Job title: Hourly paid teacher - IIoT program
Course title: Data Analysis, Visualization, and Task Automation
Work location: Champlain College Saint-Lambert, QC
Sector: Continuing Education
Discipline: Electronic Data Processing Techniques
Course number: 420-960-LA
Course type: Theory
Number of hours: 90 hours
Salary range: $99.09 - $138.27 per hour (according to years of schooling and experience)
Duration of contract: September 10, 2026 to November 14, 2026
Posting period: 2026-08-21 to 2026-08-28 23:59
JOB DESCRIPTION
The Continuing Education Department of Champlain College Saint-Lambert requires the services of an HOURLY INSTRUCTOR to teach the course DATA ANALYSIS, VISUALIZATION, AND TASK AUTOMATION (420-960-LA).
Students in this course will learn how 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. They 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, 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.
REQUIRED QUALIFICATIONS
Must have thorough knowledge of big data management, database, SQL, and data visualization in an IoT/IIoT context.
Must have knowledge implementing task flow automation, managing IoT systems and machine to machine communication.
Must have a master's degree in computer science or related discipline with a minimum of 2 years experience in IoT, or a bachelor's degree in computer science or related discipline with a minimum of 4 years of experience in the field.
Experience teaching an adult clientele is an asset.
Proficiency in English is required.
COURSE SCHEDULE:
Tuesdays
6:30 pm to 9:30 pm
(EXCEPT: September 15)
Thursdays
6:30 pm to 9:30 pm
(All)
Saturdays
9:00 am to 12:00 pm (noon)
(All)
Saturdays
1:00 pm to 4:00 pm
(Sept. 12 & 19 ONLY)
This course will be delivered in a hybrid mode: Saturday classes will be delivered onsite from the College, while the evening classes will be taught online.
Experience with online course delivery platforms such as Zoom, Moodle, LEA and Microsoft Teams is an asset.
The format of delivery may change based on the needs of the course.
COMMENTS
This course is taught in English. The selected incumbent will be required to work in English.
We thank all applicants for their interest, however only those selected for an interview will be contacted.
Please note that a cover letter and CV are required with your application.
Want to learn more about working at Champlain College? Visit the Careers section of our website: Join Our Team - Champlain College - Saint Lambert
Champlain College Saint-Lambert, a constituent college of Champlain Regional College, hires on the basis of merit and is strongly committed to equity, diversity and inclusiveness within its community. We welcome applications from racialized persons/visible minorities, women, Indigenous persons, persons with disabilities, ethnic minorities, and persons of minority sexual orientations and gender identities, as well as from all qualified candidates with the skills and knowledge to productively engage with diverse communities.