Next-Gen IT Courses

The Next-Gen IT curriculum from Arcitura is comprised of a series of 3-module specialist programs. Course delivery options can include private on-site workshops, live virtual training, public workshops or self-paced training via Study Kits or eLearning. Each module is a one-day course when taught by a Certified Trainer or can take 10-14 hours to complete via self-study.

DevOps Module 1
Fundamental DevOps

A comprehensive overview of DevOps practices, models and techniques, along with coverage of DevOps benefits, challenges and business and technology drivers. Also explained is how DevOps compares to traditional solution development and release approaches and how the application of DevOps can be monitored and measured for concrete business value.

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DevOps Module 2
DevOps in Practice

A course that delves into the application of DevOps practices and models by exploring how the DevOps lifecycle and its associated stages can be carried out and further identifying related challenges and considerations. In-depth coverage is provided for the application of Continuous Integration (CI) and Continuous Delivery (CD) approaches, along with an exploration of creating deployment pipelines and managing data flow, solution versions and tracking solution dependencies.

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DevOps Module 3
DevOps Lab

A lab during which participants apply the concepts, processes, techniques and metrics previously covered in order to complete a set of exercises. Specifically, participants are required to study case study backgrounds and carry out a series of exercises to establish DevOps processes and carry out DevOps stages and related techniques to address requirements and solve problems.

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Blockchain Module 1
Fundamental Blockchain

This course provides a clear, end-to-end understanding of how blockchain works. It breaks down blockchain technology and architecture in easy-to-understand concepts, terms and building blocks. Industry drivers and impacts of blockchain are explained, followed by plain English descriptions of each primary part of a blockchain system and step-by-step descriptions of how these parts work together.

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Blockchain Module 2
Blockchain Technology & Architecture

This course delves into blockchain technology architecture and the inner workings of blockchains by exploring a series of key design patterns, techniques and related architectural models, along with common technology mechanisms used to customize and optimize blockchain application designs in support of fulfilling business requirements.

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Blockchain Module 3
Blockchain Technology & Architecture Lab

This course module presents participants with a series of exercises and problems that are designed to test their ability to apply their knowledge of topics covered in previous courses. Completing this lab will help highlight areas that require further attention and will further prove hands-on proficiency in blockchain technologies, mechanisms and security controls as they are applied and combined to solve real-world problems.

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Machine Learning Module 1
Fundamental Machine Learning

This course provides an easy-to-understand overview of machine learning for anyone interested in how it works, what it can and cannot do and how it is commonly utilized in support of business goals. The course covers common algorithm types and further explains how machine learning systems work behind the scenes. The base course materials are accompanied with an informational supplement covering a range of common algorithms and practices.

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Machine Learning Module 2
Advanced Machine Learning

This course delves into the many algorithms, methods and models of contemporary machine learning practices to explore how a range of different business problems can be solved by utilizing and combining proven machine learning techniques.

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Machine Learning Module 3
Machine Learning Lab

This course module presents participants with a series of exercises and problems that are designed to test their ability to apply their knowledge of topics covered in previous courses. Completing this lab will help highlight areas that require further attention and will further prove proficiency in machine learning systems and techniques, as they are applied and combined to solve real-world problems.

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Artificial Intelligence Module 1
Fundamental Artificial Intelligence

This course provides essential coverage of artificial intelligence and neural networks in easy-to-understand, plain English. The course provides concrete coverage of the primary parts of AI, including learning approaches, functional areas that AI systems are used for and a thorough introduction to neural networks, how they exist, how they work and how they can be used to process information. The course establishes the five primary business requirements AI systems and neural networks are used for, and then maps individual practices, learning approaches, functionalities and neural network types to these business categories and to each other, so that there is a clear understanding of the purpose and role of each topic covered. The course further establishes a step-by-step process for assembling an AI system, thereby illustrating how and when different practices and components of AI systems with neural networks need to be defined and applied. Finally, the course provides a set of key principles and best practices for AI projects.

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Artificial Intelligence Module 2
Advanced Artificial Intelligence

This course covers a series of practices for preparing and working with data for training and running contemporary AI systems and neural networks. It further provides techniques for designing and optimizing neural networks, including approaches for measuring and tuning neural network model performance. The practices and techniques are documented as design patterns that can be applied individually or in different combinations to address a range of common AI system problems and requirements. The patterns are further mapped to the learning approaches, functional areas and neural network types that were introduced in Module 1: Fundamental Artificial Intelligence.

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Artificial Intelligence Module 3
Artificial Intelligence Lab

This course module presents participants with a series of exercises and problems that are designed to test their ability to apply their knowledge of topics covered in previous courses. Completing this lab will help highlight areas that require further attention and will further prove proficiency in AI, machine learning and deep learning systems and neural network architectures, as they are applied and combined to solve real-world problems.

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Internet of Things Module 1
Fundamental IoT

This course covers the essentials of the field of Internet of Things (IoT) from both business and technical aspects. Fundamental IoT use cases, concepts, models and technologies are covered in plain English, along with introductory coverage of IoT architecture and IoT messaging with REST, HTTP and CoAp.

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Internet of Things Module 2
IoT Technology & Architecture 

This course provides a drill-down into key areas of IoT technology architecture and enabling technologies by breaking down IoT environments into individual building blocks via design patterns and associated implementation mechanisms. Layered architectural models are covered, along with design techniques and feature-sets covering the processing of telemetry data, positioning of control logic, performance optimization, as well as addressing scalability and reliability concerns.

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Internet of Things Module 3
IoT Technology & Architecture Lab

This course module presents participants with a series of exercises and problems that are designed to test their ability to apply their knowledge of topics covered in previous courses. Completing this lab will help highlight areas that require further attention and will help prove hands-on proficiency in IoT concepts, technologies, architecture models and devices, as they are applied and combined to solve real-world problems.

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Containerization Module 1
Fundamental Containerization

This course provides comprehensive coverage of containerization models, technologies, mechanisms and environments. How the utilization of containers impacts both the technology and business of an organization are covered, along with many technical features, characteristics and deployment environments.

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Containerization Module 2
Containerization Technology & Architecture

This course provides a deep-dive into containerization architectures, hosting models, deployment models and utilization by services and applications. Numerous advanced topics are covered, including high performance requirements, clustering, security and lifecycle management.

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Containerization Module 3
Containerization Technology & Architecture Lab

This course module presents participants with a series of exercises and problems that are designed to test their ability to apply their knowledge of topics covered in previous courses. Completing this lab will help highlight areas that require further attention and will help prove hands-on proficiency in containerization concepts, technologies, architecture models and pattern application, as they are utilized and combined to solve real-world problems.

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