Intro to Data Visualization
Elitsa Kaloyanova
Course Author Elitsa Kaloyanova
Course Author
Who is it for
How it can help you
Check out the best online resources for data science according to our students and expert team of instructors—available to download and use for free.
Introduction to Data Science Disciplines
The term “Data Science” dates back to the 1960s, to describe the emerging field of working with large amounts of data that drives organizational growth and decision-making. While the essence has remained the same, the data science disciplines have changed a lot over the past decades thanks to rapid technological advancements. In this free introduction to data science practice exam, you will test your understanding of the modern day data science disciplines and their role within an organization.
Learn More
Intrо to Machine Learning
State-of-the-art machine learning algorithms have opened a whole new realm of possibilities for businesses to optimize their processes and create new product/service features, that maximize competitive advantages. Used in recommendation systems, fraud detection, spam filtering, self-driving cars, to name a few, these advanced algorithms are only getting more popular by the day. Take this free machine learning practice exam and test your knowledge on supervised, unsupervised and reinforcement machine learning, and their applications.
Learn More
Excel Basics
Ever since its first release in 1985, Excel continues to be the most popular spreadsheet application to this day- with approximately 750 million users worldwide, thanks to its flexibility and ease of use. No matter if you are a data scientist or not, knowing how to use Excel will greatly improve and optimize your workflow. Therefore, in this free Excel Basics practice exam you are going to work with a dataset of a company in the Fast Moving Consumer Goods Sector as an aspiring data analyst and test your knowledge on basic Excel functions and shortcuts.
Learn More
Useful Tools in Excel
What Excel lacks in data visualization tools compared to Tableau, or computational power for analyzing big data compared to Python, it compensates with accessibility and flexibility. Excel allows you to quickly organize, visualize and perform mathematical functions on a set of data, without the need for any programming or statistical skills. Therefore, it is in your best interest to learn how to use the various Excel tools at your disposal. This practice exam is a good opportunity to test your excel knowledge in the text to column functions, excel macros, row manipulation and basic math formulas.
Learn More
Fundamentals of Descriptive Statistics
Descriptive statistics helps us understand the actual characteristics of a dataset by generating summaries about data samples. The most popular types of descriptive statistics are measures of center: median, mode and mean. In this free practice exam you have been appointed as a Junior Data Analyst at a property developer company in the US, where you are asked to evaluate the renting prices in 9 key states. You will work with a free excel dataset file that contains the rental prices and houses over the last years.
Learn More
Intro to Jupyter Notebooks
Jupyter is a free, open-source interactive web-based computational notebook. As one of the most popular coding environments for Python and R, you are inevitably going to encounter Jupyter at some point in you data science journey, if you have not already. Therefore, in this free practice exam you are a professor of Applied Economics and Finance who is learning how to use Jupyter. You are going to be tested on the very basics of the Jupyter environment like how to set up the environment and some Jupyter keyboard shortcuts.
Learn More
Fundamentals of Inferential Statistics
While descriptive statistics helps us describe and summarize a dataset, inferential statistics allows us to make predictions based off data. In this free practice exam, you are a data analyst at a leading statistical research company. Much of your daily work relates to understanding data structures and processes, as well as applying analytical theory to real-world problems on large and dynamic datasets. You will be given an excel dataset and will be tested on normal distribution, standardizing a dataset, the Central Limit Theorem among other inferential statistics questions.
Learn More
Jupyter Notebook Shortcuts
In this free practice exam you are an experienced university professor in Statistics who is looking to upskill in data science and has joined the data science apartment. As on of the most popular coding environments for Python, your colleagues recommend you learn Jupyter Notebook as a beginner data scientist. Therefore, in this quick assessment exam you are going to be tested on some basic theory regarding Jupyter Notebook and some of its shortcuts which will determine how efficient you are at using the environment.
Learn MoreIntro to Data Visualization
