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.
KB
This is a course that gives a much-needed overview that is rarely mentioned in other resources. Ana is a very cool teacher...
CW
The lectures are very clear and easy to follow. More importantly, it gives me a big picture of how Machine Learning can be applied to the real-world business.
LM
An excellent introduction to the fascinating world of machine learning and its endless applications. Loved the emphasis on the evaluation of the business prospect of ML as well.
FM
Great Introductory course, it was delivered very good. I picked up a lot of different definitions which were simplified. Very Good!
OH
This course was very helpful and fruitful. It is a good entry for machine learning and I really recommend it. Thanks, Anna, Thanks, amii
AA
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.
SR
I have been teaching Machine Learning for some time now. This course is really good and comprehensively presents the working of machine learning process in a nutshell. Very good introductory course.
YR
one of the best ways to get started in machine learning is by this course. It rather starts with concepts before starting programing
MM
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.
BT
Course gives a broader understanding of any Machine Learning project, how to approach and what are the important things to keep in mind.
RS
I​ loved the way the course was structured, as it gave a very good introduction. The instructor was clear and concise during lectures.
PA
For me this is Excellent Course for you who want to know how we applied machine learning into business,I've learn so much , and the instructor ,I love the way she teach
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I enjoyed this course. It was a good refresher but I believe that it is also good for people that want to understand this Machine Learning hype...
The specialization based on this course sounds good. If the specialization delivers on what this course promises, it could be extremely valuable. However, I do not like how this introductory course was used in adjunction with the free 7-day trial. This course merely introduces important concepts while the rest of the courses would be the ones actually helping us learn the material in-depth, assuming they are able to deliver on that. I don't personally like how this 3-hour course just introducing terminology, even if it was informative, was released with the free trial for the entire specialization. I can't judge the specialization by this course.
Content done in 4 hours. A very general introduction. It is clearly targetted at Managers and practitioners interested to apply ML in the industry or private companies. It's much about issues dealing with ML project management. Not much of technical knowledge about ML here. Videos are clear. But I don't think it deserves a course in full. I an interested to do the next Courses of the Specialization to see how it gets more concrete
A great course for beginners (irrespective of their background knowledge) in machine learning especially if they are looking to apply machine learning in their daily lives or business needs. The instructor's friendly and warm demeanor as well as clear and concise explanations makes it really easy to follow and breeze through the course.
This course is a great as a non-technical introduction to machine learning processes from a business perspective. The explanations are very clear and the pace of the course wasn't too slow, so it didn't drag.
An excellent introduction to the mechanics of ML. Not so deep that coding is required, but simultaneously not so high-level as to be abstract. A very nice intro - thanks for this!
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The course is well structured and clearly taught. The instructor Anna Koop seems to be a very informed expert in the field and a good educator. Her language is clear. My only concern with the course is that there is not much of a space for practicing for learners. But, this may be simply because it is an introductory course. So, if you don't have expectations regarding hands-on practice, then this course is a very good one. Great intro to the field.
This course is great for getting you into applied machine learning. In fact, there is a strong emphasis on the business relevance of the technology. Every aspect of machine learning is well explained. And you finally embrace the importance of a clear definition of the business problem. I love the MLPL (machine learning process lifecycle). An effective framework and guide for delivering ML projects. Well done!
Just right course I was looking for a business level proficiency in machine learning. It enables a leader to map a business situation onto the requirements that may be addressed using machine learning, and to assess the business and technical efficacy of the model being developed by a data team. A graded assignment to test the learning in a given business scenario would be perfect addition to the course.
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.
Excellent introductory and conceptual course to machine learning, I really enjoiyed it, clear explanations and very illustrative examples. It clarifies me a lot of concepts like artificiall intelligence, data science and of course machine learning, I learnt a lot and enjoyed it very much.
Well planned and well organized, well written and nice resources for practice.
Just one more thing there should be a FAQ section for generic doubts regarding software problems, debugging and similar smaller problems regarding the theoretical course.
Thank you!!!
This course is amazing and above my expectations! Very good exercises, good speed, well communicated. The instructor made me feel very comfortable and was able to take many things away. Excellent content and very knowledgeable instructor!
Very Helpful course. This course walks you through Machine Learning in very simple way. You don't need to have technical understanding to learn this course. By end of the course, I was much more comfortable with Machine Learning.
An excellent, non-technical overview of Machine Learning projects for business managers. Recommended for those wanting to build broader AI and machine learning literacy and understanding within their organizations.
I have been teaching Machine Learning for some time now. This course is really good and comprehensively presents the working of machine learning process in a nutshell. Very good introductory course.
This is course is truly amazing for the people who want to know about the things that need to be considered when making a QUAM or an ML system. Looking forward to knowing more about ML!
It is a great course that meets its objective. It is very well structured and synthesized. The teacher is great, she explains everything in a concrete and fluent way. I recommend it.
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.