The AI Governance & Ethics course establishes the foundations of AI governance with precepts, processes and roles that address the on-going governance of predictive and generative AI systems. The governance of training and production data is covered, along with controls and considerations associated with ethical practice, model explainability and regulatory compliance. This course further extends AI governance practices and considerations in cloud-based environments. This course can be used to prepare for the AI Governance & Ethics Specialist Certification exam.

The Generative AI course provides essential coverage of generative AI concepts, models, best practices, and neural networks, including Generative Adversarial Networks (GANs), Variational Encoders (VAEs) and Transformer models. The course is focused on exploring the application of generative AI within a range of business scenarios. This course can be used to prepare for the Generative AI Specialist Certification exam.

The AI Professional Consulting course provides essential coverage of the most important and relevant topics associated with predictive AI, generative AI, as well as fundamental AI engineering and architecture. Also includes business case development techniques for AI projects and change management and AI adoption strategies. This course can be used to prepare for the AI Consultant Certification exam.

The Cloud AI Architecture & Design course covers the technology architecture of cloud-based AI systems, including cloud automation and infrastructure relevant to AI processing, serverless architectural models for AI, AI system monitoring, logging and auditing, AI in multi-cloud and hybrid architectures, as well as AI-related cloud services and infrastructure models. This course can be used to prepare for the Cloud AI Architect Certification exam.

The AI Architecture & Design course covers fundamental and advanced AI systems and technology architecture topics, including design principles, distributed AI computing and scalability and reliability infrastructure, decision-making logic, performance optimization, security and enterprise architecture integration. This course can be used to prepare for the AI Architect Certification exam.

The Cloud AI Technology & Automation course provides essential coverage of concepts and technologies for cloud-based AI systems, including infrastructure resources for reliability and scaling, AI data management, AI system deployment models, using containerization with AI systems, cloud AI serverless architecture, as well as integration of AI services with cloud-native applications. This course can be used to prepare for the Cloud AI Professional Certification exam.

The Essential AI course provides coverage of predictive AI and generative AI concepts, benefits, challenges and risks. Suitable for IT and business professionals that would like to receive a fundamental understanding of how contemporary AI works and how it can be applied in the real world. This course can be used to prepare for the AI Professional Certification exam.

The Predictive AI Engineering course covers numerous fundamental and advanced AI engineering topics specific to predictive AI systems, including a neural network design, model training approaches, data preprocessing and feature engineering, model evaluation, validation, scaling, optimization, data bias avoidance, and many more. This course can be used to prepare for the Predictive AI Engineer Certification exam.

The Generative AI Engineering course covers a wide range fundamental and advanced AI engineering topics specific to the unique requirements of generative AI systems and on-demand content creation. Topics include generative neural network design, model training approaches, creative content manipulation, model evaluation, validation, scaling, optimization, data bias and concept drift avoidance, and many more. This course can be used to prepare for the Generative AI Engineer Certification exam.