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    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 Trial
      Free Trial
      I

      IBM

      Introduction to Web Development with HTML, CSS, JavaScript

      Skills you'll gain: Hypertext Markup Language (HTML), HTML and CSS, Web Development, Web Development Tools, Cascading Style Sheets (CSS), Front-End Web Development, Web Design, Javascript, Interactive Design, Web Applications, Full-Stack Web Development, Back-End Web Development

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.3K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Web Application Technologies and Django

      Skills you'll gain: Django (Web Framework), HTML and CSS, Model View Controller, Application Deployment, Application Frameworks, Web Applications, Web Servers, SQL, Databases, Network Protocols, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Intermediate · Course · 1 - 3 Months

    • T

      The University of Edinburgh

      Understanding Obesity

      Skills you'll gain: Scientific Methods, Student-Centred Learning, Health Disparities, Research, Nutrition and Diet, Behavioral Health, Peer Review, Social Sciences, Psychology, Stress Management, Economics, Biology, Neurology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      845 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      C

      Case Western Reserve University

      Inspiring Leadership through Emotional Intelligence

      Skills you'll gain: Emotional Intelligence, Compassion, Coaching, Organizational Change, Personal Development, Leadership, Resilience, Empathy, Self-Awareness, Stress Management, Positivity, Change Management, Mindfulness, Relationship Building

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

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Virtual Teacher

      Skills you'll gain: Peer Review, Instructional Design, Education Software and Technology, Parent Communication, Instructional Strategies, Student Engagement, Learning Management Systems, Student Support and Services, Teaching, Course Development, Collaborative Software, Developing Training Materials, Curriculum Development, Curriculum Planning, Blended Learning, Virtual Environment, Data Management, Performance Testing, Augmented Reality, Web Content Accessibility Guidelines

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.3K reviews

      Beginner · Specialization · 3 - 6 Months

    • T

      The University of Edinburgh

      Chicken Behaviour and Welfare

      Skills you'll gain: Ethical Standards And Conduct, Behavior Management, Behavioral Health, Learning Theory, Human Learning, Health Assessment, Psychology

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.2K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to HTML, CSS, & JavaScript

      Skills you'll gain: HTML and CSS, Bootstrap (Front-End Framework), Web Design, Cascading Style Sheets (CSS), Front-End Web Development, Hypertext Markup Language (HTML), Web Development, Responsive Web Design, Javascript, Web Applications, Full-Stack Web Development, Scripting, Browser Compatibility, Application Programming Interface (API)

      4.5
      Rating, 4.5 out of 5 stars
      ·
      504 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Applied Social Network Analysis in Python

      Skills you'll gain: Network Analysis, Network Model, Graph Theory, Data Analysis, Pandas (Python Package), Applied Machine Learning, Matplotlib, Predictive Modeling, Simulations, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.7K reviews

      Intermediate · Course · 1 - 4 Weeks

    • P

      Pontificia Universidad Católica de Chile

      English for Interactions in the Workplace Intermediate Level

      Skills you'll gain: English Language, Language Competency, Vocabulary, Business Correspondence, Writing, Grammar, Business Communication, Oral Expression, Storytelling, Communication Strategies, Business Strategies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      284 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      MathWorks

      MathWorks Computer Vision Engineer

      Skills you'll gain: Computer Vision, Image Analysis, Anomaly Detection, Deep Learning, Applied Machine Learning, Artificial Neural Networks, Matlab, Application Deployment, PyTorch (Machine Learning Library), Machine Learning, Motion Graphics, Data Visualization, Automation, Data Mapping, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Spatial Data Analysis, Predictive Modeling, Visualization (Computer Graphics), Data Synthesis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      303 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      A

      Alberta Machine Intelligence Institute

      Machine Learning: Algorithms in the Real World

      Skills you'll gain: Supervised Learning, Feature Engineering, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Data Quality, Data Processing, MLOps (Machine Learning Operations), Jupyter, Data Validation, Machine Learning, Business Operations, Data Cleansing, Product Lifecycle Management, Ethical Standards And Conduct, Classification And Regression Tree (CART), Data Transformation, Operational Analysis, Verification And Validation, Business Strategy

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

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Virginia

      Managing an Agile Team

      Skills you'll gain: Agile Software Development, Agile Methodology, Agile Project Management, Team Performance Management, Team Management, Team Building, Team Leadership, Sprint Retrospectives, Backlogs, User Story, Kanban Principles, Sales Presentation, Lean Methodologies, Process Improvement, Selling Techniques, Prioritization, Discussion Facilitation, Decision Making

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.3K reviews

      Mixed · Course · 1 - 4 Weeks

    Deep Learning learners also search

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    1…565758…440

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

    • Introduction to Web Development with HTML, CSS, JavaScript: IBM
    • Web Application Technologies and Django: University of Michigan
    • Understanding Obesity: The University of Edinburgh
    • Inspiring Leadership through Emotional Intelligence: Case Western Reserve University
    • Virtual Teacher: University of California, Irvine
    • Chicken Behaviour and Welfare: The University of Edinburgh
    • Introduction to HTML, CSS, & JavaScript: IBM
    • Applied Social Network Analysis in Python: University of Michigan
    • English for Interactions in the Workplace Intermediate Level: Pontificia Universidad Católica de Chile
    • MathWorks Computer Vision Engineer: MathWorks

    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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