SAP Data Intelligence for Enterprise AI (openSAP)

Offered by 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.

With the recent breakthroughs in artificial intelligence (AI), many companies are pursuing the means to apply machine learning-based techniques to their business processes to transform and improve their usability and profitability and accelerate industry growth. SAP aspires to make all its enterprise solutions smart and help customers evolve to an intelligent enterprise.

This course offers an introduction to SAP Data Intelligence, SAP’s new AI/data science platform to manage complex data landscapes, build scalable data pipelines, and provision the entire data science process from proof of concept development to operationalization, continuous optimization, and adaptation. SAP Data Intelligence is a flexible solution that connects open source environments like JupyterLab with proven SAP technologies like SAP HANA and SAP Leonardo Machine Learning, while allowing you to work across them seamlessly. The features offered facilitate the building of smart applications for customers and business partners.
In this course, we’ll discuss use cases for enterprise machine learning applications. We’ll show you how to work with popular languages, such as Python and R, or your favorite libraries such as TensorFlow, in a development to production environment that supports you through the entire lifecycle management, from data access to continuous model retraining and deployment. You’ll also go through a variety of demos to learn how to build and consume your own machine learning/deep learning models.
The course is aimed mainly at data science enthusiasts but is also suitable for anyone interested in data science and innovation, focusing on the specific product capabilities for developing a data science scenario in an enterprise landscape. To learn more about the data management aspects of SAP Data Intelligence for data engineers, developers, and development operations, we highly recommend you also visit the course Freedom of Data with SAP Data Hub (HUB1) on openSAP.

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

Related Courses

Introduction to Data Science in Python (Coursera) Coursera
University of Michigan

Introduction to Data Science in Python (Coursera)

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.

Jun 8th 2026
4 Weeks
Regression Models (Coursera) Coursera
Johns Hopkins University

Regression Models (Coursera)

Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models.

Jun 8th 2026
4 Weeks
SAP HANA Data Management Suite - Strategy Talk (openSAP) OpenSAP
SAP

SAP HANA Data Management Suite - Strategy Talk (openSAP)

Join this free openSAP course to get an initial introduction to SAP HANA Data Management Suite, which was announced at SAPPHIRE NOW in June 2018. As organizations ready themselves to master the digital economy, a powerful data management framework is crucial for maintaining the highly secure and agile environment that’s needed to drive business innovation.

Self Paced
Self-Paced
Introducción a Data Science: Programación Estadística con R (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Data Science: Programación Estadística con R (Coursera)

Este curso te proporcionará las bases del lenguaje de programación estadística R, la lengua franca de la estadística, el cual te permitirá escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalación del lenguaje; también verás una introducción a los sistemas base de gráficos y al paquete para graficar ggplot2, para visualizar estos datos. Además también abordarás la utilización de uno de los IDEs más populares entre la comunidad de usuarios de R, llamado RStudio.

Jun 8th 2026
4 Weeks
The Data Scientist's Toolbox (Coursera) Coursera
Johns Hopkins University

The Data Scientist's Toolbox (Coursera)

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Jun 8th 2026
4 Weeks
Reproducible Research (Coursera) Coursera
Johns Hopkins University

Reproducible Research (Coursera)

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations.

Jun 8th 2026
4 Weeks
Predictive Modeling and Analytics (Coursera) Coursera
University of Colorado Boulder

Predictive Modeling and Analytics (Coursera)

Welcome to the second course in the Data Analytics for Business specialization! This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business.

Jun 8th 2026
4 Weeks
Exploratory Data Analysis (Coursera) Coursera
Johns Hopkins University

Exploratory Data Analysis (Coursera)

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data.

Jun 8th 2026
4 Weeks