学生对 DeepLearning.AI 提供的 Advanced Learning Algorithms 的评价和反馈
课程概述
热门审阅
DG
Apr 14, 2023
Extremely educational with great examples. Helpful to know Python beforehand or the syntax will become a time sync, and understanding the mathematics as going through the class makes it a decent pace.
SB
Nov 6, 2022
This course is a brief but thorough introduction. It has a good mixture of theory and practice.Andrew Ng explains every thing very good, understandable and in a fun way.I highly recommend this class!
176 - Advanced Learning Algorithms 的 200 个评论(共 1,265 个)
创建者 Fareed K
•Dec 16, 2022
I liked the course, I appreciate the videos and the course material by Mr Andrew Ng and his team. I have benefited to a good extent in understanding the neural network, I hope to create some applications in future.
创建者 Arihant G
•Feb 2, 2023
Greatly designed, especially the assignments. The assignments were such that they allowed to focus on learning the essence of the algorithm without getting bogged down by the complexity of full code implementation.
创建者 Ramin B
•Jan 26, 2025
I enjoyed every second of this course. Andrew is an exceptional instructor who breaks down complex concepts into simple terms, making them understandable for people from different backgrounds. Totally recommended
创建者 Hooman M G
•Apr 10, 2024
This course was very helpful for me. The most notable feature of this course is the intuitive and easy-to-grasp approach it uses to teach the material. I encourage anyone from any background to join this course.
创建者 Valentin B
•May 4, 2023
Awesome. Always Andrew explains the concepts so clearly, turning something complex to something easy to understand. The quizzes and labs are very helpful as well to practice and make sure one gets the material.
创建者 Lei L
•Feb 3, 2023
Highly recommended! It made complex models & algorithms simple to understand. It also helped me to realize the power of linear algebra and calculus which I thought were useless at one point of my college study.
创建者 Armin F
•Nov 7, 2022
I think many machine learning concepts from data clean to training to error analysis discussed here for both supervised classification and regression problems. Both Neural network and decision trees discussed.
创建者 Caroline C
•Jul 27, 2022
The concepts are explained in detail without anything rushed or skipped. It is worth it. Thank you for this course, if it wasn't for you, this opportunity would have never reached someone like me in Africa.
创建者 Yamm E
•Jun 21, 2023
I was able to do this class during the spring quarter, it was perfect. I could do it slower or faster based on exams and still learn a lot. The interactive labs were great as well. 10/10 would recommend it.
创建者 Sven S
•Feb 10, 2023
Excellent course about advanced learning algorithms like neural network and decision trees! You'll gain a solid understanding of how those algorithms work and learn how to implement them yourself in Python.
创建者 Nur M H
•Mar 27, 2023
Excellent course on machine learning techniques, including neural networks and decision trees, with lots of helpful information on how to enhance them and real-world implementation examples. Regards, sir.
创建者 Abhay K
•Jul 24, 2023
Best course on machine learning even for the beginners. The teacher himself is the best and teaches everything in a very simple way. Just loved it. Thank you for creating such a nice and helpful course.
创建者 Don G
•Apr 15, 2023
Extremely educational with great examples. Helpful to know Python beforehand or the syntax will become a time sync, and understanding the mathematics as going through the class makes it a decent pace.
创建者 Muhammad A
•Jun 22, 2025
The course is well crafted and enriched with deep learning and ensemble tree knowledge. Practice labs add strength to the development of skills. Overall good learning experience under sir Andrew NG.
创建者 Matthew W
•Dec 12, 2024
Andrew was a great teacher, explaining complicated topics in a simple and intuitive way. The programming assignments helped to put theory into practice. A great place to start learning a new field!
创建者 Md. P
•Nov 5, 2025
One of the best course for Learning Neural Network Fundamentals also dive into the advance algorithm like Decision trees,Random forest or XGB Algorithm. Thanks Andrew Ng for the top-notch course.
创建者 Cristian A A S
•Nov 2, 2024
This is a great introduction to Neural Networks and decision Trees! The only thing missing is more applied projects, but that's nothing a little bit of Kaggle can't fix. It's totally recommended!
创建者 Sian R
•Oct 31, 2024
This Course helped me to fundamentally understand Neural Network's Magical Dance and helped to explore the Wonderful Forest of Randomness and hence enabled me to have strong grasp on these Topics
创建者 Ludeke
•Feb 28, 2023
Worth it! Can easily be complete within a month (even during a full, in-person, university class load). I used this to learn more about machine learning prior to conducting biomedical research.
创建者 Arunabh S
•Mar 21, 2025
Really well explained course, keeping the lessons lengths short and explained in easy language. I am amazed at how much I feel I have learned in the last few weeks since I started this course.
创建者 Aquib V
•Mar 1, 2024
Amazing content, perfectly curated topics with hands-on labs, although Assignments and labs could be more challenging based on certain level students who already have programming backgrounds.
创建者 Lidia S E
•Aug 8, 2023
Very good course to understand the basics of Machine Learning at a deep level. I really enjoyed taking this course and all the explanations and exercises provided. I cannot recommend it more!
创建者 Aditya K
•Jul 12, 2024
what amazing course, I had never thought that i could understand these complex ml algorithm but this course not only made me understand them also taught me create these models from scratch🤯
创建者 Jianhua M
•Jul 18, 2022
The elementary method such as Linear Regression Model more meaningful than the hard method. Dr. Andrew Ng lectures are a very good combination of profound thought and perfect form. Thanks!
创建者 أحمد ر م
•Aug 12, 2025
The course only lacks to a real-world project with a real data and a whole ML project from data cleaning, feature engineering, and model development. But for the content, it is very strong.