Data Analytics, and Data Science
FREE Adding Business Intelligence (BI), Machine Learning (ML), and Artificial Intelligence (AI) to the picture
FREE An Overview of our Data Science Infographic

Section 2

The relationship between different data science fields

In this section, you will learn how data science fields relate to each other and which ones leverage on traditional and big data, business intelligence, or traditional data science methods and machine learning.

FREE When are Traditional data, Big Data, BI, Traditional Data Science and ML applied?

Section 3

What is the purpose of each data science field

Here you will learn not only which are the various data science disciplines, but also what each discipline is used for in practice. This is really valuable for you as it will allow you to gain an idea of the practical application of the different methods you will learn later on in our program.

FREE Why do we need each of these disciplines?

Section 4

Common data science techniques

There are different ways to approach Traditional data, Big data, Business Intelligence, Traditional data science methods, and Machine learning. In this part of the course, we will introduce you to some of the most common techniques to do that, and we will provide several practical examples that will make things easier and more relatable.

Premium course icon Traditional Data: Techniques
Premium course icon Traditional Data: Real-life Examples
Premium course icon Big Data: Techniques
Premium course icon Big Data: Real-life Examples
Premium course icon Business Intelligence (BI): Techniques
Premium course icon Business Intelligence (BI): Real-life Examples
Premium course icon Traditional Methods: Techniques
Premium course icon Traditional Methods: Real-life Examples
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Premium course icon Machine Learning (ML): Techniques
Premium course icon Machine Learning (ML): Types of Machine Learning
Premium course icon Machine Learning (ML): Real-life Examples
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Section 5

Common data science tools

Before we dive in to studying the different types of tools used in data science, we will provide a quick overview for you, so you can have a good idea of why we are studying different tools and how they interact with each other. This will greatly facilitate your learning process as you will already know what to expect and which tools will be necessary for a specific task.

Premium course icon Programming Languages & Software Employed in Data Science - All the Tools You Need

Section 6

Data Science Job Positions: What do they Involve and What to Look out for?

In this section, we will discuss several job positions related to the fields of data and data science, including what responsibilities they comprise, and what to look out for when choosing your path.

Premium course icon Data Science Job Positions: What do they Involve and What to Look out for?

Section 7

Dispelling common Misconceptions

We will conclude our Intro to Data and Data Science training with a lesson that dispells the most common misconceptions about the field of data science.

Premium course icon Dispelling Common Misconceptions
MODULE 1

Data Science Fundamentals

This course is part of Module 1 of the 365 Data Science Program. The complete training consists of four modules, each building up on your knowledge from the previous one. Whereas the other three modules are designed to improve upon your technical skillset, Module 1 is designed to help you create a strong foundation for your data science career. You will understand the core principles of probability, statistics, and mathematics; you will also learn how to visualize your data.

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