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Introduction to Designing Artificial Intelligence (AI) Applications

Introduction to Designing Artificial Intelligence (AI) Applications

Welcome to the official OCAD University Continuing Studies Introduction to Designing Artificial Intelligence (AI) Applications course.

In this hands-on course, students are introduced to Artificial Intelligence (AI) research and learn to design and build practical AI applications. The fundamental concepts covered by the course include logic programming, knowledge representation, and machine learning, applied to areas such as natural language processing, computer vision, and procedural generation. This course does not require computer programming expertise. Students will be introduced to languages including Python, HTML/CSS, JavaScript, which underpin development frameworks such as NLTK, OpenCV, and Tensorflow. The course will also explore ethical issues, bias, and other concerns surrounding AI.

Important Links, Tools, and Resources

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References

Week 1

Course Concept

Secondary Readings

Technical Exercise #1: Playing a game of tic-tac-toe with simple AI

Objectives: Review fundamental concepts in web development and build an AI-powered game of tic-tac-toe using HTML, CSS, and JavaScript.

Guide

Troubleshooting Resources

Week 2

Course Concept

Secondary Readings

Technical Exercise #2: Chatting with machines

Objectives: Connect to a dedicated server using secure shell to create a Python script that fuels a simple chatbot application.

Guide

Troubleshooting Resources

Week 3

Course Concept

Secondary Readings

Technical Exercise #3: Tracking position and emotion with computer vision

Objectives: Use available web services and libraries to create an application that can process video clips on-the-fly for object tracking and sentimental analysis.

Guide

Troubleshooting Resources

Week 4

Course Concept

Secondary Readings

Technical Exercise #4: Predicting and visualizing temperature with basic regression

Objectives: Train a simple regression model based on historical temperature data and create an interactive visualization with prediction capabilities.

Guide

Troubleshooting Resources

Week 5

Course Concept

Secondary Readings

Technical Exercise #5: Training an image classification model with Google Colab

Objectives: Create a web-based project via Python and Google Colab that can train an AI model that can recognize and classify a user-provided image.

Guide

Troubleshooting Resources

Week 6

Course Concept

Secondary Readings

Technical Exercise #6: Composing text with a generative model using Hugging Face Inference

Objectives: Use the GPT-2 model provided by Hugging Face to create an AI-assisted writing application.

Guide

Troubleshooting Resources

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