Course Tag: path6

P6-C3: Artificial intelligence and expert systems

Course 3: Artificial intelligence and expert systems

Course agenda

In this course, you will find:

  • Overview of AI, its branches and applications in various industries
  • Expert systems and knowledge representation for capturing and utilizing human expertise and making knowledge-based decisions
  • Machine learning (supervised learning, unsupervised learning, and reinforcement learning, deep learning and neural networks, federated learning)
  • Human factors in AI based decision making, Explainable AI (XAI), enhancing interpretability and transparency of AI systems
  • The adoption of AI to empower the working activities and improve working processes
  • Examples of practical applications and of software solutions (AI-powered automation, integration of AI in the workflow, AI for Big Data, etc.)

Organizational info:

  • This course contains 7 lessons.
  • Lessons include written content.
  • To complete this course, you need 180 minutes.
  • You can pause the course anytime and return to where you finished whenever you want.
  • You can follow the course as it flows or at your own pace, rearranging the order of the lessons.
  • At the end of the course, you will take a test containing 8 questions. 
  • You can take the test 2 times, if necessary. 
  • You must score min. 85% of the correct answers to receive the official certificate of completion.

Need more details?

Participants’ Pains

We know that…

By facing AI-related concepts, students may face difficulties in understanding how to capture and utilize human expertise to make knowledge-based decisions. Also, diversity and a number of machine-learning approaches can be challenging to understand.

For the integration of AI in working activities, it is necessary to understand organizational dynamics, change management, and the practical challenges associated with integrating AI into existing workflows. Understanding how to implement AI in real-world scenarios requires practical skills that may be lacking.

Following the progress in AI-related technologies and industry trends can be challenging and time-consuming, especially considering the continuous development of new algorithms and technologies. Moreover, the rapid evolution of AI introduces the pain point of potential skill obsolescence, as students may struggle to maintain relevance in the job market without ongoing training.

Participants’ Gains

So, we developed this course, in which…

This knowledge provides a foundation for understanding the broad impact of AI technologies. Understanding expert systems and knowledge representation equips students with the skills to capture human expertise in a structured manner. Mastery of machine learning concepts provides students with a strong foundation in the core techniques driving AI advancements

Understanding the adoption of AI to empower working activities and improve processes enables students to envision and contribute to the integration of AI in various industries. This knowledge is particularly relevant for the evolving workplace where AI technologies are transforming traditional workflows.

It enhances students’ employability in a variety of industries where AI technologies are increasingly becoming integral. From data science roles to AI research and development, students can pursue diverse career paths. Having a deep understanding of AI applications, students may identify opportunities for innovation and entrepreneurship.

P6-C2: Human-machine interaction, touch interfaces, and accessible GUIs

Course 2: Human-machine interaction, touch interfaces, and accessible GUIs

Course agenda

In this course, you will find:

  • Human-machine interaction and its role in Industry 4.0.
  • Interface technologies (touch, voice, gesture, haptic and multimodal).
  • HMIs for industrial settings (harsh environments, safety requirements, visibility in varying lighting conditions, and usability with protective equipment).
  • Accessible GUI design (user-centered design, cognitive load, user experience (UX), design principles regarding accessibility).
  • Emerging trends, i.e., augmented reality-based remote assistance, wearable interfaces, and brain-computer interfaces, etc.
  • The adoption of VR/AR technologies to create immersive experiences for workers and workplaces.
  • Examples of practical applications and software solutions (e.g. SCADA, HMI, DCS, PLC).

Organizational info:

  • This course contains 6 lessons.
  • Lessons include written content, visual content, additional materials and video links.
  • To complete this course, you need 120 minutes.
  • You can pause the course anytime and return to where you finished whenever you want.
  • You can follow the course as it flows or at your own pace, rearranging the order of the lessons.
  • At the end of the course, you will take a test containing 8 questions. 
  • You can take the test 2 times, if necessary. 
  • You must score min. 85% of the correct answers to receive the official certificate of completion.

Need more details?

Participants’ Pains

We know that…

The technical complexity in different aspects of human-machine interaction, interface technologies, and emerging trends can be challenging for individuals without a strong technical background. It can be challenging to grasp concepts such as feedback mechanisms, input-output systems, and the underlying algorithms that govern these interactions.

The course requires knowledge from multiple disciplines, such as psychology, engineering, design, and human-computer interaction. Interdisciplinarity brings students different specialized languages, research methods, and problem-solving approaches.

Limited access to resources and lack of practical experience can lead to a shallow understanding of practical skills and hands-on experience in implementing and testing the discussed technologies in real-world scenarios. Also, it can influence participants’ inclusion in the labor market with its industrial requirements and limitations, such as harsh environments, safety requirements, visibility in varying lighting conditions, and usability with protective equipment. So, these practical considerations may pose challenges for learners unfamiliar with industrial contexts.

Participants’ Gains

So, we developed this course, in which…

Students will gain competencies in various interface technologies (touch, voice, gesture, haptic, multimodal) and software solutions to enhance technological proficiency, thus preparing them for roles that require expertise in Industry 4.0 technologies. Awareness of emerging trends, such as augmented reality-based remote assistance, wearable interfaces, and brain-computer interfaces, prepares students to adapt to evolving technologies, positioning them as innovators in the field.

Gaining multidisciplinary knowledge through exposure to human-machine interaction, interface technologies, and related topics allows students to bridge gaps between fields such as engineering, psychology, design, and computer science. Interdisciplinary courses encourage collaboration between individuals with diverse backgrounds. Students develop effective communication skills and learn how to work in teams, preparing them for collaborative environments in the workforce.

The acquired knowledge on this topic will allow students to adapt to evolving technologies, positioning them as innovators in the field. Employers in various sectors seek professionals with expertise in human-machine interaction and interface technologies.

P6-C1: Internet of Things (IoT) in combination with advanced mobile connectivity (5G)

Course 1: Internet of Things (IoT) in combination with advanced mobile connectivity (5G)

Course agenda

In this course, you will find:

  • What is IoT (main principles, integration of physical and digital systems)
  • Architecture and components of an IoT system (different types of sensors and devices used in IoT)
  • Connectivity options for IoT devices and the importance of 5G in data gathering, transferring and processing
  • Integration with other technologies, i.e., cloud computing, big data analytics, artificial intelligence, and robotics
  • Security and privacy in the context of IoT
  • Impacts and advantages for workers and processes in the organizations
  • Examples of practical applications (smart office, warehouse operations, manufacturing, etc.)

Organizational info:

  • This course contains 7 lessons.
  • Lessons include written content.
  • To complete this course, you need 180 minutes.
  • You can pause the course anytime and return to where you finished whenever you want.
  • You can follow the course as it flows or at your own pace, rearranging the order of the lessons.
  • At the end of the course, you will take a test containing 8 questions. 
  • You can take the test 2 times, if necessary. 
  • You must score min. 85% of the correct answers to receive the official certificate of completion.

Need more details?

Participants’ Pains

We know that…

IoT principles can be challenging for individuals who are new to the concepts of sensor networks, data communication, and the broader IoT ecosystem, as well as hardware, software, and networking concepts. The architecture and components of an IoT system encompass a wide range of sensors and devices. Students may find it overwhelming to comprehend the diverse types of sensors and their applications within different IoT contexts.

The integration of IoT technologies with other technologies like cloud computing, big data analytics, artificial intelligence, and robotics requires a comprehensive understanding of these domains. Students may face difficulties in comprehending how these technologies work together cohesively.

This lack of exposure can hinder students’ ability to understand the complexities and challenges faced in actual IoT deployments. While examples of practical applications (smart office, warehouse operations, manufacturing, etc.) provide real-world context, students may struggle to connect theoretical concepts to practical implementation without hands-on experience.

Participants’ Gains

So, we developed this course, in which…

This foundational knowledge serves as the basis for comprehending the broader IoT ecosystem. The course provides technical proficiency in the architecture and components of an IoT system. Students learn about different types of sensors and devices used in IoT, developing skills in hardware, software, and networking relevant to IoT technologies.

This hands-on approach not only equips students with the technical expertise to navigate the complexities of IoT but also fosters a mindset for innovation, encouraging them to proactively explore novel applications and address evolving challenges within the ever-changing landscape of Internet of Things technologies.

Students learn to collaborate across domains, an essential skill in the modern workplace. The course aligns with the demands of industries leveraging IoT technologies. Graduates are well-prepared to meet the requirements of a job market that increasingly values professionals with IoT expertise.

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