APTPUO-Fall 2025-MIA5126 A
200 Lees Block E, Canada
University of Ottawa
Location:
Main CampusSession:
2025 Fall Semester | Trimestre d'automneFaculty:
Faculté de génie / Faculty of EngineeringUnit:
School of Engineering Design and Teaching Innovation_PTCourse Title:
Essential Concepts in Data Science(online)Course Code:
MIA5126Section:
ACourse Description:
This course provides an introduction to the fundamental concepts, principles and methodologies of Data Science. Topics covered will include various concepts spanning the entire data science process, encompassing business understanding, exploratory data analysis, data preprocessing, data warehousing, and predictive and descriptive modeling. Through a blend of theoretical concepts and practical applications, students are expected to develop the hands-on skills and the knowledge necessary to effectively address real-world data science challenges across a range of industries upon completion of the course.Posting limited to:
Professeur à temps-partiel régulier / Regular Part-Time ProfessorDate Posted:
May 22, 2025Applications must be received BEFORE:
June 22, 2025Expected Enrolment:
40Approval date:
May 22, 2025Number of credits:
3Work Hours:
39Course type:
BPosting type:
Régulier / RegularLanguage of instruction:
Anglais | EnglishCompetence in second language:
ActiveCourse Schedule:
Mardi | Tuesday 19:00-22:00 - -Requirements:
- Ph.D. in DTI, Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Demonstrated expertise in Data Science, with a focus on areas such as statistical modeling, machine learning, data visualization, data warehousing, and big data analytics.
- Teaching experience at the graduate and/or undergraduate level, preferably in Data Science or related fields.
- Hands-on experience with industry tools and technologies commonly used in Data Science, such as Python, SQL, TensorFlow, etc.
Preference will be given to candidates with experience in project-based learning or experiential learning approaches in Data Science.
Additional Information and/or Comments:
An acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience. If you are invited to continue the selection process, please notify us of any adaptive measures you might require. Information you send us will be handled respectfully and in complete confidence. Employees are required under provincial law to successfully complete all mandatory legislated training. The list of training may be modified by provincial law.
The hiring process will be governed by the current APTPUO collective agreements; you can click here for the main unit, here for the OLBI unit, or here for the Toronto/Windsor unit to find out more.
The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact vra.affairesprofessorales@uottawa.ca to communicate the accommodation need. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 – Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Big Data Computer Science Data analysis Data Analytics Data visualization Data Warehousing EDA Engineering Machine Learning Mathematics Python Research SQL Statistical modeling Statistics Teaching TensorFlow
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