Part-time Instructor in Understanding Ai Data - Montréal, Canada - Universite Concordia
Description
Part-time Instructor in Understanding AI Data:
Last updated:
October 30, 2023, 4:15 p.m.
Course Title:
Understanding AI Data
Course Code:
CEAI 1003
Date posted:
Application deadline:
Format:
Online (30 hours)
Schedule:
Term:
Winter 2024
Term dates:
January 16, March 19, 2024
Day:
Tue
Time of day:18:00 - 21:00
Position description:
Course description and learning outcomes:
Artificial Intelligence (AI) doesn't exist without data.
In 2006, British mathematician Clive Humby said, "Data is the new oil." And data is the fuel that powers AI.
However, having data is not enough, you need good data. But how can you identify quality data in the AI world? This course provides the answer.
The first part of the course will help participants identify good data, spot potential biases, and interpret graphs and other visualizations from data.
This section will help participants assess data requirements for AI projects, differentiate between various storage methods, and identify data sources.
Upon completion of the course, participants will grasp the single most important aspect of AI—data.
To help participants develop data skills for AI, they will be exposed to case studies and other projects that resemble data-related situations AI professionals face daily.
During these exercises, they will examine the different steps of the data lifecycle to help them assess data quality and the requirements for various AI projects.
The assignments will position the participant as the domain expert and client on an AI project and teach them how to work alongside a data scientist.
By the end of this course, the participants will be able to:- Explain the importance of "good" data in AI projects
- Describe the different types of data used in AI projects
- Identify the different techniques used to handle and store data in AI
Qualifications and assets:
-
Education:BS/MS Major in Computer Science or equivalent with a preference given to specialization in AI; or equivalent relevant work experience
-
Industry experience:5+ years relevant work experience as a data scientist or any other similar professions working with data to create AI models
-
Teaching experience: 2+ years of experience delivering training material, workshops, lectures, or classroom teaching
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Experience: Hands on experience working with data and creating machine learning models
How to apply:
Concordia strives to be an inclusive institution that is welcoming of diverse backgrounds and experiences in order to improve learning, advance research, inspire creativity, and drive productivity.
As part of this commitment to providing our students with the dynamic, innovative, and inclusive educational environment of a Next‐Generation University, we require all applicants to articulate in their cover letter how their background, as well as lived and professional experiences and expertise have prepared them to conduct innovative research and to teach in ways that are relevant for a diverse, multicultural contemporary Canadian society.
Adaptive measures:
Information about Concordia Continuing Education
***: Concordia Continuing Education (CCE) is an integral part of Concordia University. It enhances the general mission of the University by delivering a wide range of innovative professional development courses, bootcamps, programs, customized trainings and workshops that provide a unique and challenging experience. CCE is an opportunity hub that specializes in professional, personal and organizational growth. It offers distinctive learning opportunities in response to professional and organizational growth needs as well as strategic development needs. Whether it is to acquire new skills, surpass objectives or simply to discover and explore, we provide learning that works.
Information about Concordia
***: Concordia University is located on unceded Indigenous lands
Tiohtià:
ke/Montreal, on the traditional lands and waters of the Kanien'kehá:ka Nation, is historically known as a gathering place for many First Nations.
We respect the continued connections with the past, present and future in our ongoing relationships with Indigenous and other peoples within the Montreal community.
Building on the skills of our faculty and the strengths of Indigenous, local, and global partnerships, we set our sights further and more broadly than others and align the quality of learning opportunities to larger trends and substantial challenges facing society.
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