The 13 Best Deep Learning Courses and Online Training for 2023
The editors at Solutions Review have compiled this list of the best deep learning courses and online training to consider.
Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Based on artificial neural networks and representation learning, deep learning can be supervised, semi-supervised or unsupervised. Deep learning models are commonly based on convolutional neural networks but can also include propositional f formulas or latent variables organized by layer.
With this in mind, we’ve compiled this list of the best deep learning courses and online training to consider if you’re looking to grow your neural network and machine learning skills for work or play. This is not an exhaustive list, but one that features the best deep learning courses and online training from trusted online platforms. We made sure to mention and link to related courses on each platform that may be worth exploring as well.
The Best Deep Learning Courses
Neural Networks and Deep Learning
Platform: Coursera
Description: In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. By the end, 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.
Related paths/tracks: Introduction to Deep Learning, Applied AI with DeepLearning, Introduction to Deep Learning & Neural Networks with Keras, An Introduction to Practical Deep Learning, Building Deep Learning Models with TensorFlow
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Build Deep Learning Models with TensorFlow
Platform: Codecademy
Description: Deep learning is a cutting-edge form of machine learning inspired by the architecture of the human brain, but it doesn’t have to be intimidating. With TensorFlow, coupled with the Keras API and Python, it’s easy to train, test, and tune deep learning models without knowing advanced math. To start this
Path, sign up for Codecademy Pro.Go to training
Introduction to Deep Learning in Python
Platform: DataCamp
Description: Deep learning is the machine learning technique behind the most exciting capabilities in diverse areas like robotics, natural language processing, image recognition, and artificial intelligence, including the famous AlphaGo. In this course, you’ll gain hands-on, practical knowledge of how to use deep learning with Keras 2.0, the latest version of a cutting-edge library for deep learning in Python.
Related paths/tracks: Introduction to Deep Learning with PyTorch, Introduction to Deep Learning with Keras, Advanced Deep Learning with Keras
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Deep Learning Training – TensorFlow Certification
Platform: Edureka
Description: Deep Learning Training with TensorFlow Certification by Edureka is curated with the help of experienced industry professionals as per the latest requirements and demands. This deep learning certification course will help you master popular algorithms like CNN, RCNN, RNN, LSTM, and RBM using the latest TensorFlow 2.0 package in Python. In this deep learning training, you will be working on various real-time projects like Emotion and Gender Detection, Auto Image Captioning using CNN and LSTM, and many more.
Related path/track: Reinforcement Learning
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Introduction to Deep Learning
Platform: edX
Description: This 3-credit-hour, 16-week course covers the fundamentals of deep learning. Students will gain a principled understanding of the motivation, justification, and design considerations of the deep neural network approach to machine learning and will complete hands-on projects using TensorFlow and Keras.
Related paths/tracks: Deep Learning Fundamentals with Keras, Deep Learning with Python and PyTorch, Deep Learning with Tensorflow, Using GPUs to Scale and Speed-up Deep Learning, Deep Learning and Neural Networks for Financial Engineering, Machine Learning with Python: from Linear Models to Deep Learning
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Reinforcement Learning Course Certification Training
Platform: Intellipaat
Description: Intellipaat’s Online Reinforcement Learning course is designed by industry experts to assist you in learning and gaining expertise in reinforcement learning which is one of the core areas of machine learning. In this training, you will be educated on the concepts of machine learning fundamentals, reinforcement learning fundamentals, dynamic programming, temporal difference learning methods, policy gradient methods, Markov Decision, and Deep Q Learning. This Reinforcement Learning certification course will enable you to learn how to make decisions in uncertain circumstances.
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Deep Learning: Image Recognition
Platform: LinkedIn Learning
Description: In this course, learn how to build a deep neural network that can recognize objects in photographs. Find out how to adjust state-of-the-art deep neural networks to recognize new objects, without the need to retrain the network. Explore cloud-based image recognition APIs that you can use as an alternative to building your own systems. Learn the steps involved to start building and deploying your own image recognition system.
Related paths/tracks: Neural Networks and Convolutional Neural Networks Essential Training, Building and Deploying Deep Learning Applications with TensorFlow, PyTorch Essential Training: Deep Learning, Introduction to Deep Learning with OpenCV, Deep Learning: Face Recognition
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Deep Learning with Python Training
Platform: Mindmajix
Description: Mindmajix Deep learning with Python Training helps you in mastering various features of debugging concepts, introduction to software programmers, language abilities and capacities, modification of module and pattern designing, and various OS and compatibility approaches. This course also provides training on how to optimize a simple model in Pure Theano, convolutional and pooling layers, and reducing overfitting with dropout regularization. Enroll and get certified now.
Related path/track: AI & Deep Learning with TensorFlow Training
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Deep Learning: The Big Picture
Platform: Pluralsight
Description: In this course, Deep Learning: The Big Picture, you will first learn about the creation of deep neural networks with tools like TensorFlow and the Microsoft Cognitive Toolkit. Next, you’ll touch on how they are trained, by example, using data. Finally, you will be provided with a high-level understanding of the key concepts, vocabulary, and technology of deep learning. By the end of this course, you’ll understand what deep learning is, why it’s important, and how it will impact you, your business, and our world.
Related paths/tracks: Deep Learning with Keras, Building Deep Learning Models Using PyTorch, Deep Learning Using TensorFlow and Apache MXNet on Amazon Sagemaker
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Deep Learning Course Certification Training
Platform: Simplilearn
Description: In this deep learning course with Keras and TensorFlow certification training, you will become familiar with the language and fundamental concepts of artificial neural networks, PyTorch, autoencoders, and more. Upon completion, you will be able to build deep learning models, interpret results, and build your own deep learning project.
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Deep Learning and Neural Networks with Python
Platform: Skillshare
Description: It’s hard to imagine a hotter technology than deep learning, artificial intelligence, and artificial neural networks. If you’ve got some Python experience under your belt, this course will de-mystify this exciting field with all the major topics you need to know. A few hours is all it takes to get up to speed and learn what all the hype is about. If you’re afraid of AI, the best way to dispel that fear is by understanding how it really works – and that’s what this course delivers.
Related paths/tracks: Ultimate Neural Network and Deep Learning Masterclass, Deep Learning and AI with Python
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Deep Learning Nanodegree
Platform: Udacity
Description: Become an expert in neural networks, and learn to implement them using the deep learning framework PyTorch. Build convolutional networks for image recognition, recurrent networks for sequence generation, generative adversarial networks for image generation, and learn how to deploy models accessible from a website.
Related path/track: Become a Deep Reinforcement Learning Expert
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Deep Learning A-Z: Hands-On Artificial Neural Networks
Platform: Udemy
Description: Artificial intelligence is growing exponentially. There is no doubt about that. Self-driving cars are clocking up millions of miles, IBM Watson is diagnosing patients better than armies of doctors, and Google Deepmind’s AlphaGo beat the World champion at Go – a game where intuition plays a key role. But the further AI advances, the more complex become the problems it needs to solve. And only deep learning can solve such complex problems and that’s why it’s at the heart of artificial intelligence.
Related paths/tracks: Machine Learning, Data Science and Deep Learning with Python, Deep Learning Prerequisites: The Numpy Stack in Python, Complete Guide to TensorFlow for Deep Learning with Python, Data Science: Deep Learning and Neural Networks in Python, Tensorflow 2.0: Deep Learning and Artificial Intelligence, Complete Tensorflow 2 and Keras Deep Learning Bootcamp, Deep Learning Prerequisites: Linear Regression in Python, Natural Language Processing with Deep Learning in Python, Deep Learning: Convolutional Neural Networks in Python, Deep Learning: Recurrent Neural Networks in Python, Deep Learning and Computer Vision A-Z, Deep Learning Prerequisites: Logic Regression in Python
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NOW READ: The Best Deep Learning Books on Our Reading List
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