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    • Neural Networks

    Neural Networks Courses Online

    Study neural networks for deep learning applications. Learn about network architectures, training algorithms, and model evaluation.

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    Explore the Neural Networks Course Catalog

    • D

      DeepLearning.AI

      Neural Networks and Deep Learning

      Skills you'll gain: Deep Learning, Artificial Neural Networks, Tensorflow, Supervised Learning, Keras (Neural Network Library), Artificial Intelligence, Machine Learning, Python Programming, NumPy, Performance Tuning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      123K reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Convolutional Neural Networks

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Artificial Intelligence, Network Architecture, Machine Learning, Data Processing, Algorithms

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

      Intermediate · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Deep Learning

      Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Supervised Learning, Keras (Neural Network Library), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Debugging, Performance Tuning, Machine Learning Methods, Python Programming, Data-Driven Decision-Making, Text Mining, Network Architecture

      Build toward a degree

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

      Intermediate · Specialization · 3 - 6 Months

    • J

      Johns Hopkins University

      Foundations of Neural Networks

      Skills you'll gain: Data Ethics, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Reinforcement Learning, Generative AI, Debugging, Artificial Intelligence, Unsupervised Learning, Machine Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Ethical Standards And Conduct, Network Model, Bayesian Statistics, Network Architecture, Unstructured Data, Linear Algebra

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Introduction to Deep Learning & Neural Networks with Keras

      Skills you'll gain: Keras (Neural Network Library), Unsupervised Learning, Deep Learning, Artificial Neural Networks, PyTorch (Machine Learning Library), Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Supervised Learning, Regression Analysis

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

      Intermediate · Course · 1 - 3 Months

    • D
      S

      Multiple educators

      Machine Learning

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Algorithms, Applied Machine Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Artificial Neural Networks

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      32K reviews

      Beginner · Specialization · 1 - 3 Months

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      I

      IBM

      Introduction to Neural Networks and PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Statistical Methods, Artificial Neural Networks, Deep Learning, Feature Engineering, Probability Distribution, Performance Tuning, Machine Learning, Regression Analysis, Data Processing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 3 Months

    • Placeholder
      I

      IBM

      IBM AI Engineering

      Skills you'll gain: PyTorch (Machine Learning Library), Supervised Learning, Feature Engineering, Generative AI, Keras (Neural Network Library), Jupyter, Unsupervised Learning, Natural Language Processing, Reinforcement Learning, Deep Learning, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Data Manipulation, Tensorflow, Python Programming, Verification And Validation, Applied Machine Learning, ChatGPT, Artificial Neural Networks, Statistical Machine Learning

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      20K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

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      Status: Free
      Free
      U

      University of Washington

      Computational Neuroscience

      Skills you'll gain: Machine Learning Methods, Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Computer Vision, Reinforcement Learning, Computational Thinking, Mathematical Modeling, Linear Algebra, Data Analysis, Information Architecture, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • Placeholder
      J

      Johns Hopkins University

      Introduction to Neural Networks

      Skills you'll gain: Artificial Neural Networks, Machine Learning Algorithms, Deep Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Network Model, Network Architecture, Linear Algebra, Probability & Statistics

      Intermediate · Course · 1 - 3 Months

    • Placeholder
      D

      Duke University

      Introduction to Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Image Analysis, Applied Machine Learning, Deep Learning, Machine Learning, Natural Language Processing, Supervised Learning, Artificial Neural Networks, Computer Vision, Regression Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • Placeholder
      D

      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Data Ethics, Market Opportunities, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Team Building, Machine Learning, Strategic Thinking, Generative AI, Data Science, Deep Learning, Business Ethics, Artificial Neural Networks, Business Transformation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      46K reviews

      Beginner · Course · 1 - 4 Weeks

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    In summary, here are 10 of our most popular neural networks courses

    • Neural Networks and Deep Learning: DeepLearning.AI
    • Convolutional Neural Networks: DeepLearning.AI
    • Deep Learning: DeepLearning.AI
    • Foundations of Neural Networks: Johns Hopkins University
    • Introduction to Deep Learning & Neural Networks with Keras: IBM
    • Machine Learning: DeepLearning.AI
    • Introduction to Neural Networks and PyTorch: IBM
    • IBM AI Engineering: IBM
    • Computational Neuroscience: University of Washington
    • Introduction to Neural Networks: Johns Hopkins University

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    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 Neural Networks

    Neural networks, also known as neural nets or artificial neural networks (ANN), are machine learning algorithms organized in networks that mimic the functioning of neurons in the human brain. Using this biological neuron model, these systems are capable of unsupervised learning from massive datasets.

    This is an important enabler for artificial intelligence (AI) applications, which are used across a growing range of tasks including image recognition, natural language processing (NLP), and medical diagnosis. The related field of deep learning also relies on neural networks, typically using a convolutional neural network (CNN) architecture that connects multiple layers of neural networks in order to enable more sophisticated applications.

    For example, using deep learning, a facial recognition system can be created without specifying features such as eye and hair color; instead, the program can simply be fed thousands of images of faces and it will learn what to look for to identify different individuals over time, in much the same way that humans learn. Regardless of the end-use application, neural networks are typically created in TensorFlow and/or with Python programming skills.‎

    Neural networks are a fundamental concept to understand for jobs in artificial intelligence (AI) and deep learning. And, as the number of industries seeking to leverage these approaches continues to grow, so do career opportunities for professionals with expertise in neural networks. For instance, these skills could lead to jobs in healthcare creating tools to automate X-ray scans or assist in drug discovery, or a job in the automotive industry developing autonomous vehicles.

    Professionals dedicating their careers to cutting-edge work in neural networks typically pursue a master’s degree or even a doctorate in computer science. This high-level expertise in neural networks and artificial intelligence are in high demand; according to the Bureau of Labor Statistics, computer research scientists earn a median annual salary of $122,840 per year, and these jobs are projected to grow much faster than average over the next decade.‎

    Absolutely - in fact, Coursera is one of the best places to learn about neural networks, online or otherwise. You can take courses and Specializations spanning multiple courses in topics like neural networks, artificial intelligence, and deep learning from pioneers in the field - including deeplearning.ai and Stanford University. Coursera has also partnered with industry leaders such as IBM, Google Cloud, and Amazon Web Services to offer courses that can lead to professional certificates in applied AI and other areas. You can even learn about neural networks with hands-on Guided Projects, a way to learn on Coursera by completing step-by-step tutorials led by experienced instructors.‎

    Before starting to learn neural networks, it's important to have experience creating and using algorithms since neural networks run on complicated algorithms. You should also have fundamental math skills at least, but you'll be at a better advantage if you have knowledge of linear algebra, calculus, statistics, and probability. Being proficient at problem-solving is also important before starting to learn neural networks. An understanding of how the human brain processes information is helpful since artificial neural networks are patterned after how the brain works. You'll also benefit from having experience using any programming language, in particular Java, R, Python, or C++. This includes experience using these languages' libraries, which you'll access to apply the algorithms used in neural networks.‎

    People who are best suited for roles in neural networks are innovative, interested in technology, and have the ability to identify patterns in large amounts of data and draw conclusions from them. People who have a desire to make life and work easier for human beings through artificial technology are well suited for roles in neural networks too. Also, people who have good programming skills and data engineering skills like SQL, data analysis, ETL, and data visualization are likely well suited for roles in neural networks.‎

    If you are interested in the field of artificial intelligence, learning about neural networks is right for you. If your current or future position involves data analysis, pattern recognition, optimization, forecasting, or decision-making, you might also benefit from learning neural networks. Neural networks are also used in image recognition software, speech synthesis, self-driving vehicles, navigation systems, industrial robots, and algorithms for protecting information systems, so if you're interested in these technologies, learning neural networks may be helpful to you.‎

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

    When looking to enhance your workforce's skills in Neural Networks, 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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