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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

    • U

      University of London

      Machine Learning for All

      Skills you'll gain: Feature Engineering, Machine Learning, Data Processing, Artificial Intelligence, Supervised Learning, Data Analysis, Computer Vision, Data Collection

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Machine Learning Pipelines with Azure ML Studio

      Skills you'll gain: Applied Machine Learning, Classification And Regression Tree (CART), Predictive Modeling, Microsoft Azure, Machine Learning, Supervised Learning, Feature Engineering, Data Pipelines, Data Processing, Data Cleansing, Application Deployment

      4.5
      Rating, 4.5 out of 5 stars
      ·
      803 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Y

      Yonsei University

      First Step Korean

      Skills you'll gain: Language Competency, Grammar, Vocabulary, Literacy, Culture

      4.9
      Rating, 4.9 out of 5 stars
      ·
      53K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Machine Learning Introduction for Everyone

      Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Applied Machine Learning, Deep Learning, Supervised Learning, IBM Cloud, Predictive Modeling, Classification And Regression Tree (CART), Unsupervised Learning, Reinforcement Learning, Software Development Life Cycle

      4.5
      Rating, 4.5 out of 5 stars
      ·
      278 reviews

      Beginner · Course · 1 - 4 Weeks

    • A

      Amazon Web Services

      Introduction to Machine Learning on AWS

      Skills you'll gain: AWS SageMaker, Artificial Intelligence and Machine Learning (AI/ML), Amazon Web Services, Natural Language Processing, Artificial Intelligence, Image Analysis, Computer Vision, Text Mining, Machine Learning, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      138 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera Project Network

      Mining Quality Prediction Using Machine & Deep Learning

      Skills you'll gain: Regression Analysis, Predictive Modeling, Exploratory Data Analysis, Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Decision Tree Learning, Statistical Analysis, Data Analysis, Test Data, Artificial Neural Networks, Data Import/Export, Pandas (Python Package), Software Visualization

      4.8
      Rating, 4.8 out of 5 stars
      ·
      66 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • C

      Coursera Project Network

      Machine/Deep Learning for Mining Quality Prediction-Enhanced

      Skills you'll gain: Exploratory Data Analysis, Regression Analysis, Predictive Modeling, Applied Machine Learning, Data Manipulation, Data Analysis, Random Forest Algorithm, Decision Tree Learning, Machine Learning Algorithms, Data Visualization Software, Artificial Neural Networks, Deep Learning, Statistical Methods

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      I

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Jupyter, Automation, Web Scraping, Python Programming, Data Manipulation, Data Import/Export, Scripting, Data Structures, Data Processing, Data Collection, Application Programming Interface (API), Pandas (Python Package), Programming Principles, NumPy, Object Oriented Programming (OOP), Computer Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      41K reviews

      Beginner · Course · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      I

      IBM

      IBM Java Developer

      Skills you'll gain: Spring Framework, Prompt Engineering, HTML and CSS, Cloud-Native Computing, Software Development Life Cycle, Software Architecture, Hibernate (Java), Database Design, Docker (Software), Containerization, Git (Version Control System), GitHub, Software Design, Microservices, Object Oriented Programming (OOP), Large Language Modeling, Spring Boot, Object-Relational Mapping, Java Programming, Interviewing Skills

      4.6
      Rating, 4.6 out of 5 stars
      ·
      5.5K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      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
      ·
      73 reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      AI Foundations for Everyone

      Skills you'll gain: Prompt Engineering, Large Language Modeling, Generative AI, Artificial Intelligence, ChatGPT, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), OpenAI, Workflow Management, Deep Learning, Machine Learning, Artificial Neural Networks, Governance, Automation, Application Deployment, Business Transformation, IBM Cloud, Applied Machine Learning, Program Development, Computer Vision

      4.7
      Rating, 4.7 out of 5 stars
      ·
      27K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google

      Crash Course on Python

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

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

      Beginner · Course · 1 - 3 Months

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    1…456…214

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

    • Machine Learning for All: University of London
    • Machine Learning Pipelines with Azure ML Studio: Coursera Project Network
    • First Step Korean: Yonsei University
    • Machine Learning Introduction for Everyone: IBM
    • Introduction to Machine Learning on AWS: Amazon Web Services
    • Mining Quality Prediction Using Machine & Deep Learning: Coursera Project Network
    • Machine/Deep Learning for Mining Quality Prediction-Enhanced: Coursera Project Network
    • Python for Data Science, AI & Development: IBM
    • IBM Java Developer: IBM
    • An Introduction to Learning Experience Design (LXD): University of Michigan

    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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