This course was retired in October 2022.

Course Summary

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 on openSAP.

Here is what some participants are saying about the course:

"Hi, Thanks to Open SAP team in bringing, course that give insight to latest technology and providing platform for innovation.. …” Read the original post

"The course is very well put together as an introduction to AI and ML on SAP Data Intelligence for Enterprise AI platform. …” Read the original post

"I would like to thank for this opportunity and course. I found it very interesting and exciting to see the possibilities, applications and examples of the system in operation. …” Read the original post

Course Characteristics

• Starting from: January 29, 2020, 09:00 UTC (What does this mean?)
  
• Duration: The course is open for 5 weeks
  
• Effort: 4-6 hours in total
  
• Course assignment: You can take the course assignment at any time whilst the course is open.
  
• Course closure: March 5, 2020, 09:00 UTC
  
• Course language: English
  
• How is an openSAP course structured?
  

Course Content

Unit 1: Enabling the Intelligent Enterprise with Machine Learning
Unit 2: Intelligent SAP Applications
Unit 3: Customer Use Cases
Unit 4: SAP Data Intelligence Capabilities for Data Scientists
Unit 5: SAP Data Intelligence Launchpad and Components
Unit 6: Machine Learning Scenario Manager
Unit 7: Data Science Experiments in Jupyter Notebook (PAL, APL, Python)
Unit 8: Working with the SAP Data Intelligence Pipeline Modeler
Unit 9: Operationalizing Python and R with the Pipeline Modeler
Unit 10: Intelligent Services
Unit 11: Summary and Outlook

Target Audience

• Executive managers
  
• IT professionals
  
• Data scientists
• Solution consultants
  
• Anyone interested in data science and innovation
  

Course Requirements

• Data science knowledge, preferably in one of the languages Python or R and TensorFlow
  
• Knowledge of the openSAP course Freedom of Data with SAP Data Hub is recommended
  

Content Expert

Matthias Sessler

Dr. Matthias Sessler is a Product Expert at SAP and leads the technical enablement for SAP Data Intelligence. His vision is to enable customers, partners, and internal development teams to make enterprise applications intelligent. 

Matthias has more than 15 years of experience in the SAP technology and SAP Leonardo Machine Learning area. He previously held several positions in presales, software development, and product management. In addition, he worked as a lecturer in digital technology and computer architecture at DHBW Mosbach.

With his academic background as physicist, one of his main focuses are the Data Science capabilities of SAP Data Intelligence. Matthias earned his PhD at CERN in collaboration with the University of Heidelberg, where he developed pattern recognition algorithms for finding the Higgs boson.