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This AWS SageMaker Canvas course will help you become a machine learning expert and will enhance your skills by offering you comprehensive knowledge and the required hands-on experience on this newly launched cloud-based ML tool, by solving real-time industry-based projects, without needing any complex coding expertise.

Learn the process to design and develop big data engineering projects using Apache Spark. This example-driven advanced-level course will help you understand real-time stream processing using Apache Spark and you can apply that knowledge to build real-time stream processing solutions.

This course will help you understand the importance of Linux PAM (Pluggable Authentication Module) and its configuration file, module interface, control flags, and modules. You will also discover PAM-aware services and stacks and learn how to verify if a service or program is linked with PAM. No prior knowledge of Linux is required to take this course.

The Management's Guide to Understanding Risk Management Decisions in Cybersecurity and Information Technology (IT)!

Want to learn how to use Maven and SonarQube effectively for code building and code quality analysis as a DevOps engineer? Then you are in the right place. This learner-centered hands-on course will help you gain confidence in using important DevOps tools such as SVN, Maven, Jenkins, Chef, Puppet, Nagios, Splunk, Selenium, and more. Some basic knowledge of Linux, Git, and AWS EC2 will help you get the most out of this course.

Learn how to build real-world applications using Spring Framework 5 and Spring Boot 2

Delve into big data streaming with Azure using Event Hubs, Data Lake, and Azure Stream Analytics

Learn how to code in HTML from scratch. Perfect for beginners and anyone who wants to learn HTML

This course will enable you to master Docker fundamentals that are required for Spring Boot developers. You'll learn the essential concepts needed to create Dockerfiles for your projects using Docker, Docker Compose, Volumes and various Docker commands. You will launch multiple Docker containers for your microservices that will communicate with each other.

Kickstart your journey into deep learning and gain a strong understanding of deep neural networks through practical exercises. Develop your intuition and learn the fundamentals of artificial neural networks, activation functions, and loss functions. Gain practical experience with Python and TensorFlow 2.x, and apply your skills to build powerful deep learning models.