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’.
Create a free account and start learning data science today.create free account
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.
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.
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.
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.
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.
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.
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.
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.See All Modules
Real-life project and data. Solve them on your own computer as you would in the office.
Our expert instructors are happy to help. Post a question and get a personal answer by one of our instructors.
Earn a verifiable certificate after each completed course. Celebrate your successes and share your progress with your professional network!
The course is in-depth and is delivered at a steady pace with eye catching visuals. The instructors go through all the basics really well. They try not to over-simplify the material, you get a good sense аof how deep Data Science is in the course. Great job!!!
This course is amazing! After watching the video carefully and doing all the exercises, I am even capable of having discussions with Machine learning major Master’s students! High standard course with reasonable pricing.
Very clear and in-depth explanation of data science and how all the inter-related concepts apply in real life business environment. Absolutely great for beginners! Best data science course I have come across so far!
I would highly recommend the course to any beginner who wants to venture into the world of Data Science. The concepts are very well explained and there is an emphasis on practical application which really helps create a better understanding of the concepts.