Do you want to know why data science has been labeled the sexiest profession of the 21st century? After taking this course, you will be able to answer this question, understand what data science is and what data scientists do, and learn about career paths in the field.
What is Data Science?
This course is part of multiple programs.
Instructors: Rav Ahuja
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What you'll learn
Define data science and its importance in today’s data-driven world.
Describe the various paths that can lead to a career in data science.
Summarize advice given by seasoned data science professionals to data scientists who are just starting out.
Explain why data science is considered the most in-demand job in the 21st century.
Skills you'll gain
Details to know
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23 assignments
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There are 4 modules in this course
In Module 1, you delve into some fundamentals of Data Science. In lesson 1, you listen to how other professionals in the field define what data science is to them and the paths they took to consider data science as a career for themselves. You explore different roles data scientists fulfill, how data analysis is used in data science, and how data scientists follow certain processes to answer questions with that data. Moving on to Lesson 2, the focus shifts to the daily activities of data scientists. This encompasses learning about various real-world data science problems that professionals solve, the skills and qualities needed to be a successful data scientist, and opinions on how “big data” relates to those skills. You also learn a little about various data formats data scientists work with and algorithms used in the field to process data.
What's included
11 videos6 readings5 assignments1 discussion prompt4 plugins
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.
What's included
13 videos3 readings6 assignments5 plugins
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.
What's included
10 videos8 readings8 assignments6 plugins
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.
What's included
11 videos3 readings4 assignments3 plugins
Recommended if you're interested in Data Analysis
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Showing 3 of 73393
Reviewed on Jul 24, 2021
Thank you for this coursera.
Reviewed on Jul 18, 2018
I thought this course introduced the topic of data science very well. I think I have a much better idea how to describe data science and common terms associated with the field (like machine learning).
Reviewed on Sep 7, 2023
It is an excellent introduction for people interested. I felt some of the questions could have been a bit harder to test a slightly deeper understanding, although this will probably be the case later.
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