There is an ever-increasing demand for storing different types of data in organizations. Be it a small or big organization, employers want to keep records of their employees, customers, accounts, feedback, and so on. However, maintaining such an enormous collection of data is not possible without the help of data science. This video course will help you to learn the important concepts and theories of applied data science that you need to know to store, manipulate, and visualize huge chunks of data.
The course starts with an introduction to applied data science and a tutorial on how to set up a Jupyter notebook. You’ll then go on to understand linear regression using Boston data. As you advance, you’ll discover data visualization techniques and explore time series and data evaluation. You'll also get to grips with extended data analysis with the help of a temperature analysis activity. Toward the end, you’ll be introduced to k-means clustering and gain a solid understanding of decision trees.
By the end of this course, you’ll be well-versed with applied data science concepts and be able to apply your skills in the real world.
Gain a solid understanding of applied data science
Get to grips with extended data analysis using an example data set
Find out how to perform linear and logistic regression
Become familiar with scattered and advanced scattered plot
Develop skills to plot time-series data
Explore k-means clustering and define centroids for clustering