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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

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Machine Learning Engineer

      Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), Apache Airflow, Cloud Infrastructure, CI/CD, Artificial Intelligence and Machine Learning (AI/ML), Data Pipelines, Dataflow, Systems Design, Cloud Platforms, Data Management, Data Governance, Hybrid Cloud Computing, Workflow Management, Application Deployment

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.8K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • G

      Google

      Put It to Work: Prepare for Cybersecurity Jobs

      Skills you'll gain: Incident Response, Computer Security Incident Management, Data Ethics, Cybersecurity, Security Management, Security Awareness, Incident Management, Cyber Security Assessment, Data Security, Personally Identifiable Information, Computer Security Awareness Training, Technical Communication

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

      Beginner · Course · 1 - 3 Months

    • G

      Google

      IT Security: Defense against the digital dark arts

      Skills you'll gain: Network Security, Information Systems Security, Cybersecurity, Application Security, Encryption, Security Controls, Cyber Attacks, Security Awareness, Data Security, Cryptography, Threat Modeling, Security Management, Network Administration, Computer Security Awareness Training, Information Assurance, Wireless Networks, Hardening, Firewall, Malware Protection, Authentications

      4.8
      Rating, 4.8 out of 5 stars
      ·
      25K reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Advanced Learning Algorithms

      Skills you'll gain: Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Artificial Intelligence, Supervised Learning, Deep Learning, Random Forest Algorithm, Artificial Neural Networks, Performance Tuning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      7.8K reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      Packt

      Building and Training Neural Networks with PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Deep Learning, Computer Vision, Classification And Regression Tree (CART), Predictive Modeling, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 3 Months

    • P

      Packt

      Deep Learning - Artificial Neural Networks with TensorFlow

      Skills you'll gain: Tensorflow, Artificial Neural Networks, Deep Learning, Keras (Neural Network Library), Image Analysis, Classification And Regression Tree (CART), Supervised Learning, Machine Learning, Regression Analysis, NumPy, Network Architecture, Probability & Statistics

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      S

      Stanford University

      Cryptography I

      Skills you'll gain: Cryptography, Data Encryption Standard, Encryption, Key Management, Advanced Encryption Standard (AES), Public Key Cryptography Standards (PKCS), Cybersecurity, Authentications, Data Integrity, Secure Coding, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      4.4K reviews

      Mixed · Course · 1 - 3 Months

    • P

      Packt

      Deep Learning - Recurrent Neural Networks with TensorFlow

      Skills you'll gain: Time Series Analysis and Forecasting, Natural Language Processing, Tensorflow, Text Mining, Forecasting, Image Analysis, Deep Learning, Artificial Neural Networks, Predictive Modeling, Data Processing

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud Network Engineer

      Skills you'll gain: Application Performance Management, Distributed Denial-Of-Service (DDoS) Attacks, Google Cloud Platform, Cloud Infrastructure, Load Balancing, System Monitoring, Prompt Engineering, Kubernetes, Network Performance Management, Network Monitoring, Cloud Computing Architecture, Containerization, Network Architecture, Network Security, Cloud Storage, Cloud Services, Identity and Access Management, Network Routing, Virtual Private Networks (VPN), Network Troubleshooting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      49K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM AI Foundations for Business

      Skills you'll gain: Large Language Modeling, Data Literacy, Data Mining, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Information Architecture, Strategic Decision-Making, Enterprise Architecture, Cloud Computing, Applied Machine Learning, Data Analysis, Data Science, Deep Learning, Digital Transformation, Data Strategy, Business Strategy, Business Process Automation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      93K reviews

      Beginner · Specialization · 1 - 3 Months

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud Security Engineer

      Skills you'll gain: Application Performance Management, Distributed Denial-Of-Service (DDoS) Attacks, Google Cloud Platform, Kubernetes, Cloud Infrastructure, Identity and Access Management, Data Loss Prevention, Load Balancing, System Monitoring, Prompt Engineering, Network Monitoring, Cloud Computing Architecture, Containerization, Network Architecture, Role-Based Access Control (RBAC), Network Security, OAuth, Network Routing, Cloud Security, Virtual Private Networks (VPN)

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      50K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free
      Free
      S

      Stanford University

      Social and Economic Networks: Models and Analysis

      Skills you'll gain: Network Analysis, Network Model, Social Sciences, Sociology, Economics, Policy, and Social Studies, Game Theory, Behavioral Economics, Graph Theory, Mathematical Modeling, Markov Model, Probability & Statistics, Probability Distribution, Bayesian Statistics, Simulations

      4.8
      Rating, 4.8 out of 5 stars
      ·
      754 reviews

      Advanced · Course · 1 - 3 Months

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

    • Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
    • Put It to Work: Prepare for Cybersecurity Jobs: Google
    • IT Security: Defense against the digital dark arts : Google
    • Advanced Learning Algorithms: DeepLearning.AI
    • Building and Training Neural Networks with PyTorch: Packt
    • Deep Learning - Artificial Neural Networks with TensorFlow: Packt
    • Cryptography I: Stanford University
    • Deep Learning - Recurrent Neural Networks with TensorFlow: Packt
    • Preparing for Google Cloud Certification: Cloud Network Engineer: Google Cloud
    • IBM AI Foundations for Business: IBM

    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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