Getting Started with Data Science (openSAP)

Offered by SAP,
Getting Started with Data Science (openSAP)

In 2012, Harvard Business Review named data science the "sexiest job of the 21st century." Why are data scientists in such demand these days? The answer is that over the past decade, there has been an explosion in the data generated and retained by companies, and they need to leverage and exploit it. Data scientists are the people who make sense out of all this data and figure out just what can be done with it. If you’re interested in learning about data science, this course will introduce you to the fundamentals of data preparation, predictive modeling, data science, and the deployment and maintenance of models in a business environment following a tried and tested project methodology.

In the first week, we’ll cover the fundamental challenges of business problem understanding and identifying the appropriate analytical approach. In the second week, we’ll cover data preparation, selecting variables, and data encoding. Weeks three and four will introduce you to a wide range of algorithms such as decision trees, regression, neural networks, basket analysis, and simulation. Week five explains how we evaluate the performance of our models and the approaches we take to improve them. In week 6, you’ll learn about model deployment and maintenance, and we’ll debunk some common myths.

Data science is a complex subject to understand, but in this course you’ll learn about the fundamental principles, look at how the algorithms can add value to your business, and we’ll demystify the complex processes. You don’t have to be a rocket scientist to be a data scientist.

Course Content

Week 1: Business & Data Understanding
Week 2: Data Preparation
Week 3: Modeling (1)
Week 4: Modeling (2)
Week 5: Evaluation
Week 6: Deployment & Maintenance
Week 7: Final Exam

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

Related Courses

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).

Sep 14th 2026
4 Weeks
Data Management for Clinical Research (Coursera) Coursera
Vanderbilt University

Data Management for Clinical Research (Coursera)

This course presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research. Understanding and implementing solid data management principles is critical for any scientific domain. Regardless of your current (or anticipated) role in the research enterprise, a strong working knowledge and skill set in data management principles and practice will increase your productivity and improve your science. Our goal is to use these modules to help you learn and practice this skill set.

Sep 14th 2026
5-12 Weeks
SAP Data Intelligence for Enterprise AI (openSAP) OpenSAP
SAP

SAP Data Intelligence for Enterprise AI (openSAP)

Join this free online course to learn about SAP Data Intelligence, SAP’s new AI/data science platform for managing complex data landscapes, building scalable data pipelines, and provisioning the entire data science process. You’ll learn how to work with languages such as Python and R, open source libraries / services like TensorFlow, libraries like PAL and APL, and the functional, technical and business services of SAP Leonardo Machine Learning.

Self Paced
Self-Paced
Experimentation for Improvement (Coursera) Coursera
McMaster University

Experimentation for Improvement (Coursera)

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In this course, you will learn how to plan efficient experiments - testing with many variables. Our goal is to find the best results using only a few experiments. A key part of the course is how to optimize a system.

Sep 14th 2026
5-12 Weeks
Principles of fMRI 1 (Coursera) Coursera
Johns Hopkins University

Principles of fMRI 1 (Coursera)

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data, including psychological inference, MR Physics, K Space, experimental design, pre-processing of fMRI data, as well as Generalized Linear Models (GLM’s).

Sep 14th 2026
4 Weeks