Instructor (FastLane) Data Readiness & Model Deployment (DaRMoD) - Canada - Vector Institute

Description

Instructor (FastLane) Data Readiness & Model Deployment (DaRMoD)

Compensation: $1,500 to $2,250 Fixed Price

Experience Level

Degree Required

Masters Degree

Education

Company Size

Scaling

Application Type

Vector Quick Apply

Please note, this ad is for one to three Instructor positions within the Data Readiness and Model Deployment program in summer 2024. Candidates may apply to teach one or all three of the modules indicated below. The positions(s) will not be formally contracted until the enrollment is finalized and the program is confirmed as running. Confirmation is expected on or before May 7, 2024. The decision on whether to proceed with the program is dependent on the number of participant registrations (i.e., a minimum number of participants must be registered).

We are advertising for these positions in advance of May 7, 2024, so we are able to move quickly on staffing and developing the program content once confirmed. Any work done prior to the program confirmation will be remunerated accordingly, even if the program is cancelled.

Please note that the Vector Institute will conduct an evaluation of workshop participants to both evaluate the performance of the instructor(s), as well as consider program improvements for future iterations.

The instructor(s) for this program may be asked to provide their service to other programs of similar type, where offered by the Vector Institute in the same fiscal year, provided they receive positive feedback from the program participants and receive successful evaluation from Vector's Technical Education Specialists.

STATEMENT OF WORK: FastLane - Data Readiness & Model Deployment - Instructor

These Instructor positions are for the development and delivery of the Data Readiness & Model Deployment program. This program is being held for employees of companies within the Vector Institute's FastLane ecosystem. It will equip FastLane SMEs with the skills and knowledge necessary to accelerate the implementation of machine learning on a predefined use case within their organizations. The program spans the life cycle of a typical machine learning project from data preparation to model deployment.

The program consists of three modules: 1) Data Readiness, 2) Model Development, and 3) Model Deployment. The instructor(s) will be responsible for developing and delivering lecture content and performing hands-on demos for the assigned module(s). In your application, please indicate which module(s) you are applying for . The teaching commitment will vary depending on the module(s) for which you apply. Each lecture will be 2 hours in duration.

Fees: This is a paid position. The flat fee for development and delivery of content is $2250 (CAD) for modules 1 and 3, and $1500 for module 2.

Tentative Program Dates

Orientation Tuesday, May 14, 300 PM - 4:30 PM EST

Module 1: Data Readiness – 3 Weeks

Tutorials : Wednesdays (May 29, June 5 & 12) 3:00 PM - 5:00 PM EST

Tutorials : Wednesdays, June 19 & 26) 3:00 PM - 5:00 PM EST

Lectures: Tuesdays (July 9, 16, 23) 3:00 AM - 5:00 PM EST

Tutorials: Wednesdays (July 10, 17, 24) 3:00 AM - 5:00 PM EST

Program Times and Location

Lectures and tutorials: 3:00 am to 5:00 pm EST

Virtually via Zoom

The capstone presentations will take place 2:00 PM - 5:00 PM in-person or in a hybrid format.

Instructor content creation and delivery include:

Preparation Phase

• Prepare content and ensure that all course materials (e.g. lesson objectives, slides, discussion prompts, assignment activities) are prepared in advance of the lecture time and are available in the Vector Learning Management System (LMS), currently D2L
• Attend scheduled program team meetings (including TA onboarding): planning and debrief (typically weekly)
• Participate in a Vector training workshop/briefing with Vector staff
• Coordinate with TES and TAs on assignment activity expectations

Execution phase

• Teach all lectures in the program on time, to a high standard of service, and in an environment free of distractions
• Assist with use case discussions throughout the program
• Answer questions from participants when appropriate, during demo/tutorial activities and otherwise
• Manage participants' learning progress: work closely with Technical Advisors (TAs) and the Vector Professional Development (PD) staff to ensure the program is delivered successfully and participants' issues are dealt with in a professional manner. The Instructor and TAs will interact directly with participants on the content itself. Vector staff will grant extensions and notices of completion, and all other issues considered "customer service".

The instructor, in communication with Vector Professional Development staff, will develop and deliver content in line with the following:

Introduction

The rapid evolution of AI has significantly transformed business operations for companies. SMEs leveraging machine learning algorithms gain a competitive edge in their respective markets, can make better business decisions, and work more efficiently. Many SMEs may not have the expertise or resources to integrate machine learning into their business practices. To address these challenges, the Vector Institute has developed a new training program designed to equip SMEs with the essential skills and knowledge necessary to accelerate the implementation of machine learning for a pre-defined use case within their organizations.

Program sessions will be delivered in an interactive lecture/discussion format, with practical examples and case studies used to spark reflection and discussion. Sessions are designed to leverage learners' prior experience, stimulate conversation, and move each company towards a Proof of Concept (PoC) by the end of the program.

Program Overview

The program is designed to cover the entire lifecycle of a machine learning project. Each module will be conducted over a period of three weeks and SMEs will be assigned a Technical Advisor (TA) to provide guidance and support throughout the program. TAs are experienced machine learning practitioners who will provide feedback on the SMEs' work and help address any roadblocks that may arise during the program.

1. Data Readiness

Many companies face the challenge of having sparse or low-quality data or may inadvertently work with incorrect data transformations, which can all affect the accuracy of machine learning models. By the end of the module, learners will be able to:

• Identify relevant data sources to successfully train their machine learning models
• Apply data cleaning and preprocessing techniques for their specific data types
• Create data visualizations to identify relevant patterns and relationships in their data
• Identify strategies to mitigate bias and implement data governance practices within their organizations

By the end of this module, learners will be able to:

• Demonstrate the ability to select appropriate machine learning algorithm(s) for their use cases
• Evaluate and optimize model performance
• Develop a self-guided approach to model development that best aligns with their projects by referencing examples implemented by Vector Institute
• Understand effective principles and practices for building trustworthy AI systems

By the end of this module, learners will be able to:

• Develop a strategy for deploying and integrating their machine learning models into their business practices
• Apply effective monitoring and maintenance techniques so their deployed models will maintain a high-performance level

4. Capstone

At the end of the program, SMEs will have four weeks of dedicated time to focus on their use case, in consultation with their TA. The program culminates in a 10-minute capstone presentation where companies will have an opportunity to showcase their work and receive feedback from their peers and members of the Vector community.

Pedagogical Approach

Program sessions will be delivered in an interactive lecture/discussion format, with practical examples and case studies used to spark reflection and discussion. Sessions are designed to leverage learners' prior experience, stimulate conversation, and move each company towards a viable Proof of Concept (PoC) by the end of the program. All sessions will be delivered online.

Level of Training and Learner Prerequisites

The program will expose learners to several open-source Python packages. Coding concepts will be delivered at an intermediate level and each company should have at least one technical participant who is familiar with the following packages:

• numpy and pandas for manipulating arrays and dataframes
• matplotlib or similar visualization or exploratory data analysis packages
• scikit-learn, TensorFlow or PyTorch: popular machine learning frameworks

Compensation

Module 1 - $2,250

Module 2 - $1,500

Module 3 - $2,250

Application

To apply, please submit your CV and cover letter to . In your application, please indicate which module(s) you are applying for .

Applications will be reviewed on a rolling basis until filled.

Vector Institute (Internal Opportunities Only)

Vector Institute (Internal Opportunities Only)