The Blockchain Architecture course develops skills in Blockchain functions, architectural models, technology and security. This course can be used to prepare for the Blockchain Architect Certification exam.

The IoT Architecture course develops skills in Internet of Things (IoT) technology and architecture, along with proficiency in radio protocols, telemetry messaging and IoT architecture layers. This course can be used to prepare for the IoT Architect Certification exam.

The Robotic Process Automation (RPA) course develops skills in RPA technologies, practices and business process automation models. This course can be used to prepare for the RPA Specialist Certification exam.

The Digital Business Technology course provides easy-to-understand, fundamental coverage of a broad range of contemporary IT technologies and associated IT practices. Coverage is intentionally non-technical and limited to explaining the strategic purpose and significance of each technology as it may relate to an organization’s business operations. Topics include Digital Transformation Solutions, Artificial Intelligence (AI), Robotic Process Automation (RPA), Cloud Computing, Blockchain, Internet of Things (IoT), Machine Learning, Big Data and Cybersecurity. This course can be used to prepare for the Digital Business Technology Professional Certification exam.

The Containerization Architecture course develops skills in containerization technology and architecture, along with proficiency in assessing, designing and securing highly available container-hosted services and solutions. This course can be used to prepare for the Containerization Architect Certification exam.

The Digital Transformation course provides a clear understanding of Digital Transformation from both business and technical perspectives and further develop fundamental skills in Digital Transformation practices and technologies. This course can be used to prepare for the Digital Transformation Specialist Certification exam.

The Fundamental SOA Design with Services & Microservices course establishes an essential understanding of the technologies and concepts associated with designing and composing API-driven services and microservices, as well as models and characteristics of service-oriented architecture. This course can be used to prepare for the SOA Professional Certification exam.

The Service API Design & Management course provides comprehensive coverage of API design techniques, coupling and granularity considerations, and API management practices including API versioning. Also covered are serialization protocols, as well as topics pertaining to REST and RPC protocols. This course can be used to prepare for the Service API Specialist Certification exam.

The Cloud Computing course develops knowledge and skills in Cloud Computing concepts, industry technologies, mechanisms and cloud delivery and deployment models. Also covered are business metrics, SLAs and topics pertaining to cloud security. This course can be used to prepare for the Cloud Technology Professional Certification exam.

The Big Data Analytics & Fundamental Data Science course develops skills in Big Data analytics and analysis, as well as data science fundamentals. This course can be used to prepare for the Big Data Science Professional Certification exam.

The Machine Learning course develops skills in Machine Learning practices, models and algorithms, as well as Machine Learning systems that can perform a range of data analysis processing tasks. This course can be used to prepare for the Machine Learning Specialist Certification exam.

The Quantum Computing course provides comprehensive coverage the concepts, technology models and infrastructure components that comprise contemporary quantum computing solutions, as well as guidance for how to utilize these solutions in IT enterprise environments. This course can be used to prepare for the Quantum Computing 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 NLP Engineering course provides in-depth coverage of natural language processing, NLP linguistics, text preprocessing and normalization and semantic analysis techniques, as well as Transformer models, sentiment analysis and emotion detection, dialogue systems and machine translation and transliteration. This course can be used to prepare for the NLP Engineer Certification exam.

The Cloud AI Fundamentals 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.