A Coursera specialization by Andrew Ng, offered through DeepLearning.ai, that introduces core machine learning concepts and practical techniques for beginners. It is the newer successor to Ng's well-known Stanford-derived machine learning course.

Commenters call it a very famous, industry-respected starting point, with Andrew Ng's courses described as the best option for learners who don't need graduate-level math.

On Reddit (5)

1. Strongly recommendsIronFilmr/learnprogramming2023in “Best way to start with AI”▲ 3

   Do the ***very*** famous course in Machine Learning that Andrew Ng taught. https://www.deeplearning.ai/courses/machine-learning-specialization/

2. Recommendsahmad4919r/learnmachinelearning2023in “How do I start learning ML as a beginner?”

   Machine Learning Specialization by DeepLearning.ai is good.. Datacamp is also good, they have some good machine learning lectures. If you want to go for deep learning, i highly recommend to watch neural networks zero to heros series by Sr Andrej Karpathy on youtube.

3. RecommendsBellyDancerUrgotr/learnmachinelearning2022in “How long to get a job at an ML engineer?”▲ 43

   Yes front end knowledge doesn't translate to ML at all. And ML is a lot more than just programming. Do some certifications like the ML and the DL specialization from deeplearning.ai , I think Andrew's courses are by far the best from an industry point of view where you don't need masters or PhD…

4. Mentionsmano-vijnanar/learnmachinelearning2022in “Help with getting started ML”

   Start with FastAI's Deep Learning for Coders, do some projects, and only then go back and learn math (Coding the Matrix or MIT's open courseware course for linear algebra, and MIT's calculus courses if necessary. Otherwise, if you're getting by fine with a more shallow understanding just watch…

5. Mentionstoodimr/MachineLearning2015in “In your experience, which machine learning course on Coursera (or other MOOC web site) was the best?”

   It really depends on what you're looking for. There are a lot of good courses out there but they all differ a bit in terms of content, prerequisites, etc. Here's a summary of some of the more popular ones (In order of increasing difficulty/math required): Into to ML (Udacity): ML sampler with…

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