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Andrew Ng Courses – All Machine Learning and Deep Learning Courses

All Machine Learning and Deep Learning Courses
Data Science

Andrew Ng Courses – All Machine Learning and Deep Learning Courses



In this article, we’ve listed all Machine Learning and Deep Learning courses by Andrew Ng, an excellent teacher from Standford University, and a tech-entrepreneur.

All Machine Learning and Deep Learning Courses

The Machine Learning and Deep Learning courses given below are all available on Coursera in case you are interested in enrolling in any one of them.

1. AI For Everyone Course by Andrew Ng and DeepLearning.AI – Coursera

The ‘AI For Everyone’ Course by Andrew Ng and DeepLearning.AI focuses on teaching the fundamental concepts needed to learn Artificial Intelligence.

AI For Everyone Course by Andrew Ng and DeepLearning.AI

In this course, you will learn the meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science; What AI realistically can and cannot do; How to spot opportunities to apply AI to problems in your own organization; What it feels like to build machine learning and data science projects; How to work with an AI team and build an AI strategy in your company; How to navigate ethical and societal discussions surrounding AI.

2. Machine Learning Course by Andrew Ng and Stanford – Coursera

The Machine Learning course by Stanford and popularized by Andrew Ng’s teaching is the best certification course in Machine Learning you can go for.

Machine Learning by Andrew Ng and Stanford

The course is 11 weeks long and covers almost everything that you need to know about Machine Learning with great examples and assignments. The course has a 4.9/5 average rating from over 160,000 student ratings.

3. Neural Networks and Deep Learning Course by Andrew Ng and DeepLearning.AI – Coursera

The ‘Neural Networks and Deep Learning’ course by Andrew Ng is part of the Deep Learning Specialization and teaches you the foundational concept of neural networks and deep learning.

Neural Networks and Deep Learning Course by Andrew Ng and DeepLearning.AI

By the end of this course, you will be familiar with the significant technological trends driving the rise of deep learning, build, train, and apply fully connected deep neural networks, implement efficient (vectorized) neural networks, identify key parameters in a neural network’s architecture, and apply deep learning to your own applications.

4. Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization Course by Andrew Ng and DeepLearning.AI – Coursera

The ‘Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization’ course by Andrew Ng is part of the Deep Learning Specialization in which you will open the deep learning black box to understand the processes that drive performance and generate good results in deep learning systematically.

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization Course by Andrew Ng and DeepLearning.AI

By the end of this course, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow.

5. Structuring Machine Learning Projects Course by Andrew Ng and DeepLearning.AI – Coursera

The ‘Structuring Machine Learning Projects’ course by Andrew Ng is part of the Deep Learning Specialization in which you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader.

Structuring Machine Learning Projects by Andrew Ng and DeepLearning.AI

By the end of this course, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning.

6. Convolutional Neural Networks Course by Andrew Ng and DeepLearning.AI – Coursera

The ‘Convolutional Neural Networks’ course by Andrew Ng is part of the Deep Learning Specialization in which you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more.

Convolutional Neural Networks by Andrew Ng and DeepLearning.AI

By the end of this course, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data.

7. Sequence Models Course by Andrew Ng and DeepLearning.AI – Coursera

The ‘Sequence Models’ course by Andrew Ng is part of the Deep Learning Specialization in which you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more.

Sequence Models by Andrew Ng and DeepLearning.AI

By the end of this course, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use HuggingFace tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering.

8. Introduction to Machine Learning in Production Course by Andrew Ng and DeepLearning.AI – Coursera

The ‘Introduction to Machine Learning in Production’ course by Andrew Ng is part of the Machine Learning Engineering for Production (MLOps) Specialization.

Introduction to Machine Learning in Production Course by Andrew Ng and DeepLearning.AI

By the end of this course, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype the process for developing, deploying, and continuously improving a productionized ML application.


Andrew Ng Courses - All Machine Learning and Deep Learning Courses Andrew Ng Courses - All Machine Learning and Deep Learning Courses

Comments (2)

  1. Amir Nasr

    Hello and thank you for such a great post!
    I’m an AI enthusiast who recently decided to study Andrew’s courses, but a little too new to understand the correct order of the list you have provided. Could you please point it out?
    Thank you once more for your time in advance

    1. The Click Reader

      We’ve updated the list in the order recommended to study the courses. Hope it helps!

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