Introduction to Applied Machine Learning

This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application.After completing all four courses, you will have gone through the entire process of building a machine learning project. You will be able to clearly define a machine learning problem, identify appropriate data, train a classification algorithm, improve your results,

( 28 Reviews )

Created by: Anna Koop

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Overall Score : 96 / 100

Course Description

This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project.By the end of the course, you will be able to clearly define a machine learning problem using two approaches. You will learn to survey available data resources and identify potential ML applications. You will learn to take a business need and turn it into a machine learning application. You will prepare data for effective machine learning applications.This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute.

Time: 9h

Instructor Details

Anna Koop

4.8 Rating
28 Reviews

Anna is Senior Scientific Advisor at the Alberta Machine Intelligence Institute (Amii), working to nurture productive relationships between industry and academia. Anna, whose research mainly focused on reinforcement learning, received her Master's in Computing Science under the supervision of Dr. Richard Sutton, one of the field's pioneers, and she is currently a PhD candidate working to develop algorithms for real-time learning in dynamic environments. Passionate about making science accessible for all, Anna has developed and taught a wide range of computing science classes through the University of Alberta.

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4.8

28 total reviews

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By Vern E on 22-Sep-19

I have taken a great deal of knowledge in this course and have applied it to what I have seen in the ML and AI world. This was a great introduction!

By Abdullah A on 12-Sep-19

very comprehensive course on applied machine learning. the most interesting information in this course is business needs for ML and what it's requirement to have a good QuAM.

By Fezile M on 12-Nov-19

Great Introductory course, it was delivered very good. I picked up a lot of different definitions which were simplified. Very Good!

By MALIKI M on 29-Oct-19

I have really got benefit from this course as a beginner to ML, it gives me the best understanding of ML. I m looking forward to getting into it more efficiently with more practices.

By najla on 24-Oct-19

very solid and the instructor is really good

By Omar H on 25-Oct-19

This course was very helpful and fruitful. It is a good entry for machine learning and I really recommend it. Thanks, Anna, Thanks, amii

By Olof B on 8-Nov-19

Good introduction to ML

By Kirkpng on 24-Sep-19

refresh course and I learn something new

By Nancy A A on 25-Sep-19

thanks for gain this opportunity to learn

By Chandrashekar B S on 7-Oct-19

I'm enjoying this process of studying!

By Jean M G on 6-Oct-19

I liked very much this course on Machine Learning. The theoretical background is really fantastic on how to build your QuAM and also the Machine learning Process Lifecycle. Additional things are related to what Machine Learning is and the differences with other disciplines such as Artificial Intelligence and Data Science.

By Vivek R on 3-Oct-19