What are the Best Neural Network Courses on Udemy?

Similar to the brain of human intelligence, there is a brain for artificial intelligence too. That brain is called ‘Neural Networks’ or ‘deep learning.’ This branch of fake intelligence deals with analyzing and taking actions based on input information. A neural network is a web of neurons, similar to the human brain. For example, a neuron of artificial intelligence is mathematical formula or information from which the next step is decided. 

Neural networks consist of information storage called nodes which are connected to other nodes to form a network. The human brain inspires these computational neural networks. Target recognition, process modeling, control, machine diagnostics, portfolio management, credit rating, medical diagnosis, targeted marketing, fraud detection, intelligent searching, etc., are some of the applications of neural networks. 

Due to the profound advent of information technology and artificial intelligence in our lives, the demand for highly skilled engineers in the branch of the neural network of artificial intelligence has grown manifold in the last decade. All the new voice recognition, verbal instruction responsive systems that find their way in our lives result from Neural network engineers’ efforts.

Let us check out the best 10 courses on Neural Network courses on Udemy, the largest online learning platform.

Reviews of 10 Best Neural Network Courses on Udemy

1. Deep Learning A-Z: Hands-on Artificial Neural Networks by Kirill Eremenko and the team

Deep Learning A-Z Hands-on Artificial Neural Networks by Kirill Eremenko and the team

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This course attended by more than three lakh students worldwide and rated by more than twenty thousand students as a five-star course starts with teaching you the intuition behind artificial thinking. Then it slowly takes you into the subject of convolutional neural network systems. In subsequent levels of this course, you are taught about the intuition behind recurrent neural networks, self-organizing maps, Boltzmann machines, autoencoders, and how to apply all of them to achieve your requirements.

This course has an enormous amount of information. It consists of more than twenty-two hours of video lectures supported by thirty-seven articles for your reference and five downloadable resources for your practice. As per the review of the students, this course helps make your fundamentals strong to further build the advanced levels upon it.


2. Machine Learning, Data Sciences, and Deep Learning with Python by Frank Kane

Machine Learning, Data Sciences, and Deep Learning with Python by Frank Kane

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This course by Frank Kane teaches you data visualization using MatPlotLib and Seaborn platforms. The subject of Neural networks is taught as a part of the entire course on deep learning. This course has been attended by close to one and a half lakh students from across the world. You will be taught how to implement machine learning at a massive scale with Apache Spark’s MLLib. 

You will also be guided to create a real-time project of building a movie recommender system using item-based and user-based collaborative filtering. This course has more than fifteen hour-long video courses, supported by six reference articles and a downloadable resource for testing your knowledge. As per the reviews by the learners, the course was precise, to the point, and organized perfectly to make the student understand the subject without any confusion.

See Also: What are the Best Programming Courses on Udemy?


3. Data Science – Deep Learning and Neural Networks in Python by Lazy Programmer Inc.

Data Science - Deep Learning and Neural Networks in Python by Lazy Programmer Inc.

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This course by Lazy programmer inc. It teaches you how machine learning works instead of just showing diagrams and coding. It helps you code a neural network program in Python and Numpy from scratch. Instead of just coding, it also teaches you how neural networking is built on the basic building blocks called neurons. 

This course adds additional value by introducing the different types of neural networks and the different applications used to solve various problem statements. You will learn the entire course in a mere eleven hours. Therefore, it is better to revise your basic mathematics, such as calculus, derivatives, probability, matrix arithmetics, before attending the course. Moreover, it will not waste any additional time if you are pre-equipped with Numpy, Python, and Tensorflow before joining. 


4. Deep Learning – Recurrent Neural Networks in Python by Lazy Programmer Inc.

Deep Learning - Recurrent Neural Networks in Python by Lazy Programmer Inc.

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In this twelve-hour-long video course, you will be taught GRU, Stock predictions, Natural Language Processing, Time Series Forecasting, LSTM, and many more using artificial intelligence. This course has been attended by more than twenty-five thousand students from across the world. You will also learn how to apply RNNs to time series forecasting, image classification, text classification activities such as spam detection.

You will be taught how to solve problems during the coding, like the vanishing gradient program, and understand the simple recurrent unit. As per the students’ review, the tutor has used simple real-life examples to make you understand this subject without any difficulty. In addition, the tutor has been so helpful in guiding the students in creating an actual life project by making use of the skills taught in this course.


5. Deep Learning; Convolutional Neural Networks in Python by Lazy Programmer Inc.

Deep Learning; Convolutional Neural Networks in Python by Lazy Programmer Inc.

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This course by Lazy programmer is another gem from the same author’s series on neural networks. This course attended by more than twenty-five students teaches you how to use CNNs for image recognition, Natural Language Processing, artificial intelligence, machine learning, and data science. In this twelve-hour-long video course, you will learn how convolution is helpful for deep understanding and implement it in Tensorflow2. 

Furthermore, you will understand and able to explain the architecture of a CNN. This course will also teach you how to build a model image data in code, model text data for NLP, use embeddings for tensorflow2 for NLP, and use batch normalization and dropout regularization Tensorflow2, and many more.


6. Convolutional Neural Networks in Python – CNN computer vision by Start-Tech Academy

Convolutional Neural Networks in Python - CNN computer vision by Start-Tech Academy

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This course on Convolutional Neural Networks(CNNs) teaches you the subject in the least possible time. This course consists of a close to eight-hour-long video course that teaches you how to use the Python platform for computer vision and image recognition. By the end of this course, you will have a strong understanding of CNNs and deep learning. Along with these, you must have also gained expertise in artificial neural networks to make predictions. 

You will be provided with four reference articles to let you learn the usage of Keras and Tensorflow libraries. Once you complete this course, you will identify the image recognition problems that can be solved using CNN models. Many other systems on the same subject teach you how to run analysis, but this course believes that solid theoretical knowledge is essential to building future projects.

See Also: What are the Best NLP Courses on Udemy?


7. The Complete Neural Networks Bootcamp – Theory, Applications by Fawaz Sammani

The Complete Neural Networks Bootcamp - Theory, Applications by Fawaz Sammani

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Click Here to View Course DetailsThis course is one of the highest-rated courses on the Udemy platform on the subject of neural networks. You will be provided with enormous video lectures that are close to forty hours and are supported by fifteen articles for knowledge sharing and two downloadable resources for practice purposes. In addition, this course will be taught about deep learning and neural networks theory and their applications with Python.

By the end of this course, you will understand how the backpropagation algorithm works, transfer learning to CNNs, understand weight initialization and regularization techniques, CNN visualization, and many more. As per the reviews by the learners, the course is updated by the tutor very regularly and has been explained by him lucidly.


8. Neural Networks in Python – Deep Learning for Beginners by Start-Tech Academy

Neural Networks in Python - Deep Learning for Beginners by Start-Tech Academy

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If you want to learn about neural networks on the Python platform within 10 hours, this is the right course. This course teaches you how to build predictive deep learning models using Keras and Tensorflow software. This course is provided with four reference articles, one downloadable resource, and one practice test for brushing up your skills. This course helps you tackle the real business scenarios where applying for neural networks works. 

A verifiable certificate of completion of the course is provided to you upon completing all the video modules. You will also learn how to create ANN models in Python, data preprocessing, classic ML technique – Linear Regression. This course is especially for those who want to establish their career in deep learning and neural networking.


9. Artificial Neural Networks(ANNs) with Keras in Python and R by Start-Tech Academy

Artificial Neural Networks(ANNs) with Keras in Python and R by Start-Tech Academy

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In this eleven-hour-long video course attended by more than one lakh students, the tutor lets you understand deep learning and build neural networks using Tensorflow2.0 and Keras in Python and R. By completing this course, you will know about how to solve real business scenarios using Neural network models. Confidently practice, discuss and understand deep learning concepts, and clearly understand advanced neural network concepts such as Gradient descent, forward, backward propagation, etc.

This course is supported by three reference articles and three downloadable resources to help you practice real-life problem solving with the help of the knowledge you gain from this course. As per the reviews by the learners, the tutor first makes the learners familiarize themselves with basic Python and R concepts and then slowly takes them to the application of ANNs.


10. Deep Learning CNN – Convolutional Neural Networks with Python

Deep Learning CNN - Convolutional Neural Networks with Python

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This course is a relatively new course on the subject on the Udemy platform. In this course, you will have the opportunity to learn to use CNN for image recognition, computer vision using Tensorflow2 & VGG face2. You will also be taught about the importance of CNN in data science and the essential concepts with comprehensive unfolding with examples in Python. State-of-the-art CNNs that are much more recent, accurate, and efficient are taught in this course.

After completing this course, you will build your applications for human face verification and neural style transfer to understand why hand engineering shifts to CNNs. As per the reviews by the learner, the course is expressive, exhaustive, practical with live coding, easy to understand.

Conclusion

Every business that wants to penetrate deep into society has to first connect with the customer personally. To create and maintain that relationship, enormous human resources are needed. Hence, companies nowadays are looking to replace the human need with an artificial brain that can converse, take instructions and respond accordingly to the user’s requirements. To develop these systems, businesses are in dire need of skilled engineers in neural networks. In the last decade, the science of neural networks has grown into a very lucrative career for professional engineers.

To beat the competition and push themselves ahead, the professionals require unique and practical knowledge which can be delivered through these courses. So, wait no more and enroll in one of these courses already. If you have any more queries to be clarified, please let us know in the comments section. We will reply as soon as possible.

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