Home Collections 10 Best + Free Neural Networks Courses with Certificates

10 Best + Free Neural Networks Courses with Certificates

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TensorFlow is an open source machine learning framework. It has the ability to bring the power of machine learning to everyone. With the help of TensorFlow, it becomes easier for developers to create neural network based machine learning models. To know more about TensorFlow, our team at takethiscourse.net has compiled a list of Best + Free Neural Networks Courses with Certificates. With the help of courses/classes available in this list, you can find the right one for yourself and start learning today.

# Course Name University/Organization Ratings Duration
1. Deep Learning A-Z™: Hands-On Artificial Neural Networks Course Udemy ★★★★★ 4.5 22 Hours
2. Neural Networks and Deep Learning DeepLearning.AI ★★★★★ 4.9 25 Hours
3. Introduction to Artificial Neural Network and Deep Learning Udemy ★★★★★ 4.7 07 Hours
4. Build, Train, and Deploy Your First Neural Network with TensorFlow 2 Pluralsight ★★★★★ 4.7 03 Hours
5. Deep Learning: Recurrent Neural Networks in Python Udemy ★★★★★ 4.6 13 Hours
6. Recurrent Neural Networks (RNN) for Language Modeling in Python datacamp 04 Hours
7. Top Neural Network Courses Pluralsight
8. Convolutional Neural Networks in TensorFlow DeepLearning.AI ★★★★★ 4.7 17 Hours
9. Neural Networks in Python: Deep Learning for Beginners Udemy ★★★★★ 4.6 10 Hours
10. Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization DeepLearning.AI ★★★★★ 4.9 24 Hours
11. Free Neural Network Courses edX
12. Google Neural Network Course Google
In order to help our readers in taking a knowledgeable learning decision, TakeThisCourse.net has introduced a metric to measure the effectiveness of an online course. Learn more about how we measure an online course effectiveness.

Best + Free Neural Networks Courses with Certificates

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Deep Learning A-Z™: Hands-On Artificial Neural Networks Course

      • Kirill Eremenko via Udemy
      • 347,660+ already enrolled!
      • ★★★★★ (41,864 Ratings)

Deep Learning A-Z™ - Hands-On Artificial Neural Networks

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Excellent
★★★★★
Fair
★★★☆☆
Fair
★★★☆☆

In this course, you will be taught how to create deep learning algorithms in Python and that too from two machine learning and data science experts.

  • The best thing about this course is its focus on helping you understand the intuition behind artificial neural networks.
  • This course is for those who wish to learn to apply neural networks in practice.
This was an awesome course that taught me all about deep learning from A to Z. The course turned out to be great for beginners like me and I believe it has content that is also suitable for advanced level individuals. The course also offers great practice materials to get better hands-on practice. (Aamina K, ★★★★★)

Coursera Plus Courses

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Neural Networks and Deep Learning

      • DeepLearning.AI via Coursera
      • 1,145,585+ already enrolled!
      • ★★★★★ (117,273 Ratings)

Neural Networks and Deep Learning

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Excellent
★★★★★
Good
★★★★☆
Good
★★★★☆

This is an intermediate-level course that explains the foundational concept of neural networks and deep learning in detail. Here you will be familiarized with the significant technological trends that drive the rise of deep learning.

  • The reason why we chose this course is its focus on explaining how to build, train, and apply fully connected deep neural networks and implement efficient neural networks.
  • This course is for those who wish to understand the capabilities, challenges, and consequences of deep learning.
This was an extremely helpful course offering a great review of the basics rooted in mathematics but not overly cumbersome. I believe the entire content was explained in a clear manner and the example coding exercises helped a lot in understanding the importance of vectorization. (Brandon C, ★★★★★)

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Introduction to Artificial Neural Network and Deep Learning

      • Kirill Eremenko via Udemy
      • 3,258+ already enrolled!
      • ★★★★★ (654 Ratings)

Introduction to Artificial Neural Network and Deep Learning

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Good
★★★★☆
Fair
★★★☆☆
Fair
★★★☆☆

Are you interested in learning the best machine learning techniques for data science in Java and Neuroph with application in image recognition? If yes, then this course is for you.

  • The best thing about this course is its focus on explaining the entire process of neural networks and visualization in neural networks.
  • This course is for those who wish to learn to do regression and prediction using neural networks.
I would highly recommend this course to all those who are new in neural network and deep learning why because this course has the ability to explain all the concepts in an immense and clear manner. (Elis K, ★★★★★)

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Build, Train, and Deploy Your First Neural Network with TensorFlow 2

      • Jerry Kurata via Pluralsight
      • ★★★★★ (57 Ratings)
      • 03 Hours of effort required!
Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Good
★★★★☆
Good
★★★★☆
Fair
★★★☆☆
Fair
★★★☆☆

In this engaging class, the instructor will explain how to build, train, and deploy your first neural network with TensorFlow2. Here you will learn the foundational knowledge required for creating your own neural networks.

  • The best thing about this class is its focus on exploring the basic principles of how machine learning allows us to create models and how to apply principles to neural networks.
  • This class is for those who wish to learn to deploy their neural network and make its predictive power available to client applications.

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Deep Learning: Recurrent Neural Networks in Python

      • Lazy Programmer Inc. via Udemy
      • 31,615+ already enrolled!
      • ★★★★★ (4,229 Ratings)
Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Good
★★★★☆
Fair
★★★☆☆
Fair
★★★☆☆

This is a highly informative course that explains how to apply RNNs to Time Series Forecasting, Text Classification and Natural Language Processing.

  • The reason why we chose this course is its focus on helping you understand the simple recurrent unit (Elman Unit), GRU, and LSTM (Long short-term memory unit).
  • This course is for those who wish to understand how to mitigate the vanishing gradient problem and write various recurrent networks in TensorFlow 2.
Taking this course was a good decision that I made as the course was very helpful. It explained all the concepts of LSTM is a great manner and this is exactly what I was looking for. The course helped me a lot in completing my Master thesis. (Jonathan A, ★★★★★)

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Recurrent Neural Networks (RNN) for Language Modeling in Python

      • David Cecchini via datacamp
      • 11,355+ already enrolled!
      • 04 Hours of effort required!

A very engaging and highly informative class that explains how to use recurrent neural networks for classifying text, generate phrases, and translate Portuguese sentences into English.

  • The reason why we chose this class is its focus on explaining the foundations of recurrent neural networks.
  • This class is for those who wish to understand how information flows through a recurrent neural network.

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Top Neural Network Courses

      • via Pluralsight

If you are interested in learning all about neural networks and understand how it works then PluralSight has the best courses you can consider. These Top Neural Network Courses have been instructed by highly competitive instructors and allow you to study at your own ease and pace. So, find yourself a course today and start learning all about neural networks now.

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Convolutional Neural Networks in TensorFlow

      • DeepLearning.AI via Coursera
      • 120,551+ already enrolled!
      • ★★★★★ (7,630 Ratings)

Convolutional Neural Networks in TensorFlow

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Excellent
★★★★★
Good
★★★★☆
Fair
★★★☆☆

In this course, the instructor will explain how to handle real-world image data in detail.

  • The best thing about this course is its focus on explaining how to plot loss and accuracy and explore strategies to prevent overfitting.
  • This course is for those who wish to learn to transfer learning and understand how learned features can be extracted from models.
This course offers clear explanation on the concepts at a higher level and explains the practical applications in detail. The exercises were quite engaging and helpful. (Sandanakishnan S, ★★★★★)

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Neural Networks in Python: Deep Learning for Beginners

      • Start-Tech Academy via Udemy
      • 123,172+ already enrolled!
      • ★★★★★ (1,214 Ratings)

Neural Networks in Python - Deep Learning for Beginners

Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Good
★★★★☆
Fair
★★★☆☆
Fair
★★★☆☆

Are you interested in learning all about Artificial Neural Networks (ANN) in Python? In this course, you will learn to do that and understand how to build predictive deep learning models using Keras and TensorFlow.

  • The best thing about this course is its focus on explaining the business scenarios where Artificial Neural Networks (ANNs) are applicable.
  • This course is for those who wish to learn to use Pandas DataFrames for manipulating data and making statistical computations.
This was a great course that taught me so much even though I had prior experience in programming and statistics. (Jorge C, ★★★★★)

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Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

      • DeepLearning.AI via Coursera
      • 477,110+ already enrolled!
      • ★★★★★ (61,721 Ratings)
Online Course Effectiveness Score 
Content Engagement Practice Career Benefit
Excellent
★★★★★
Excellent
★★★★★
Good
★★★★☆
Good
★★★★☆

In this intermediate-level course, the instructor will talk about the deep learning black box to help you understand the processes that drive performance and generate good results systematically.

  • The best thing about this course is its focus on explaining the best practices to train and develop tests sets and analyze bias for building deep learning applications.
  • This course is for those who wish to understand how to use standard neural network techniques and learn about hyperparameter tuning, regularization and optimization in neural networks.
This was an excellent course that taught me how to implement ANN using Keras in Python. I can say I was able to understand so much about neural networks through this course. (RKS, ★★★★★)

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Free Neural Network Courses

      • via edX

If you are interested in learning all about neural networks and that too for free then you need to visit edX today as it offers free Neural Network courses that can help you build skills in artificial intelligence. Whether you want to master the AI basics or understand deep learning. Similarly, understand all about machine learning and finance or understand deep learning with Keras. Whatever you want to learn about neural networks, edX has a course that fits your needs.

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Google Neural Network Course

      • via Google

In this course, the instructor will explain how neural networks are a more sophisticated version of feature crosses.

  • The best thing about this course is its focus on helping you develop intuition about neural networks.
  • This course is for those who wish to understand all about hidden layers and activation functions and develop a good understanding of the neural networks.