Name: Advanced Learning Algorithms
Brand: DeepLearning.AI
Availability: OnlineOnly
Rating: 4.9 (1234 reviews)

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Learner Reviews & Feedback for Advanced Learning Algorithms by DeepLearning.AI

4.9

stars

8,281 ratings

About the Course

In the second course of the Machine Learning Specialization, you will: • Build and train a neural network with TensorFlow to perform multi-class classification • Apply best practices for machine learning development so that your models generalize to data and tasks in the real world • Build and use decision trees and tree ensemble methods, including random forests and boosted trees The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key theoretical concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start....

Top reviews

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.

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!

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1226 - 1237 of 1,237 Reviews for Advanced Learning Algorithms

By Shahzaib k

•

Aug 8, 2024

its a great course that I have done in my life .I am really excited that I should able to learn some thing new from Andrew ng which is best professor of all time. I am really thankful to the all the team members and the staff who contribute in creating the specialization machine learning course . I am the luckiest student that I should participate and join the coursera platform for my personal growth . I really re commend this course and specially the course platform for the machine learner who want to be a part of this platform . This platform provide a great opportunity to learn new thing and deep dive into the new trending technology .

By Philip R K

•

Sep 8, 2025

Why Course Two Was Operationally Hollow This course promised depth in decision trees, random forests, and XGBoost—but delivered mimicry, not architecture. Key concepts like entropy, information gain, and ensemble logic were introduced without derivation, context, or programming scaffolding. Students were expected to implement complex algorithms from scratch despite never being shown how recursion, data partitioning, or impurity metrics actually work in code. Autograders enforced formatting rituals rather than validating understanding, punishing deviation while never explaining edge cases like pure nodes or split logic. The labs relied on sedative walkthroughs and vague diagrams, leaving learners to reverse-engineer functionality from silence. Every skill gained came not from instruction, but from reverse-engineering its collapse.

By Patricia R

•

Oct 20, 2023

La verdad no me gustó porque finalmente uno lo intenta y sin aprobar los laboratorios que no entiendo por que dan error si apruebo los test, segun el sistema igualmente indican que no estás aprobado y no hay forma de obtener los certificados aunque hayas cursado todo y aprobado los examenes remanentes, asi que mal, realmente me ha pasado ya varias veces con coursera asi que me rindo siento que así no vale la pena tanto esfuerzo porque al final vale es el certificado

By Paul J

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Apr 13, 2023

If I could give it negative stars I would. You have completely wasted my time and money. I got to the next-to-last question on the last graded lab, and although my results appeared to match what was required -- according to the lab feedbac - an odd Python error was triggered that caused my submission to be ungrade-able. ZERO useful feedback provided. This ended up being a rip-off.

By Brian H

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Sep 26, 2023

No means to get help for final assignment. Received correct expected answers for all four questions but was given a 0% on the grade with no access to course help.