Part-time Instructor in Understanding Ai Data

3 weeks ago

Montréal, Canada Universite Concordia Full time

**Part-time Instructor in Understanding AI Data**:
Last updated: February 20, 2023, 4:11 p.m.

**Course Title**:Understanding AI Data
**Course Code**:CEAI 1003
**Date posted**: 2023-02-20
**Application deadline**:2023-03-12
**Format**:Online (30 hours)

**Schedule**:
**Term**:Spring 2023
**Term dates**:April 4, 2023 - June 6, 2023
**Day**:Tuesday

**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. The second part of the course will focus on the practical aspects of data for AI projects. 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
- Assess what is required to carry out an AI project

**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
- **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. We define diversity broadly to include both ethnic and socio‐cultural background and diversity of perspectives, ideologies and traditions.

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**:
**Information about Concordia**:
**Information about Montreal**:
**Territorial Acknowledgement**:

- Concordia University is located on unceded Indigenous lands. The Kanien’kehá:ka Nation is recognized as the custodians of the lands and waters on which we gather today. Tiohtià:ke/Montreal is historically known as a gathering place for many First Nations. Today, it is home to a diverse population of Indigenous and other peoples. We respect the continued connections with the past, present and future in our ongoing relationships with Indigenous and other peoples within the Montreal community._

**Employment Equity**:

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