Learning about controls, the Internet of Things, and artificial intelligence in the factory environment. Participants acquire skills in defining and developing control systems, IoT, and AI solutions in a manufacturing environment.
Suggested by: Coursera (What is Coursera?)
No prior knowledge required
No unnecessary risks
Sure! Here’s an HTML bullet list of the skills a learner will acquire from the course:
- Circuit Design Skill
- Circuit Simulation Tools
- Programming
- Embedded C
- Python
- PCB Design Skills
- PCB Design Software
- Software Integration Skills
- Libraries and Functions for Application
This structure organizes the skills into a clear and readable list format.
To advance the engineering skills required for digital factories, the offered specialization in Intelligent Digital Factories provides those interested with a strong foundation in microcontrollers, which includes:
Learners get the opportunity to explore:
With industry examples and integration strategies with:
The data collected and processed is transmitted and stored in the cloud, thereby promoting business intelligence. This part of the IoT component is presented along with various IoT solutions in the industry such as:
Then, another component of the specialization promotes skills in AI algorithms:
Along with Edge Computing strategies such as:
Which include:
Finally, the specialization guides learners on AI applications in real engineering problems in areas such as:
like:
Learners will develop digitization skills by:
Overall, this specialization supports the learning of interdisciplinary engineers and equips them with new technological skills, so that they will be able to fulfill various roles in digital factories of Industry 5.0 in the future.
Today, there is a paradigm shift in every organization towards digital transformation in line with the rapid growth of industrial automation. Since automation directly impacts the return on investment, every organization, be it in the field of design, manufacturing, assembly or logistics, is successfully transforming into digital industries. One of the key components of this transformation is the appreciation of fast, compact and multi-functional microcontrollers. The global microcontroller market is estimated to grow at a CAGR of 7.6% during 2021-2023.
This creates a large employment opportunity for the engineering community in the coming decade in the field of digital transformation. The main objective of this course is to prepare learners for this field of engineering. Therefore, the course “Microcontrollers and Industrial Applications” has been designed with a clear vision and a path that details the fundamentals of microcontrollers, microcontroller design methodologies, and hands-on training on application-specific integrated boards and real-time industrial applications. The course includes complete demonstrations through a digital platform with real-world examples, providing full engagement of the learners. The course also provides practical knowledge and experience about integrated development boards and integrated development environment (IDE) tools. Learners will be introduced to the versatile development boards preferred in industrial applications. The teaching methodology of the course allows learners to gain good insights into the demonstrations and stimulate their creativity. The course discourse encourages the learner to develop creative integrated solutions for real-world applications.
Today, there is a paradigm shift in every organization towards digital transformation in line with the rapid growth of industrial automation. Since automation directly impacts the return on investment, every organization, whether in the field of design, manufacturing, assembly or logistics, is successfully transforming into digital industries. The main objective of this course is to prepare learners with an advanced technical process of data collection in digital industries. A comprehensive course on “Industrial Internet of Things” provides an in-depth exploration of the evolution of the industry, from the stages of the industrial revolution to the changing landscape of IIoT.
The course begins with a historical overview of the industry’s evolution, understanding the principles of IIoT, and analyzing the drivers, benefits, and challenges of IoT through real-world examples such as dam water level monitoring and STP monitoring. The course then delves into solar power plant management, railway service monitoring, and a breakdown of IIoT architecture components. Learner engagement includes hands-on experiences with message monitoring and dairy processing. The course gets learners to understand the basics of sensors, their types, and selection criteria. The course also explores applications in pharmaceuticals, power distribution, and energy metering. Hands-on machine condition demonstrations highlight real-world relevance, and delve into technology updates, gate types, and configurations. Practical insights are gained through product packaging, bottle manufacturing, and pulse counting and video analytics demonstrations. Understand IoT connections, wireless protocols, and follow an IIoT example with a wheel loader. Real-world applications in the course include automotive component casting, diesel generator monitoring, aircraft parts manufacturing, and bulk milk refrigeration monitoring. The course concludes with a discussion of the IIoT security problem and connected work solution cases.
With the paradigm shift of digital transformation in industries, there is a large amount of digital data in cloud storage related to people, materials and machines of the organization. This data contains a lot of information that can be used for process planning, failure prediction and business optimization. This course is designed to provide learners with the various Strategic principles of artificial intelligence theory, which help extract this information from the existing data. The impact of AI in every field is growing along with programming.
The course introduces appropriate programming skills within the modules, and learners will be able to learn by practicing many problems. The long-term vision of AI with Edge operations is described in the course along with the principles required to implement Edge AI. Learners will be able to distinguish and defend between cloud and edge operations based on real-world problems. Various practice problems with appropriate software and hardware architecture support learning Edge AI with appropriate metrics. Overall, learners will experience an exciting journey of understanding and implementing AI algorithms, processing the algorithms for the Edge, and implementing Edge AI sample solutions. Edge AI products available in the market are introduced to learners, providing them with the ability to link their AI skills with appropriate career options.
The course begins with a transformative learning journey that explores the power of artificial intelligence in diverse fields such as electrical, mechanical, civil, and general applications. This course elevates learners’ insights into AI in line with practical applications by bridging the gap between theory and practical applications. The course also provides hands-on experience in implementing AI algorithms in potential applications.
The healthcare examples provided in the course will enlighten learners with a definitive perspective on real-world solutions. This course is designed to introduce key AI principles required for real-time electrical engineering applications such as load forecasting and fault diagnosis in substations. The course also addresses the application of AI in mechanical engineering, including seismic data processing, geological imaging, and reservoir engineering. Civil engineering learners will learn about the role of AI in collecting data from the cloud on construction sites and its applications in transportation engineering and traffic forecasting.
Join the future of AI with a focus on machine and deep learning operations to gain insights that enable you to discern and apply AI solutions to real-world challenges. Experience software-supported exercises to gain a comprehensive understanding of AI metrics. Strengthen your skills and broaden your horizons with the power of AI.
