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    • Deep Learning

    Deep Learning Courses Online

    Study deep learning for advanced machine learning. Learn about neural networks, backpropagation, and deep learning frameworks.

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    Explore the Deep Learning Course Catalog

    • D

      DeepLearning.AI

      Deep Learning

      Skills you'll gain: Machine Learning, Deep Learning, Artificial Neural Networks, Machine Learning Algorithms, Applied Machine Learning, Python Programming, Machine Learning Software, Network Model, Algorithms, Computer Programming, Computer Vision, Network Architecture, Natural Language Processing, Tensorflow, Human Learning, Exploratory Data Analysis, Organizational Development, Process Analysis, Strategy, Mathematics, Mathematical Theory & Analysis, Regression, Calculus

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      145K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Neural Networks and Deep Learning

      Skills you'll gain: Artificial Neural Networks, Deep Learning, Machine Learning, Machine Learning Algorithms, Python Programming, Computer Programming, Network Architecture, Network Model, Calculus, Human Learning, Regression, Mathematics

      4.9
      Rating, 4.9 out of 5 stars
      ·
      122K reviews

      Intermediate · Course · 1 - 4 Weeks

    • D
      S

      Multiple educators

      Machine Learning

      Skills you'll gain: Machine Learning, Machine Learning Algorithms, Applied Machine Learning, Algorithms, Deep Learning, Machine Learning Software, Artificial Neural Networks, Human Learning, Statistical Machine Learning, Python Programming, Regression, Mathematics, Tensorflow, Critical Thinking, Network Model, Training, Reinforcement Learning

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      31K reviews

      Beginner · Specialization · 1 - 3 Months

    • I

      IBM

      Introduction to Deep Learning & Neural Networks with Keras

      Skills you'll gain: Algorithms, Artificial Neural Networks, Deep Learning, Human Learning, Machine Learning, Machine Learning Algorithms, Network Model, Applied Machine Learning, Network Architecture, Python Programming, Regression

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.7K reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      IBM Deep Learning with PyTorch, Keras and Tensorflow

      Skills you'll gain: Deep Learning, Machine Learning, Artificial Neural Networks, Machine Learning Algorithms, Python Programming, Applied Machine Learning, Human Learning, Algorithms, Network Model, Extract, Transform, Load, Network Architecture, Data Analysis, Data Visualization, Machine Learning Software, Reinforcement Learning, Tensorflow, Regression

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      Illinois Tech

      Deep Learning

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      8 reviews

      Beginner · Course · 1 - 3 Months

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      D

      DeepLearning.AI

      DeepLearning.AI TensorFlow Developer

      Skills you'll gain: Artificial Neural Networks, Computer Programming, Computer Vision, Deep Learning, Forecasting, Machine Learning, Natural Language Processing, Tensorflow

      4.7
      Rating, 4.7 out of 5 stars
      ·
      25K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Placeholder
      D

      DeepLearning.AI

      Convolutional Neural Networks

      Skills you'll gain: Artificial Neural Networks, Computer Vision, Machine Learning, Applied Machine Learning, Deep Learning, Machine Learning Software, Machine Learning Algorithms, Network Model, Tensorflow, Algorithms, Human Learning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      42K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Placeholder
      I

      IBM

      Deep Learning with PyTorch

      4.4
      Rating, 4.4 out of 5 stars
      ·
      10 reviews

      Intermediate · Course · 1 - 3 Months

    • Placeholder
      I

      IBM

      Deep Learning and Reinforcement Learning

      Skills you'll gain: Artificial Neural Networks, Deep Learning, Human Learning, Machine Learning, Machine Learning Algorithms, Applied Machine Learning, Reinforcement Learning, Algorithms, Network Model, Tensorflow

      4.6
      Rating, 4.6 out of 5 stars
      ·
      225 reviews

      Intermediate · Course · 1 - 3 Months

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      M

      MathWorks

      Deep Learning for Computer Vision

      Skills you'll gain: Computer Vision, Deep Learning, Matlab

      4.9
      Rating, 4.9 out of 5 stars
      ·
      15 reviews

      Beginner · Specialization · 1 - 3 Months

    • Placeholder
      D

      DeepLearning.AI

      Mathematics for Machine Learning and Data Science

      Skills you'll gain: Machine Learning, Calculus, Differential Equations, Mathematics, Machine Learning Algorithms, Regression, Algebra, Algorithms, Artificial Neural Networks, General Statistics, Linear Algebra, Probability & Statistics, Statistical Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.5K reviews

      Intermediate · Specialization · 1 - 3 Months

    Searches related to deep learning

    deep learning specialization
    deep learning ai
    deep learning.ai
    deep learning for business
    deep learning with pytorch
    deep learning with pytorch : image segmentation
    deep learning with keras and tensorflow
    deep learning and reinforcement learning
    1234…350

    In summary, here are 10 of our most popular deep learning courses

    • Deep Learning: DeepLearning.AI
    • Neural Networks and Deep Learning: DeepLearning.AI
    • Machine Learning: DeepLearning.AI
    • Introduction to Deep Learning & Neural Networks with Keras: IBM
    • IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
    • Deep Learning: Illinois Tech
    • DeepLearning.AI TensorFlow Developer: DeepLearning.AI
    • Convolutional Neural Networks: DeepLearning.AI
    • Deep Learning with PyTorch: IBM
    • Deep Learning and Reinforcement Learning: IBM

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Deep Learning

    Deep learning is a powerful application of machine learning (ML) algorithms modeled after biological systems of information processing called artificial neural networks (ANN). Machine learning is an artificial intelligence (AI) technique that allows computers to automatically learn from data without explicit programming, and deep learning harnesses multiple layers of interconnected neural networks to generate more sophisticated insights.

    While this field of computer science is quite new, it is already being used in a growing range of important applications. Deep learning excels at automated image recognition, also known as computer vision, which is used for creating accurate facial recognition systems and safely driving autonomous vehicles. This approach is also used for speech recognition and natural language processing (NLP) applications, which allow for computers to interact with human users via voice commands.

    Machine learning algorithms such as logistic regression are key to creating deep learning applications, along with commonly used programming languages such as Tensorflow and Python. These programming languages are generally preferred for teaching and learning in this field due to their flexibility and relative accessibility - an important priority given the relevance of deep learning to a wide range of professionals without a computer science background.‎

    A familiarity with the capabilities and development process for deep learning applications can be an asset in a growing number of careers. For example, the use of deep learning is being explored in healthcare for automatic reading of radiology images, as well as searching for patterns in genes and pharmaceutical interactions that can aid in the discovery of new types of medicines. In many fields, even a basic understanding of deep learning can help professionals identify new potential applications of this powerful technology.

    Those with a deeper expertise in deep learning may become computer research scientists in this field, responsible for inventing new algorithms and finding new applications for these techniques. Given the wide range of uses for deep learning, computer scientists in this field are in high demand for jobs at private companies as well as government agencies and research universities. According to the Bureau of Labor Statistics, computer research scientists earned a median annual salary of $122,840 as of 2019, and these jobs are expected to grow much faster than average.‎

    Certainly - in fact, Coursera is one of the best places to learn about deep learning. Through partnerships with deeplearning.ai and Stanford University, Coursera offers courses as well as Specializations taught by some of the pioneering thinkers and educators in this field. You can also learn via courses and Specializations from industry leaders such as Google Cloud and Intel, or get a professional certificate from IBM. Guided Projects also offer an opportunity to build skills in deep learning through hands-on tutorials led by experienced instructors, allowing you to learn with confidence.‎

    The skills or experience you may need to have before studying deep learning, and which can help you better understand an advanced concept such as deep learning, can include sign language reading, music generation, and natural language processing (NLP), in addition to many others. If you have knowledge of Python 3 and understand the basic concepts of general machine-learning algorithms and deep learning, you may have the necessary skills to learn this specialization. You may also want to know about probability and statistics to study deep learning concepts. Basic math, such as algebra and calculus, is also an important prerequisite to deep learning because it relates to machine learning and data science. Also, if you have worked in the tech or artificial intelligence (AI) fields, you may have the necessary experience to study deep learning.‎

    The type of person who is best suited to study deep learning is someone comfortable working with statistics, programming, advanced calculus, advanced algebra, and engineering. Deep learning benefits someone passionate about working in the AI fields which can create types of deep learning networks that help machines perform human functions. A person best suited to learn about deep learning has a vested interest in understanding how the intelligence is built to run everything from driverless cars, mobile devices, stock trading systems, and robotic surgery equipment, for example. Deep learning benefits someone with a goal of working with systems such as computer vision, speech recognition, NLP, audio recognition bioinformatics systems, and medical image analysis.‎

    Deep learning may be right for you if you want to break into AI. The specialization may benefit you if you are a machine learning researcher or practitioner who is seeking to learn the next generation of machine learning, and you want to develop practical skills in the popular deep learning framework TensorFlow. Deep learning is one of the most highly sought-after skills in tech, and mastering it may lead you to many opportunities in the field of AI. It may also benefit you if you want to learn how to build neural networks and how to lead successful machine learning projects, and if you have a passion for learning about convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and how to master concepts in Python and TensorFlow.‎

    Online Deep Learning courses offer a convenient and flexible way to enhance your knowledge or learn new Deep Learning skills. Choose from a wide range of Deep Learning courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Deep Learning, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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