DIGITAL ENGINEERING: IoT & EDGE: ENTRY LEVEL CERTIFICATIONS

Energy management systems (EMS) using sensors and analytics utilize real-time data collection and advanced analytics to optimize energy consumption, reduce costs, and improve efficiency. These systems leverage the Internet of Things (IoT) to gather data from various sources like smart meters, sensors, and equipment, allowing for better monitoring, control, and decision-making.

This course is suitable for professionals working in Smart cities, large buildings/campuses, sustainability analyst, civil projects and digital factory planning domains.

AI software solutions enable companies to  unlock the potential of their frontline operations, harnessing the power of automation to make better business decisions.  AI software applies from retail to healthcare, logistics, and manufacturing, that digitize and automate workflows, creating new ways of working for frontline operations, equipping people with AI-enabled solutions intelligently integrated into the processes that are streamlined to enhance operational agility, workflows are automated to increase efficiency, and work is made easier—every day.

This course is suitable for professionals across all business & industry to understand the digital platform to manage a connected, smart enterprise.

Machine monitoring software helps manufacturers maximise output, productivity and efficiency. A production monitoring system also helps manufacturers identify bottlenecks and other issues on their shop floor. A production monitoring system is critical to the success of a manufacturer. Seamless data collection makes it possible to view production at a deep level of detail. This makes the individual processes in your production consistently comprehensible. Secure storage of your data also enables a reliable comparison of whether the processes have changed: the deviations immediately reveal sources of defects, quality fluctuations or side effects immediately. 

This course is essential to lay the foundation of a smart, connected enterprise.

This course introduces a comprehensive study of an integrated AI powered platform to drive digital transformation by integrating sensors data, analytics algorithms, ML and AI engine to study the performance of constituent units across an enterprise and take decisions in real time. AI engine automates workflows through advanced simulation, data analytics, artificial intelligence (AI), and high-performance computing (HPC). The platform optimizes operations, while AI-driven analytics enhance predictive maintenance and efficiency. By enabling end-to-end digital transformation, the platform delivers the intelligence and computational power needed to maximize productivity and innovation across the entire supply chain.

This course will help the learners understand and build intelligent copilots and AI agents effortlessly with a code-optional interface that allows users to create advanced AI-driven solutions without extensive programming knowledge. Design and deploy these smart assistants to automate tasks, provide real-time support, and enhance operator experiences. Additionally, enable seamless interaction with complex documentation by querying it using natural language, making it easier to access and understand critical information quickly and efficiently.

IoT devices connects the devices and with connected devices comes data and with data comes opportunity. Tapping into the enormous flow of IoT data can transform enterprises into digital businesses and facilitate new business models, increase efficiency and improve customer engagement.

(Internet of Things) test automation frameworks are tools and frameworks designed specifically for automating the testing of IoT devices, systems and applications. These frameworks provide a structured approach to automate the testing process, manage test cases, simulate IoT environments, and generate test data. 

This course is a foundational course for professionals planning to move into digital factory and industry 4.0 domain.

IoT application development presents an enormous opportunity to reshape entire industries. IoT application development requires many, disparate technologies. IoT solutions are typically composed of a complex, heterogeneous mix of IoT endpoints, platforms, back-end systems and data (e.g. sensors, actuators, processors, embedded software, local and long-range connectivity, middleware, apps, analytics, machine learning, etc.). In addition, building IoT applications requires scarce, hard-to-find specialist skills. This course develops a deep understanding of IoT, big data and machine learning technologies required to make sense of real-time data streams.

This course will enable learners to develop Smart apps with the understanding of the development platform.

This course is for professionals who want to get skilled in managing a development platform with diverse capabilities like geofencing and an integrated simulation dashboard for monitoring. This course will help learners to connect all the data and unify the metrics, decide where your device can work and when it should alert, create custom alerts, Implement your business logic with a visual low-code interface. Define the data flow for your automations, alerts, or custom KPIs effortlessly.