Course Outline
Introduction to Data Science
We commence the course by defining data science. We will cover the data science workflow and illustrate how data science is applied to solve real-world business problems. We will conclude the chapter by learning how to structure your data team to meet your organization's needs.
Analysis and Visualization
In this chapter, we will discuss methods for exploring and visualizing data via dashboards. We will examine the elements of a dashboard and how to craft a directed request for one. This chapter will also cover making ad hoc data requests and conducting A/B tests, which are powerful analytics tools that help de-risk decision-making.
Data Collection and Storage
Now that we understand the data science workflow, we will delve deeper into the first step: data collection. We will learn about the different data sources your company can utilize and how to store that data once it is collected.
Prediction
In this final chapter, we will discuss the most trending topic in data science: machine learning! We will cover supervised and unsupervised machine learning, as well as clustering. Then, we will move on to special topics in machine learning, including time series prediction, natural language processing, deep learning, and explainable AI!
Testimonials (1)
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
