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Avis et commentaires pour d'étudiants pour Machine Learning Foundations for Product Managers par Université Duke

4.6
étoiles
53 évaluations
13 avis

À propos du cours

In this first course of the AI Product Management Specialization offered by Duke University's Pratt School of Engineering, you will build a foundational understanding of what machine learning is, how it works and when and why it is applied. To successfully manage an AI team or product and work collaboratively with data scientists, software engineers, and customers you need to understand the basics of machine learning technology. This course provides a non-coding introduction to machine learning, with focus on the process of developing models, ML model evaluation and interpretation, and the intuition behind common ML and deep learning algorithms. The course will conclude with a hands-on project in which you will have a chance to train and optimize a machine learning model on a simple real-world problem. At the conclusion of this course, you should be able to: 1) Explain how machine learning works and the types of machine learning 2) Describe the challenges of modeling and strategies to overcome them 3) Identify the primary algorithms used for common ML tasks and their use cases 4) Explain deep learning and its strengths and challenges relative to other forms of machine learning 5) Implement best practices in evaluating and interpreting ML models...

Meilleurs avis

WM

9 janv. 2022

A very good introduction to ML Jon Reifschneider explains very well the topics with real-world experience\n\n-based on this professional experience.

SV

29 nov. 2021

Really a good introduction to Machine Learning, it helps you to boost your interest on the field and create a product from zero!

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1 - 14 sur 14 Avis pour Machine Learning Foundations for Product Managers

par Jun W T

18 déc. 2021

A very clear introduction to the 'types' of Artificial Intelligence and other necessary concepts required in dealing with AI.

par Wolf Z

9 mai 2022

It is a good introduction into machine learning concepts that finds the right balance between required depth and and time efficient knowledge transfer.

As the title indicates, it is a good introduction on management level and is not suited to train data scientists.

A negative point: The instructor speaks incredibly slow and is rather unenthusiastic. However putting the speed on 1.5-2 times fixes this.

par Justine R

17 mars 2022

I love the way the course is structured. Jon Reifschneider allows you to view and download the slides before diving into the videos. He explains the content thoroughly and supports his explainations with charts and diagrams which I personally find very helpful. I'm so glad I took the time to complete this course.

par Wilberto M

10 janv. 2022

A very good introduction to ML Jon Reifschneider explains very well the topics with real-world experience

-based on this professional experience.

par Sofía P V

30 nov. 2021

Really a good introduction to Machine Learning, it helps you to boost your interest on the field and create a product from zero!

par John P

25 avr. 2022

G​reat course. Clear, informative, and cited numerous real-world examples to help learners grasp seemingly abstract concepts.

par Nancy

18 janv. 2022

Very good courses that clearly and precisely covered the foundation concepts for machine leaning!

par Pankaj

3 mars 2022

Great content, Knowledgeable Instructor, well explained.

Course has been helpful , Thanks!

par B S P

7 mars 2022

Very practical to apply

par Ali A

26 mars 2022

Very useful, indeed.

par Gaytri B

24 janv. 2022

Good KT

par Andrei K

16 mars 2022

The training provides a good overview of ML concepts. At the same time pre-project data quality review and initial data analysis could have a more extensive coverage from my point of view

par Ramanan K

21 févr. 2022

A lot of good content, but not a great presentation/organization making it hard to be engaging. Especially for working professionals, the presenter's energy level does not motivate them to keep going. You are better off doing a proper AI/ML course instead.

par Amr

28 janv. 2022

t​he instructor is reading from a slide,it is not a well prepared course