Course Outline
Introduction to Data Science
We will begin the course by defining what data science entails. We will cover the data science workflow and how data science is applied to real-world business challenges. We will conclude the chapter by learning how to structure your data team to meet your organisation's needs.
Analysis and Visualisation
In this chapter, we will discuss methods for exploring and visualising data through dashboards. We will examine the components of a dashboard and how to formulate specific requests for dashboards. This chapter will also cover making ad hoc data requests and conducting A/B tests, which are powerful analytics tools that help mitigate risk in 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 various data sources your company can utilise and how to store that data once it has been collected.
Prediction
In this final chapter, we will discuss the most exciting topic in data science: machine learning! We will cover supervised and unsupervised machine learning, and 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.
