Introduction to AI

Introduction to AI

Instructor: Arm Education

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1,634 already enrolled

7 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

7 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

31 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

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There are 7 modules in this course

Discover the fundamental concepts behind artificial intelligence (AI) and machine learning in this introductory course. Explore the various types of AI, examine ethical considerations, and delve into the key machine learning models that power modern AI systems. Whether your goal is to work directly with AI, strengthen your software development skills, or enhance your data science expertise, this course provides an essential foundation for success in the field.

What's included

1 video2 readings

What's included

6 videos12 readings5 assignments

6 videosTotal 17 minutes

Welcome to Module 11 minute
1.1 History of AI4 minutes
1.2 Fitting It Together: AI, ML, and DS4 minutes
1.3 Current Applications of AI2 minutes
1.4 Explore Some AI2 minutes
Video2 minutes

12 readingsTotal 60 minutes

1.1 History of AI5 minutes
Critical Thinking5 minutes
Action Point5 minutes
1.2 Fitting It Together: AI, ML, and DS5 minutes
Critical Thinking5 minutes
Action Point5 minutes
1.3 Current Applications of AI5 minutes
Critical Thinking5 minutes
Action Point5 minutes
1.4 Explore Some AI5 minutes
Action Point5 minutes
Stretch Tasks5 minutes

5 assignmentsTotal 25 minutes

Graded Questions5 minutes
1.1 History of AI5 minutes
1.2 Fitting It Together: AI, ML, and DS5 minutes
1.3 Current Applications of AI5 minutes
1.4 Explore Some AI5 minutes

What's included

6 videos11 readings5 assignments

6 videosTotal 22 minutes

Welcome to Module 22 minutes
2.1 Approaches to Machine Learning4 minutes
2.2 Key Algorithms and Models5 minutes
2.3 Classifiers3 minutes
2.4 Linear Regression4 minutes
Video2 minutes

11 readingsTotal 80 minutes

2.1 Approaches to Machine Learning5 minutes
Critical Thinking5 minutes
Action Point5 minutes
2.2 Key Algorithms and Models5 minutes
Action Point5 minutes
2.3 Classifiers5 minutes
Critical Thinking5 minutes
Action Point5 minutes
2.4 Linear Regression30 minutes
Action Point5 minutes
Stretch Tasks5 minutes

5 assignmentsTotal 25 minutes

Graded Questions5 minutes
2.1 Approaches to Machine Learning5 minutes
2.2 Key Algorithms and Models5 minutes
2.3 Classifiers5 minutes
2.4 Linear Regression5 minutes

What's included

6 videos10 readings5 assignments

6 videosTotal 19 minutes

Welcome to Module 32 minutes
3.1 Introduction to Neural Networks4 minutes
3.2 Neural Network Layers3 minutes
3.3 Introducing the MNIST Database2 minutes
3.4 Training your Neural Network3 minutes
Video1 minute

10 readingsTotal 50 minutes

3.1 Introduction to Neural Networks5 minutes
Critical Thinking5 minutes
Action Point5 minutes
3.2 Neural Network Layers5 minutes
Action Point5 minutes
3.3 Introducing the MNIST Database5 minutes
Critical Thinking5 minutes
Action Point5 minutes
3.4 Training your Neural Network5 minutes
Critical Thinking5 minutes

5 assignmentsTotal 25 minutes

Graded Questions5 minutes
3.1 Introduction to Neural Networks5 minutes
3.2 Neural Network Layers5 minutes
3.3 Introducing the MNIST Database5 minutes
3.4 Training your Neural Network5 minutes

What's included

7 videos12 readings6 assignments

7 videosTotal 21 minutes

Welcome to Module 42 minutes
4.1 Training, Validation and Test Data3 minutes
4.2 Overfitting and Underfitting3 minutes
4.3 Loss Functions and Optimizers3 minutes
4.4 More use of MNIST3 minutes
4.5 Power Consumption, Performance, and Sustainability3 minutes
Video2 minutes

12 readingsTotal 85 minutes

4.1 Training, Validation and Test Data5 minutes
Critical Thinking5 minutes
Action Point5 minutes
Action Point5 minutes
4.3 Loss Functions and Optimizers5 minutes
Critical Thinking5 minutes
4.4 More use of MNIST5 minutes
Action Point30 minutes
4.5 Power Consumption, Performance, and Sustainability5 minutes
Critical Thinking5 minutes
Action Point5 minutes
Stretch Tasks5 minutes

6 assignmentsTotal 35 minutes

Graded Questions5 minutes
4.1 Training, Validation and Test Data5 minutes
4.2 Overfitting and Underfitting5 minutes
4.3 Loss Functions and Optimizers5 minutes
4.4 More use of MNIST5 minutes
4.5 Power Consumption, Performance, and Sustainability10 minutes

What's included

6 videos11 readings5 assignments

6 videosTotal 18 minutes

Welcome to Module 52 minutes
5.1 Introduction to CNNs and RNNs4 minutes
5.2 Introduction to the PyTorch Framework3 minutes
5.3 Linear Number Relationships2 minutes
5.4 Text Recognition3 minutes
Video1 minute

11 readingsTotal 55 minutes

5.1 Introduction to CNNs and RNNs5 minutes
Critical Thinking5 minutes
Action Point5 minutes
5.2 Introduction to the PyTorch Framework5 minutes
Action Point5 minutes
5.3 Linear Number Relationships5 minutes
Critical Thinking5 minutes
Action Point5 minutes
5.4 Text Recognition5 minutes
Action Point5 minutes
Stretch Tasks5 minutes

5 assignmentsTotal 45 minutes

Graded Questions5 minutes
5.1 Introduction to CNNs and RNNs10 minutes
5.2 Introduction to the PyTorch Framework10 minutes
5.3 Linear Number Relationships10 minutes
5.4 Text Recognition10 minutes

What's included

6 videos12 readings5 assignments1 plugin

6 videosTotal 19 minutes

Welcome to Module 62 minutes
6.1 Ethics and AI4 minutes
6.2 AI in the Cloud3 minutes
6.3 AI on the Edge3 minutes
6.4 Capstone Project3 minutes
Video2 minutes

12 readingsTotal 65 minutes

6.1 Ethics and AI5 minutes
Critical Thinking5 minutes
Action Point5 minutes
6.2 AI in the Cloud5 minutes
Critical Thinking5 minutes
6.3 AI on the Edge5 minutes
Critical Thinking5 minutes
Action Point5 minutes
6.4 Capstone Project5 minutes
Action Point5 minutes
Next Steps5 minutes
Share your experience10 minutes

5 assignmentsTotal 45 minutes

Graded Questions5 minutes
6.1 Ethics and AI10 minutes
6.2 AI in the Cloud10 minutes
6.3 AI on the Edge10 minutes
6.4 Capstone Project10 minutes

1 pluginTotal 5 minutes

Course Survey5 minutes

Instructor

Arm Education

Arm

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Arm

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Introduction to AI

Skills you'll gain

Details to know

See how employees at top companies are mastering in-demand skills

There are 7 modules in this course

Welcome to the Course

What's included

Module 1: Introduction to AI

What's included

Module 2: AI and Machine Learning

What's included

Module 3: What's in the Black Box? Deep Learning and Neural Networks

What's included

Module 4: Training and Evaluating Models

What's included

Module 5: Advanced Topics in AI

What's included

Module 6: Ethics, Challenges, and the Future of AI

What's included

Instructor

Offered by

Why people choose Coursera for their career

Explore more from Computer Science

Introduction to Artificial Intelligence

How to Get Into AI

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