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Today, there exists a changing paradigm for every organization towards Digital Transformation in alignment with rapid growth of Industrial Automation. As automation impacts the business-returns directly, every organization, be it Designing, Manufacturing, Assembling or Logistics sector, sincerely is getting transformed as Digital Industries. The major objective of this course is to equip learners with advanced technical process of Data Collection in such Digital Industries. Thus, comprehensive course on 鈥淎pplied Industrial IoT鈥� provides a deep dive into the evolution of industrialization, from the phases of the Industrial Revolution to the transformative landscape of the Industrial Internet of Things (IIoT). The course begins with a historical review of industrial evolution, understanding core IIoT concepts, and dissecting the drivers, benefits, and challenges of IoT through real-world examples like Dam Water Level Monitoring and STP Monitoring. Next, the course delves into Solar Plant Management, Utility Monitoring in Railways, and a detailed breakdown of IIoT Architecture components. Engagements for learners include hands-on experiences with Annunciator Monitoring and Dairy Product Processing. The course makes the learners understand sensor fundamentals, types, and selection criteria. The course also explores applications in Pharma, Electricity distribution, and Energy Measurement. Practical demonstrations on Machine Status highlight real-world relevance, explore Edge Computing intricacies, Gateway types, and configurations. Practical insights are gained through Packaging, Bottle Manufacturing, and demonstrations on Pulse counting and Video Analytics. Grasp IoT Connectivity, Wireless Protocols, and witness an IIoT example with a Wheel Loader. Real-world applications in the course include Automotive Component Casting, Diesel Generators Monitoring, Aerospace Parts Manufacturing, and Bulk Milk Cooler Monitoring. Finally, the course caps off with IIoT Security Concerns and a case study on an IoT Connected Workplace Solution.

With the paradigm shift of Digital Transformation in industries, there exists a huge volume of digital data in cloud storage about the Men, Materials and Machines of the organization. This data incurs a lot of information which could be used for process planning, predictive failures and business optimization. This course aims to equip the learners with various strategic principles of Artificial Intelligence theory which helps to extract such information from the pool of available data. The reach of AI in every area is consistently growing along with the features of programming. The course introduces appropriate programming skills blended in the modules and the learners will be able to learn by doing lots of practice problems. The long-term vision of AI, with Edge operations are explained in the course along with the principles required in implementing Edge AI. The learner can distinguish and will be able to segment the cloud and edge-based operations appropriately for the real-world problems. The different exercise problems with relevant software and hardware architecture support the learning of Edge AI with suitable metrics. On the whole the learners will get an exciting journey of understanding and applying AI algorithms, processing the algorithms for edge and implementing sample edge AI solutions. Edge AI products available in the market are introduced to the learners and this provides the learners with an ability to map their AI skills with suitable upcoming career options.

The course Embarks on a transformative learning journey exploring the power of Artificial Intelligence across diverse fields such as electrical, mechanical, civil, and general applications. This course elevates the learner鈥檚 insight on AI towards the real-world practices by bridging the gap between theory and practical applications. It also provides hands-on experience of applying AI algorithms into potential applications. The examples of AI in healthcare provided in the course will enlighten the learners with an end-to-end perspective of real-world solutions. This course is crafted to introduce key AI principles required for challenging real-time applications of electrical engineering like load predictions and fault diagnosis in substations. The course also covers the application of AI in mechanical engineering, encompassing seismic data processing, geo-modelling, and reservoir engineering. The civil engineering learners will learn about AI's role in cloud data collection at construction sites and its applications in transport engineering and road traffic prediction. Immerse yourself in the future of AI with a focus on Machine and Deep learning operations, gaining insights that enable you to distinguish and apply AI based solutions to real-world challenges. Explore hands-on exercises with software support, gaining a comprehensive understanding of AI metrics. Enhance your skills and broaden your horizons with the power of AI.