Best Coursera Neural Networks Courses and Certification

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Coursera is a well known and popular MOOC teaching platform that partners with top universities and organizations to offer online courses.

A typical course at Coursera includes pre recorded video lectures, multi-choice quizzes, auto-graded and peer reviewed assignments, community discussion forum and a sharable electronic course completion certificate.

You can study the course materials for free with the help of audit option.

But you have to pay if you want course certification and peer graded assignments.

Some Coursera courses facilitate onetime payment fee that lasts for 180 days.

If you enroll to courses that are part of a specialization, you have to opt for monthly subscription fee to have access to the courses.

Coursera hosts around a good number of courses, specializations, certificate programs and master’s degree in the field of data science and machine learning.

All these courses are curated and taught by professors from world’s best universities.

Below are our best picks of Coursera neural network courses if you want to understand how neural networks work.

Neural Networks and Deep Learning –

The neural networks and deep learning coursera course from Andrew NG is a popular choice to get started with the complexities of neural networks and the math behind it.

It is the introductory course of his popular Deep learning specialization and gives you a solid start with deep learning basics.

Course Ratings: 4.9+ from 46,974+students

Key Learning’s from the Course:

  • Understand the major technology trends driving Deep Learning
  • How to build, train and apply fully connected deep neural networks
  • How to implement vectorized neural networks
  • Know the key parameters in a neural network’s architecture
  • How to build NN models from scratch
  • Understand the basics of NN programming

Who is this course best suited?  Learn how to create an entire deep neural network from scratch from a pioneer in ML and AI.

Skills Gained from the course: Artificial Neural Network, Backpropagation, Python Programming and Deep Learning

Course Reviews:


Convolutional Neural Networks –

The convolutional neural networks Coursera course teaches you how to build CNN and apply it to image data on various AI applications.

This is the fourth course of the popular Andrew NG deep learning specialization and covers both basics and applications of CNN in multiple fields (object detection, face recognition, neural style transfer, etc) in detail.

Course Ratings: 4.8+ from 18,660+ students

Key Learning’s from the Course:

  • Understand how to build CNN networks
  • How to apply CNN to visual detection and recognition tasks
  • How to use neural style transfer to generate art
  • How to apply algorithms to a variety of image, video and other data.

Who is this course best suited?  If you want an in-depth understanding of how CNN works in DL.

Skills Gained from the course: Facial Recognition System, TensorFlow, Convolutional Neural Network and Artificial Neural Network

Course Reviews:


Machine Learning – Stanford

The very much popular Coursera Andrew NG machine learning curriculum touches on the artificial neural network concepts for machine learning on a basic level.

It gives you a more grounded knowledge on the maths involved in NN’s and implementation of ML algorithms.

Course Ratings: 4.9+ from 94,947+ students

Key Learning’s from the Course:

  • Broad introduction to machine learning, data mining and statistical pattern
  • Understand supervised learning concepts: parametric/non-parametric algorithm, support vector machines, kernels and neural networks
  • Understand unsupervised learning techniques: Clustering, dimensionality reduction, recommender systems and deep learning
  • Best practices of machine learning
  • How to apply these ML algorithms to build various real world applications

Who is this course best suited?  If you want an introduction to neural networks for machine learning applications

Skills Gained from the course: Logistic Regression, Artificial Neural Network, ML Algorithms and Machine Learning

Course Reviews:


Practical Reinforcement Learning – National Research University

The deep neural networks Coursera Course is part of the Advance ML specialization from HSE.

It aims at teaching you in-depth about RL concepts and how to implement RL algorithms with interesting applications.

Note: Though the course is lauded for their rich content, the course has received mixed responses from their learners in terms of bugs in assignments and grading systems

Course Ratings: 4.2+ from 164+ students

Key Learning’s from the Course:

  • Foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc
  • How to use deep neural networks for RL tasks
  • How to apply RL algorithms such as ‘duct tape’ for practical problems
  • How to use neural networks to play games

Who is this course best suited?  If you want to know how to implement RL algorithms in deep neural networks

Skills Gained from the course: Deep neural networks, Reinforcement Algorithms, RL methods

Course Reviews:


Computational Neuroscience – University of Washington

Offered by University of Washington, the course teaches basic computational methods and understand how our nervous systems function and operate.

Course Ratings: 4.6+ from 480+ students

Key Learning’s from the Course:

  • Introduction to computational neuroscience and basic neurobiology
  • Understand what neural information coding means using mathematical formulations
  • The role of neural decoding in applications such as neuroprosthetics and brain-computer interfaces
  • Identify connection between information theory and neural coding
  • Understand the biophysics of neuron model called Hodgkin –Huxley model for spike generation
  • How to create network models with the help of neuron models
  • Understand such computational principles, processing of information in neural networks and algorithms for adaptation and learning

Who is this course best suited?  If you want a quantitative understanding of neurons and networks

Skills Gained from the course: Computational Neuroscience, Artificial Neural Network, Reinforcement Learning and Biological Neuron Mode

Course Reviews:


Do you recommend any other Coursera Neural Networks courses worth enrolling into? Let us know in the comments.

Happy Learning!