Artificial Intelligence Algorithms Models and Limitations

This course is part of Ethics in the Age of AI Specialization

Instructor: LearnQuest Network

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22,708 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

530 reviews

Beginner level

No prior experience required

5 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

530 reviews

Beginner level

No prior experience required

5 hours to complete

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Generative AI

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

12 assignments

Taught in English

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This course is part of the Ethics in the Age of AI Specialization

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There are 4 modules in this course

We live in an age increasingly dominated by algorithms. As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations in the real world. Whether it's making loan decisions or re-routing traffic, machine learning models need to accurately reflect our shared values. In this course, we will explore the rise of algorithms, from the most basic to the fully-autonomous, and discuss how to make them more ethically sound.

Welcome to the course! We're going to get started with an overview of the course structure as well as an introductory look at the world of algorithms

What's included

5 videos2 readings3 assignments

5 videos Total 19 minutes

Specialization Introduction 4 minutes
Course Introduction 4 minutes
Sorting: functions and data 4 minutes
You, as a dataset 5 minutes
Weekly Review 1 minute

2 readings Total 25 minutes

Example of simple algorithms, and how to sort 10 minutes
Ethics and AI: What You Need to Know 15 minutes

3 assignments Total 37 minutes

Exam: Getting Started with Algorithms 25 minutes
What's an Algorithm? 6 minutes
Machine learning and everyday life 6 minutes

This week, we are going to dive into predictive modeling the core differences in theory and practice

What's included

3 videos2 readings3 assignments

3 videos Total 12 minutes

Programming the program 5 minutes
Out of the lab: models in production 5 minutes
Weekly Review: AI and Model Outcomes 2 minutes

2 readings Total 24 minutes

Example Predictive Model 20 minutes
Understanding Ethics in AI: How Algorithms Affect Real People 4 minutes

3 assignments Total 41 minutes

Exam: AI and Model Outcomes 25 minutes
Predictive models in theory 10 minutes
Predictive models in reality 6 minutes

This week we are going to focus on machine learning accuracy and training guidelines in the quest for more accurate and ethical models

What's included

4 videos2 readings3 assignments

4 videos Total 17 minutes

Modeling structure : Understanding Model Accuracy and Its Pitfalls 4 minutes
Modeling structure : Building Better Predictive Models Through Design and Domain Knowledge 6 minutes
Mirrors: training models with real data 6 minutes
Weekly Review: Rules for AI 2 minutes

2 readings Total 10 minutes

Beyond Accuracy: precision and recall 4 minutes
Image Recognition as a mirror 6 minutes

3 assignments Total 50 minutes

Exam: Rules for AI 30 minutes
Optimizing models for accuracy 10 minutes
Training data: a reflection of society 10 minutes

In our final week, we're going to ask some big questions about where all this predictive intelligence leads. We will discuss the trajectory of artificial intelligence and the broader implications for society as well