Machine learning enables computers to learn from large amounts of data without being explicitly programmed to do so. We can already see how machine learning gives rise to new intelligent applications, from self-driving cars to intelligent assistants on our smartphones.
Increasingly, businesses recognize the importance of using machine learning to transform their data assets into business value. However, many companies are unsure how machine learning can be applied to solve problems in an enterprise context. As the world’s most relevant enterprise data is part of SAP’s system and business network, SAP aspires to make all its enterprise solutions intelligent and help customers to leverage their data.
The objective of this course is to help business decision makers understand the significance of machine learning for enterprise computing. After taking this course, participants should be aware of recent advances in machine learning, have an understanding of the basic concepts involved and how business problems can be solved with machine learning. In particular, the course gives guidelines on how to formulate a business problem as a machine learning problem. This course is mainly aimed at a business audience. In the meantime, we are working on another machine learning course for a developer audience, and expect this course to be available next year.
• Starting from: November 14, 2016, 09:00 UTC. (What does this mean?)
• Duration: The course is open for 5 weeks
• Effort: 2-3 hours in total
• Course assignment: You can take the course assignment at any time whilst the course is open.
• Course closure: December 20, 2016, 09:00 UTC
• Course language: English
• How is an openSAP course structured?
Unit 1: Intelligent Applications Powered by Machine Learning
Unit 2: What Is Machine Learning?
Unit 3: From Business Problem to Machine Learning: A Recipe
Unit 4: Machine Learning in Enterprise Computing
Unit 5: Application Example: Natural Language Processing
Unit 6: Application Example: Computer Vision
Unit 7: Key Takeaways
• Solution managers
• Executive managers
If you would like to enroll for this course, there are no formal prerequisites or limitations. The course is free and open for everyone. Just register for an account on openSAP and go for the course!Enroll me for this course
This course was held from Nov 14, 2016 through Dec 20, 2016.
11402 learners enrolled.
Dr. Daniel Dahlmeier is head of machine learning for Sales and Service at SAP. Daniel manages a cross-functional, start-up-like team to make the enterprise applications we use every day more intelligent, and create a small revolution in the way we work.
Daniel’s background is in natural language processing and machine learning. He holds a PhD in computer science from the National University of Singapore and a Master in Computer Science from the Karlsruhe Institute of Technology.
Dr. Markus L. Noga is vice president of Machine Learning at SAP. His team is on a mission to make all enterprise applications intelligent by applying machine learning, deep learning and data science to real-world business challenges. Markus previously served as VP for New Business & Portfolio at SAP, where his team launched the SAP HANA Enterprise Cloud, and as a director in the Corporate Strategy Group. Prior to that, he was a principal at Booz & Company, advising blue chip customers in a dozen countries.
Markus holds a PhD in computer science from the Karlsruhe Institute of Technology, where his research focused on the optimization of document processing. An early digital native, he started programming computers at the age of seven, and shows no signs of stopping. He has a passion for building businesses, and has served as a mentor for promising startups at TechStars and other accelerators.