AN
Nov 5, 2019
Highly recommended for anyone wanting to start learning about AI. Explained in an coherent and intuitive way and will help lay the foundation for a lifelong learning experience and a new career in AI.
HC
May 11, 2019
I now are equipped with right attitude to AI projects, it's limitation and how it will affect our society/jobs. It is very beneficial for me to set up the right mindset to carry on to next AI courses.
By Lavanya T
•May 2, 2020
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By Sanjay K L
•May 1, 2020
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By Dianne P
•Apr 27, 2020
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•Apr 26, 2020
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•Apr 20, 2020
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By Antoine J G D
•Apr 15, 2020
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•Jan 16, 2020
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By Anand R
•Dec 29, 2019
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By Ashish A
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•Dec 5, 2019
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By Yong P
•Oct 14, 2019
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By Jonathan C
•Sep 24, 2019
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•May 23, 2019
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By Punith G
•Aug 16, 2023
The "AI for Everyone" course is a fantastic introduction to the world of artificial intelligence. Andrew Ng's approachable teaching style makes complex concepts easy to grasp, even for non-technical learners. The course strikes a perfect balance between simplicity and depth, providing a comprehensive understanding of AI, machine learning, and deep learning without overwhelming participants.
What sets this course apart is its focus on real-world relevance and ethical considerations. Ng thoughtfully addresses the practical implications and ethical challenges of AI, encouraging responsible and conscientious AI usage. This emphasis equips learners with the knowledge to make informed decisions and contribute positively to their organizations and society.
In summary, "AI for Everyone" offers a well-rounded and accessible entry point into AI, making it an invaluable resource for individuals seeking to understand AI's potential impact on various industries while navigating ethical complexities.
By Dan H
•Mar 5, 2019
The course is a solid high level introduction to the concepts of artificial intelligence, machine learning, data science, and mentions (in passing) some deeper concepts like natural language processing and knowledge graphs. I enjoyed it! My critical feedback revolves around the final week: I appreciated the attention given to ethics in AI, but it seems worth mentioning that efforts to eliminate bias and prejudice are themselves inherently based on judgement calls, and will reflect the value(s) of the person(s) making those judgements. Since this course is aimed at business leaders, I suggest adding some verbiage to the need for an enterprise to articulate those values in a manner that supports their inclusion (at an engineering level) into the techniques, data, and algorithms being developed by those AI teams.