Arizona State University
Introduction to Machine Learning with Python
Arizona State University

Introduction to Machine Learning with Python

Adwith Malpe

Instructor: Adwith Malpe

1,581 already enrolled

Included withCoursera Plus

Gain insight into a topic and learn the fundamentals.
3.4

(14 reviews)

Beginner level

Recommended experience

12 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
3.4

(14 reviews)

Beginner level

Recommended experience

12 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Students will be able to apply advanced python coding skills in the real world by creating machine learning models.

Details to know

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Assessments

9 assignments

Taught in English

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This course is part of the Python: A Guided Journey from Introduction to Application Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course

This course will give you an introduction to machine learning with the Python programming language. You will learn about supervised learning, unsupervised learning, deep learning, image processing, and generative adversarial networks. You will implement machine learning models using Python and will learn about the many applications of machine learning used in industry today. You will also learn about and use different machine learning algorithms to create your models. You do not need a programming or computer science background to learn the material in this course. This course is open to anyone who is interested in learning how to code and write programs in Python. We are very excited that you will be learning with us and hope you enjoy the course!

What's included

1 video1 reading

In this module you will learn about machine learning and how each branch of machine learning works in Python.

What's included

6 videos12 readings3 assignments

In this module, you will learn about two other supervised machine learning models: k-nearest neighbors (kNN) and support vector machines (SVM). You will learn under which conditions you’d use these two models. You will also learn about unsupervised machine learning models and how they work.

What's included

4 videos11 readings3 assignments1 discussion prompt

In this module, you will gain an overview of advanced machine learning topics, including deep learning, image processing, and generative adversarial networks (GANs).

What's included

4 videos6 readings3 assignments1 peer review1 discussion prompt

Instructor

Instructor ratings
3.4 (5 ratings)
Adwith Malpe
Arizona State University
4 Courses4,860 learners

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