Industrial Internet of Things (IIoT) LEA.D2

This introductory course will enable learners to leverage their technical knowledge across IoT environments. In this course, we will introduce the concept of IoT. We will explore the ‘things’ that make up the Internet of Things, including how those components are connected together, how they communicate, and how they add value to the data generated. We will also examine the IoT data analysis, security, privacy and optimization of the IIoT scenarios. The students will briefly review the most common IoT use cases and the interaction between the IIoT devices and digital transformation of industries.

This course will introduce the students to the basics of Python programming. The goal of the course is to introduce students to basics of Python programming using hands-on experience. Students will learn how to install Python and use different IDEs (integrated development environments) such as PyCharm for writing and debugging programs. The students will also learn to use Python and Jupyter platforms on Raspberry Pi. They will receive the tools necessary to create basic programs and resolve simple problems. Students will apply Python built-in data structures such as lists, dictionaries, and tuples to perform data analysis. Functions, classes and basic libraries of Python will also be covered in this course. After completing this course, students will be ready to take more advanced programming courses in Python.

This course provides the students with a full overview of wired computer networking as it relates to IoT. They will have an opportunity to design, implement, and support a LAN network in an IoT setting. By the end of the course, students will be able to build simple LANs, perform configurations on routers and switches, and implement IP addressing schemes using both equipment and emulators.

In the course, students will be introduced to the components and specifics of OT networks commonly found in a manufacturing environment. Students will have the opportunity to set up and establish communication, as well as retrieve and log data from an industrial control unit.

This course will introduce students to the technical approach used for analyzing and designing an application by applying object-oriented programming. Students will develop the ability to select and use programming languages, desktop integrated development environments (IDE) Software Development Kits (SDKs) and application programming interfaces (APIs) for an IIoT environment. Students will also learn to program IoT devices using Arduino and Raspberry Pi platforms with the purpose to control the physical world (various sensors and actuators like LED modules, motion sensors, DHT22 Temperature and Humidity Sensors, Digital push buttons). The Raspberry Pi is typically installed with a Linux-based operating system, so the basics of Linux and its use will be introduced to the students as well as some of its main features including navigating the file system and managing processes. Students will be exposed to the text-based user interface through the shell and have an overview of the graphic user interface that is the default with the Raspian Linux distribution.

This course provides the students with an opportunity to design and implement wireless technology, test wireless communications, optimize wireless transmission and support a wireless network in an IIoT setting in compliance with regulations.

This course will provide students with the necessary skills to securely extract, transform and load IIoT Data and DataSets to IIoT oriented Databases in conformity with Industrial Data classification
models and Security best practices. Students will explore relational and non-relational databases as well as how to use local or cloud-based IIoT Data ETL (Extract, Transfer and Load) solutions and platforms.

In this class, students will learn how to integrate external devices (sensors, motors, GPS, orientation, LCD screens, etc.) with the IIoT system to get an IoT device to interact with the real world. Students will use embedded systems, build hardware systems and connect devices to control the environment. They will also learn methods to secure the IoT devices. Simple implementation of Industry 4.0 processes such as digital twin will also be covered in this course.

This course will provide students with the necessary skills to securely extract, transform and load IIoT data and datasets to IIoT-oriented Databases in conformity with Industrial Data classification models and Security best practices. Students will explore relational and non-relational databases as well as how to use local or cloud-based IIoT data ETL (extract, transfer, and load) solutions and platforms.

This course will provide students with the skills required to use cloud computing in various modes (SaaS, PaaS, etc.) in an IIoT environment. This course describes how to connect, set up and use cloud resources, e.g. EC2 (Elastic Compute Cloud), for IoT scenarios to enhance the performance of IoT solutions and to better analyze the IoT data. Different services such as telemetry and its relation to the IoT services will be covered in this course. Students will learn to locate IoT services in the cloud and acquire knowledge of the basic steps for setting it up. Moreover, in this course, students will learn to develop a simple IoT application to send and receive data to/from the cloud and to structure the IoT app with a variety of different cloud services. Briefly, this course will help students to integrate the embedded systems into the cloud.

This course provides students with an opportunity to transform IoT data to enhance the performance of industrial operations. This course will expose students to the data analytics practices executed in the industrial IoT. They will move from the stages of problem identification to planning and applying a variety of data-driven solutions. They will learn to work with data and create an environment in which analytics can flourish. Students will learn how to manipulate and analyze IoT data and explore different use cases in IoT. For instance, they will learn to retrieve data from databases (static and real-time) using queries. The basics of machine learning for IoT data analysis will be covered. Students will also learn how to use common visualization tools. They will discover how data visualization can be used to better present the IoT data. They will explore the fundamental concepts of data visualization common interfaces and dashboards such as Power BI and Kibana, identifying and applying the various tools dashboards offer. By the end of the course, students will be able to prepare and import data into tables and explain the relationship between data analytics and data visualization.

Students will learn the steps involved in automating tasks based on predetermined conditions. They will also learn about intelligent process automation (IPA) and common event-driven task automation approaches with a focus on applications in a variety of IIoT systems.

In the final capstone project completed in small groups of 2-3 students, students will apply the skills they have learned, by designing, building, controlling and testing in a controlled experimentation environment (IIoT testbed), as well as by collecting, storing, analyzing and visualizing the IIoT data. There will be an emphasis on ensuring that the final project is suitable as a showcase to future employers.

An internship experience provides the student with an opportunity to explore career interests while putting in practice knowledge and skills acquired in the program in a work setting. This course with help students to identify the practical issues of IIoT and provide a better platform to work with technological solutions. The internship provides hands-on training to effectively use and customize device interactions, networks, data management and analysis. Students will understand the essentiality of inter-connected devices and the benefits of task/process automation in industry. Students will get an overview of IoT application deployment in industry. The experience also helps students gain a clearer sense of future learning direction to adapt their knowledge and skills and provides an opportunity to build professional networks.

Applicants must have a Secondary V diploma or equivalent or have acquired knowledge and skills deemed sufficient by the College for potential success in the program.  More specifically, they must show proof of:

• A Diploma of High School Studies OR
• A College Diploma or a University Degree OR
• A partial high school program, coupled with a recommendation from a current or former employer that you would benefit from pursuing your education at the post-secondary level.

And

The applicant must meet one of the following requirements:

• Have interrupted studying full-time for at least two consecutive terms or one school year OR
• Be covered under an agreement between the college and an employer, or benefiting from a government program OR
• Have completed at least one year of post-secondary studies over a period of one year or more OR
• Hold a Diploma of Vocational Studies (DVS/DEP)

In addition to the ministerial admission requirements, the following requirements apply specifically to this program:

• Demonstrated schooling and/or work experience involving IT or OT
• Mathematics (either Secondary IV, Technical and Scientific option; or Secondary IV, Science option; or Secondary V, Cultural, Social and Technical option, or equivalent)

Prospective candidates will be asked to submit a curriculum vitae (CV) and will be tested for their basic networking knowledge prior to being admitted.

Note: Entrance exams may be administered.

To take part in the instructor-led virtual classes, you will need a personal computer with these minimal requirements:

• PC compatible with Windows 10
• Intel® Core™ i5 Processor
• 8 GB of RAM
• Hard drive of 500 GB
• Network cable or adapter
• Webcam with microphone
• High-speed internet (minimum 2 megabits)

The first step in the application process is to sign up for an information session. You can do that by clicking the “Attend an information session” button and completing the form that follows. During the information session, which might be in a group or held individually, the pedagogical counsellor for the program will explain in detail the admission requirements, how the program works, and the application process.  

After attending an information session, you will receive an email with detailed application instructions and the link you will use to access Omnivox, Champlain College Saint Lambert’s online application platform. Submit your application for admission via Omnivox by following the instructions provided in the email.

You will be asked during the online application process to upload the following required documents.

Proof of residency documents, based on your status:

• Québec birth certificate OR
• Canadian birth certificate AND a valid Quebec RAMQ card OR
• Canadian citizenship card/certificate AND a valid Quebec RAMQ Card OR
• Permanent resident card AND a CSQ (Certificate of Selection of Quebec) or a valid Quebec RAMQ card in the event that you did not receive a CSQ

Schooling documents:

• Secondary school, college, or university certificates AND
• Transcripts for the highest level of schooling completed AND
• Any other certifications relevant to the program.

Up-to-date curriculum vitae (CV)

Once you have submitted all required documents, no further action is needed from you. Our admissions’ team will be reviewing your application, and we will contact you by email as soon as the admission verdict is available. We will also contact you by email should our admissions team require additional documentation or information before an admission decision can be made.

Should you have any questions after submitting your documents and completing your application, please do not hesitate to contact the Continuing Education Department/your program’s dedicated administrative support staff member.

AEC/IIOT program is a great opportunity to get practical knowledge in microcontroller, networking, programming, database, automation and PLCs. This AEC program gave me the chance to get a deep understanding of industry 4.0 and the whole ecosystem of players that turns around it. The program staff were very cooperative and supported us a lot morally and with all the materials that we needed to achieve our courses/projects and labs. I strongly recommend this program for everyone who has the capability to take this challenge and dive into a wonderful education journey.