Machine Learning with Apache SystemML

This IBM certified course comprises five purposely designed modules that take you on a carefully defined learning journey.

It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 3-4 hours per week, you will complete the course in 2 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And don’t worry, you’re not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.

The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include videos, reading material, and online exam questions.

As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services will vary across packages.

Once you have successfully completed the course, you will earn your IBM Certificate.

After completing this course, you will be able to :

• Understand how the optimizers function is handled by SystemML.
• Understand the purpose of SystemML and know its alternatives.
• Compare performances of SystemML with the alternatives.
• Use MLContext to interact with SystemML (in Scala).
• Describe and use a number of SystemML algorithms.
• Understand DML and how to use it.
• Describe the optimizer stack.
• Understand why SystemML is faster than single-node R.

• Data scientists looking to develop machine learning algorithms independent of data and cluster characteristics.
• Individuals who wish to use Apache SystemML for automatic scaling and to optimize machine learning code.
• Big data engineers seeking to explore Apache SystemML to improve their work efficiency.

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