What is Data Science? (Coursera)

Offered by IBM,
What is Data Science? (Coursera)

The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

This course is part of multiple programs
This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:

Syllabus

WEEK 1
Defining Data Science and What Data Scientists Do
In this module, you will view the course syllabus to learn what will be taught in this course. You will hear from data science professionals to discover what data science is, what data scientists do, and what tools and algorithms data scientists use on a daily basis. Finally, you will complete a reading assignment to find out why data science is considered the sexiest job in the 21st century.

WEEK 2
Data Science Topics
In this module, you will hear from Norman White, the Faculty Director of the Stern Centre for Research Computing at New York University, as he talks about data science and the skills required for anyone interested in pursuing a career in this field. He also advises those looking to start a career in data science. Finally, you will complete reading assignments to learn about the process of mining a given dataset and about regression analysis.

WEEK 3
Data Science in Business
In this module, you will learn about the approaches companies can take to start working with data science. You will learn about some of the qualities that differentiate data scientists from other professionals. You will also learn about analytics, story-telling, and the pivotal role data scientists play in creating an effective final deliverable. Finally, you will apply what you learned about data science by answering open-ended questions.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Code Free Data Science (Coursera) Coursera
University of California, San Diego

Code Free Data Science (Coursera)

The Code Free Data Science class is designed for learners seeking to gain or expand their knowledge in the area of Data Science. Participants will receive the basic training in effective predictive analytic approaches accompanying the growing discipline of Data Science without any programming requirements. Machine Learning methods will be presented by utilizing the KNIME Analytics Platform to discover patterns and relationships in data.

Oct 26th 2026
4 Weeks
Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Nov 9th 2026
4 Weeks
Making Data Science Work for Clinical Reporting (Coursera) Coursera
Genentech

Making Data Science Work for Clinical Reporting (Coursera)

This course is aimed to demonstrate how principles and methods from data science can be applied in clinical reporting. By the end of the course, learners will understand what requirements there are in reporting clinical trials, and how they impact on how data science is used. The learner will see how they can work efficiently and effectively while still ensuring that they meet the needed standards.

Nov 2nd 2026
4 Weeks
Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera) Coursera
Johns Hopkins University

Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera)

Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: a basic understanding of linear algebra and multivariate calculus; a basic understanding of statistics and regression models; at least a little familiarity with proof based mathematics; basic knowledge of the R programming language.

Oct 26th 2026
4 Weeks
Applied Plotting, Charting & Data Representation in Python (Coursera) Coursera
University of Michigan

Applied Plotting, Charting & Data Representation in Python (Coursera)

This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework.

Nov 2nd 2026
4 Weeks
Introducción a la Minería de Datos (Coursera) Coursera
Pontificia Universidad Católica de Chile

Introducción a la Minería de Datos (Coursera)

En este curso, aprenderás de manera gradual y práctica los conceptos básicos de Minería de Datos, junto a los algoritmos más utilizados hoy en día. Al finalizar el curso, serás capaz de entender la importancia de manejar la información y de explorar por ti mismo distintas bases de datos reales. Este curso es el primer paso para convertirte en un/a profesional con habilidades básicas de un científico de datos o Data Scientist, de manera tal que puedas abrirle la puerta al futuro.

Nov 2nd 2026
5-12 Weeks
Materials Data Sciences and Informatics (Coursera) Coursera
Georgia Institute of Technology

Materials Data Sciences and Informatics (Coursera)

This course aims to provide a succinct overview of the emerging discipline of Materials Informatics at the intersection of materials science, computational science, and information science. Attention is drawn to specific opportunities afforded by this new field in accelerating materials development and deployment efforts.

Nov 2nd 2026
5-12 Weeks
Practical Predictive Analytics: Models and Methods (Coursera) Coursera
University of Washington

Practical Predictive Analytics: Models and Methods (Coursera)

Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems.

Oct 26th 2026
4 Weeks
Data Science in Stratified Healthcare and Precision Medicine (Coursera) Coursera
University of Edinburgh

Data Science in Stratified Healthcare and Precision Medicine (Coursera)

An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine.

Nov 2nd 2026
5-12 Weeks
Understanding China, 1700-2000: A Data Analytic Approach, Part 1 (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Understanding China, 1700-2000: A Data Analytic Approach, Part 1 (Coursera)

The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history.

Oct 26th 2026
5-12 Weeks