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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

    • Status: Free
      Free
      C

      Commonwealth Education Trust

      Foundations of Teaching for Learning: Introduction

      Skills you'll gain: Creative Thinking, Classroom Management, Teaching, Adaptability, Education and Training, Pedagogy, Instructional Strategies, Professionalism, Instructing, Curriculum Planning, Student Engagement, Professional Development, Learning Theory, Collaboration

      4.6
      Rating, 4.6 out of 5 stars
      ·
      826 reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Michigan

      An Introduction to Learning Experience Design (LXD)

      Skills you'll gain: Multimedia, Learning Theory, Instructional Design, Web Content Accessibility Guidelines, Educational Materials, Learning Management Systems, Course Development, Design Thinking, Professional Development, Brainstorming, Education Software and Technology, Motivational Skills, Communication, Design, Student-Centred Learning, Creative Thinking, Diversity Equity and Inclusion Initiatives, User Centered Design, Technology Strategies, Quality Assurance

      4.8
      Rating, 4.8 out of 5 stars
      ·
      68 reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: New
      New
      V

      Vanderbilt University

      AI Agent Developer

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI Agents, Generative AI, OpenAI, Ideation, Verification And Validation, Data Validation, Data Presentation, Productivity, AI Personalization, Document Management, Python Programming, Agentic systems, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Personalized Service, Large Language Modeling, Risk Management Framework, Expense Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud DevOps Engineer

      Skills you'll gain: Site Reliability Engineering, Kubernetes, Application Performance Management, Google Cloud Platform, Cloud Infrastructure, System Monitoring, Prompt Engineering, Application Deployment, Identity and Access Management, DevOps, CI/CD, Containerization, Cloud Storage, Cloud Security, Cloud Services, Cloud Management, Service Level Agreement, Safety Culture, Event Monitoring, Culture Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      54K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free
      Free
      P

      Peking University

      Chinese for Beginners

      Skills you'll gain: Language Learning, Language Competency, Vocabulary, Oral Expression, Oral Comprehension

      4.8
      Rating, 4.8 out of 5 stars
      ·
      20K reviews

      Mixed · Course · 1 - 3 Months

    • I
      I

      Multiple educators

      IBM and ISC2 Cybersecurity Specialist

      Skills you'll gain: Network Security, Incident Response, Cloud Computing Architecture, Penetration Testing, Computer Security Incident Management, Cloud Services, Security Controls, Business Continuity, Disaster Recovery, Information Assurance, Peripheral Devices, Cybersecurity, Configuration Management, Computing Platforms, Cloud Security, Cloud Infrastructure, Network Troubleshooting, Cloud Platforms, Encryption, Data Storage

      4.7
      Rating, 4.7 out of 5 stars
      ·
      13K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Cloud Developer

      Skills you'll gain: Containerization, Cloud Applications, Google Cloud Platform, Cloud Infrastructure, Application Deployment, Docker (Software), Kubernetes, Application Development, CI/CD, Cloud Development, Microservices, Authentications, Serverless Computing, Identity and Access Management, Cloud Storage, Cloud Services, Virtual Machines, Generative AI, Cloud API, Prompt Engineering

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

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Generative AI Fundamentals

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, OpenAI, Data Ethics, Large Language Modeling, Leadership and Management, Business Leadership, Strategic Leadership, Business Ethics, Legal Risk, IBM Cloud, Google Cloud Platform, Artificial Intelligence, Program Development, Artificial Neural Networks, Business Development, Deep Learning, Content Creation, Business Transformation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.6K reviews

      Beginner · Specialization · 3 - 6 Months

    • G

      Google

      Crash Course on Python

      Skills you'll gain: Programming Principles, Scripting, Python Programming, Computer Programming, Computational Thinking, Algorithms, Data Structures, Integrated Development Environments, Debugging, Development Environment

      4.8
      Rating, 4.8 out of 5 stars
      ·
      39K reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google Cloud

      Google Cloud Database Engineer

      Skills you'll gain: Google Cloud Platform, Cloud Infrastructure, Application Deployment, Prompt Engineering, Kubernetes, Containerization, Database Architecture and Administration, MySQL, Cloud Computing Architecture, PostgreSQL, Identity and Access Management, Cloud Storage, Data Migration, Cloud Services, Database Administration, Cloud Management, Virtual Machines, Cloud Security, Cloud Applications, Operational Databases

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

      Intermediate · Specialization · 3 - 6 Months

    • Status: New
      New
      V

      Vanderbilt University

      AI Agents and Agentic AI in Python: Powered by Generative AI

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI Agents, OpenAI, Productivity, Python Programming, Agentic systems, Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Artificial Intelligence, Large Language Modeling, Creative Thinking, Ingenuity, Brainstorming, Software Development Tools, Application Development, Prototyping, Persona (User Experience), Business Logic, Automation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.8K reviews

      Beginner · Specialization · 3 - 6 Months

    • V

      Vanderbilt University

      Generative AI Automation

      Skills you'll gain: Prompt Engineering, ChatGPT, Ideation, Verification And Validation, Data Validation, Data Presentation, Productivity, Generative AI, Document Management, Data Synthesis, Image Analysis, Data Capture, Artificial Intelligence, OpenAI, Large Language Modeling, Data Analysis, Organizational Skills, Risk Management Framework, Computer Vision, Microsoft Excel

      4.8
      Rating, 4.8 out of 5 stars
      ·
      6.5K reviews

      Beginner · Specialization · 3 - 6 Months

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    1…141516…428

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

    • Foundations of Teaching for Learning: Introduction: Commonwealth Education Trust
    • An Introduction to Learning Experience Design (LXD): University of Michigan
    • AI Agent Developer: Vanderbilt University
    • Preparing for Google Cloud Certification: Cloud DevOps Engineer: Google Cloud
    • Chinese for Beginners: Peking University
    • IBM and ISC2 Cybersecurity Specialist: ISC2
    • Preparing for Google Cloud Certification: Cloud Developer: Google Cloud
    • Generative AI Fundamentals: IBM
    • Crash Course on Python: Google
    • Google Cloud Database Engineer: Google Cloud

    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 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.‎

    Yes, Coursera offers a variety of free courses across many topics, including deep learning. While you can access most course materials for free by auditing the courses, this does not include graded assignments or a completion certificate. For those looking to obtain a certificate to showcase their learning or enhance their professional profile, Coursera provides the option to purchase the course. Additionally, Coursera offers free trials or financial aid to learners who qualify, making certifications more accessible to everyone.‎

    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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