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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 Trial
      Free Trial
      G

      Google Cloud

      Responsible AI: Applying AI Principles with Google Cloud

      Skills you'll gain: Data Ethics, Business Ethics, Accountability, Compliance Training, Ethical Standards And Conduct, Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Governance, Decision Making, Corporate Strategy

      4.6
      Rating, 4.6 out of 5 stars
      ·
      598 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Fundamentals of Management

      Skills you'll gain: Goal Setting, Professional Networking, Business Management, Staff Management, Leadership and Management, Operations Management, People Management, Business Administration, Business Planning, Customer Service, Organizational Leadership, Organizational Strategy, Leadership, Change Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.9K reviews

      Mixed · Course · 1 - 4 Weeks

    • S

      Stanford University

      Stanford's Short Course on Breastfeeding

      Skills you'll gain: Child Health, Maternal Health, Preventative Care, Pediatrics, Nutrition Education, Nutrition and Diet, Community Health

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Introduction to Statistics & Data Analysis in Public Health

      Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, Statistical Software, R Programming, Statistics, Public Health, Descriptive Statistics, Probability Distribution, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Social Work Practice: Advocating Social Justice and Change

      Skills you'll gain: Social Work, Community and Social Work, Social Justice, Advocacy, Cultural Sensitivity, Diversity Awareness, Research, Systems Thinking, Human Development, Policy Development, Ethical Standards And Conduct, Interpersonal Communications

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      413 reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      Pontificia Universidad Católica de Chile

      Hacia una práctica constructivista en el aula

      Skills you'll gain: Education Software and Technology, Teaching, Pedagogy, Cultural Diversity, Instructional Design, Student-Centred Learning, Instructional Strategies, Human Learning, Curriculum Planning, Learning Theory, Student Engagement, Interpersonal Communications

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.6K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Career Discovery

      Skills you'll gain: Professional Networking, LinkedIn, Mentorship, Professional Development, Interviewing Skills, Social Media, Relationship Building, Social Media Strategy, Planning, Strategic Communication, Communication, Social Skills, Adaptability, Collaboration, Business Research, Negotiation, Leadership Development, Professionalism, Lifelong Learning, Goal Setting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of Minnesota

      Recommender Systems

      Skills you'll gain: AI Personalization, Machine Learning Algorithms, Taxonomy, Applied Machine Learning, Machine Learning, Dimensionality Reduction, Performance Metric, Spreadsheet Software, Data Collection, Performance Measurement, Benchmarking, Usability Testing, Exploratory Data Analysis, A/B Testing, Analysis, Artificial Intelligence and Machine Learning (AI/ML), Technical Design, Algorithms, System Design and Implementation, Predictive Modeling

      4.3
      Rating, 4.3 out of 5 stars
      ·
      823 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      K

      Keller Williams

      Keller Williams Real Estate Agent

      Skills you'll gain: Lead Generation, Administrative Support, Real Estate, Office Management, Real Estate Sales, Value Propositions, Property and Real Estate, Sales Process, Customer Relationship Building, Real Estate Transactions, Customer Acquisition Management, Sales Management, Organizational Skills, Sales Prospecting, Sales Presentation, Showrooms, Prospecting and Qualification, Closing (Sales), Branding, Prioritization

      4.7
      Rating, 4.7 out of 5 stars
      ·
      156 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Y

      Yale University

      Health Behavior Change: From Evidence to Action

      Skills you'll gain: Public Health and Disease Prevention, Nutrition and Diet, Public Health, Behavioral Health, Mental Health, Mental and Behavioral Health, Behavioral Economics, Patient Education And Counseling, Program Evaluation, Preventative Care

      4.8
      Rating, 4.8 out of 5 stars
      ·
      453 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      MedCerts

      Medical Billing and Coding Essentials

      Skills you'll gain: Revenue Cycle Management, Medical Billing and Coding, ICD Coding (ICD-9/ICD-10), Electronic Medical Record, Copayment Collection and Processing, Health Care Procedure and Regulation, Medical Privacy, Healthcare Industry Knowledge, Patient Registration, Health Information Management, Medicare, Medical Terminology, Data Security

      4.7
      Rating, 4.7 out of 5 stars
      ·
      523 reviews

      Beginner · Course · 1 - 4 Weeks

    • E

      Eindhoven University of Technology

      Improving your statistical inferences

      Skills you'll gain: Statistical Inference, Scientific Methods, Statistical Hypothesis Testing, Quantitative Research, Bayesian Statistics, Statistical Analysis, Statistical Methods, Probability & Statistics, Sample Size Determination, Research, Data Collection, R Programming, Data Sharing, Probability Distribution

      4.9
      Rating, 4.9 out of 5 stars
      ·
      796 reviews

      Intermediate · Course · 1 - 3 Months

    Deep Learning learners also search

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

    • Responsible AI: Applying AI Principles with Google Cloud: Google Cloud
    • Fundamentals of Management: University of California, Irvine
    • Stanford's Short Course on Breastfeeding: Stanford University
    • Introduction to Statistics & Data Analysis in Public Health: Imperial College London
    • Social Work Practice: Advocating Social Justice and Change: University of Michigan
    • Hacia una práctica constructivista en el aula: Pontificia Universidad Católica de Chile
    • Career Discovery: Kennesaw State University
    • Recommender Systems: University of Minnesota
    • Keller Williams Real Estate Agent: Keller Williams
    • Health Behavior Change: From Evidence to Action: Yale 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 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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