This course is aimed at preparing individuals to gain knowledge, skills, and abilities to demonstrate an advanced knowledge of the Amazon Web Services (AWS) platform. This course covers advanced topics such as cloud costs, billing practices, overview of core AWS services, including computer, network, databases, and storage. Material covered will also include identifying resources for technology support, and identify resources available for billing support.

This course is aimed at preparing individuals to gain knowledge, skills, and abilities to demonstrate intermediate knowledge of the AWS platform. This course offers an intermediate understanding of Amazon Web Services (AWS) cloud security best practices, AWS cloud economics, defining the AWS shared responsibility model, AWS access management capabilities, and resources for security support.

This course is aimed at preparing individuals to gain knowledge, skills, and abilities to demonstrate basic knowledge of the Amazon Web Services (AWS) platform. The student will learn the values of using the cloud as a service, understand the AWS shared responsibility model, and cloud security best practices. This course also discusses cloud economics, architecture design principles, as well as learning the AWS shared responsibility model.

This course focuses on best practices for managers in gaining control over AI implementations and ethical data analysis. The course addresses the responsibilities of a data science manager in overseeing automated decision making that goes beyond the delivery of the modeling results and deployment of the systems. The course studies improving the data monitoring procedures for adhering to a higher ethical standard and responsible data management within an organization.

This course introduces you to the basics of artificial intelligence, data science, and data analytics for the handling of massive databases. The course covers concepts and data mining for big data analytics and introduces you to data visualization and some basic statistical concepts for data science.

This course provides students with the understanding of the key principles, techniques, and applications associated with artificial intelligence (AI) for business strategies and transformation. Students will gain knowledge about knowledge representation, game theory, search problems using computational theories. The course will also explore different issues surrounding AI such as ethics and bias. Some key concepts and terms like deep learning and neural networks will also be covered as part of the course.

In this course, students will examine fundamental concepts and theories related to machine learning. Students will explore the different machine learning models that include: supervised and unsupervised learning, and reinforcement learning. Students will gain an understanding of applications of machine learning in different areas and how to select the appropriate model for a particular scenario. Students will also relate machines learning to other related areas like artificial intelligence, data analytics, and data science.

Amazon App Development I examines Android mobile application development for Amazon devices utilizing Android Studio. The two primary devices include Amazon Fire TB and Fire tablets. Topics will include Amazon App development tools and frameworks, Amazon app guidelines, storyboarding, and user interface design principles.