In the first lesson in this module, you gain insight into the impact of big data on various aspects of society, from business operations to sports, and develop an understanding of key attributes and challenges associated with big data. You will learn about the big data fundamentals, how data scientists use the cloud to handle big data, and the data mining process. Lesson two delves into machine learning and deep learning and the relationship of artificial intelligence to data science.

In the first lesson, you learn about the power of data science applications and how organizations leverage this power to drive business goals, improve efficiency, make predictions, and even save lives. You also reviewed the process you will follow as a data scientist to help your organization accomplish these ends. In the second lesson, you investigate what companies seek in a competent, experienced data scientist. You will learn how to position yourself to get hired as a data scientist. Amidst the diverse backgrounds from which data scientists emerge, you identify the qualities they share and skills that consistently set them apart from other data-related roles. You will complete a peer-reviewed final project by looking at a job posting for data scientist and identifying commonalities between the job and what you learned in this course. You will also walk through a case study, where you learn about Sarah and her data science journey.

This optional module focuses on understanding data and data literacy and is intended to supplement what you learned in the first three modules. As a data scientist, you will need to understand the ecosystem in which your data lives and how it gets manipulated to analyze it. This module introduces you to some of these fundamentals. In lesson one, you explore how data can be generated, stored, and accessed.  In lesson two, you take a deeper dive into data repositories and processes for handling massive data sets.