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Our Courses
Blockchain Scalability and its Foundations in Distributed Systems
Blockchain promises to disrupt industries once it will be efficient at large scale. In this course, you will learn how to make blockchain scale. You will learn about the foundational problem of distributed computing, consensus, that is key to create blocks securely. By illustrating limitations of mainstream blockchains, this course will indicate how to improve the technology in terms of security and efficiency.
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Course by
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Self Paced
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11 hours
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English
Introduction to the Multiphase Optimization Strategy (MOST)
This course is aimed at intervention scientists working in any area--including public health, education, criminal justice, and others—interested in learning about an innovative framework for conducting intervention research.
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Course by
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Self Paced
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18 hours
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English
Omnibond: Creating an HPC Environment in Google Cloud with CloudyCluster
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you create a complete turn-key High Performance Computing (HPC) environment in Google Cloud. This environment will provide the familiar look and feel of on-prem HPC systems but with the added elasticity and scalability of Google Cloud. In this lab you see how CloudyCluster can easily create HPC/HTC jobs that will run on-prem or in CloudyCluster on Google Cloud. You can rely on the familiar look and feel of a standard HPC environment while embracing the capabilities and elasticity of Google Cloud.
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Course by
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Self Paced
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2 hours
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English
Introduction to NoSQL Databases
Get started with NoSQL Databases with this beginner-friendly introductory course! This course will provide technical, hands-on knowledge of NoSQL databases and Database-as-a-Service (DaaS) offerings. With the advent of Big Data and agile development methodologies, NoSQL databases have gained a lot of relevance in the database landscape. Their main advantage is the ability to handle scalability and flexibility issues modern applications raise.
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Course by
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Self Paced
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18 hours
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English
Building Cloud Services with the Java Spring Framework
This MOOC describes by example how to build cloud services via the use of object-oriented design techniques; Java programming language features; Java Servlets, the Java Spring Framework; and cloud computing platforms, such as Amazon Web Services. Due to the importance of building secure and scalable mobile/cloud platforms, this MOOC will not only show you how to build cloud services, but how to do so securely, scalably, and efficiently.
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Course by
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Self Paced
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14 hours
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English
Entrepreneurship II: Preparing for Launch
This course builds on previous concepts and outlines strategies and tactics for forming, financing, and launching a new venture. Topics to be addressed will include building the new venture’s initial management team, identifying and reaching out to early customers, developing financial plans, raising startup and initial growth financing, and preparing for and managing rapid growth.
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Course by
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Self Paced
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17 hours
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English
Cloud Computing Concepts, Part 1
Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing. Some of these concepts include: clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, and much, much more! Know how these systems work from the inside out.
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Course by
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Self Paced
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23 hours
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English
Advanced Machine Learning and Signal Processing
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<<\n\nThis course, Advanced Machine Learning and Signal Processing, is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines.
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Course by
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28 hours
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English
Cloud Computing Concepts: Part 2
Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies – all centered around distributed systems. Learn about such fundamental distributed computing "concepts" for cloud computing. Some of these concepts include: clouds, MapReduce, key-value/NoSQL stores, classical distributed algorithms, widely-used distributed algorithms, scalability, trending areas, and much, much more! Know how these systems work from the inside out.
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Course by
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Self Paced
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20 hours
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English