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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 Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

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

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      Deep Learning for Healthcare

      Skills you'll gain: Deep Learning, Health Informatics, Generative AI, Image Analysis, Machine Learning, Keras (Neural Network Library), Applied Machine Learning, Health Care, Artificial Neural Networks, Supervised Learning, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, PyTorch (Machine Learning Library), Graph Theory, Computer Vision, Network Analysis, Machine Learning Software, Unsupervised Learning, Program Development

      3.1
      Rating, 3.1 out of 5 stars
      ·
      44 reviews

      Advanced · Specialization · 1 - 3 Months

    • U

      University of Washington

      Machine Learning

      Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Intermediate · Specialization · 3 - 6 Months

    • P

      Packt

      Keras Deep Learning & Generative Adversarial Networks (GAN)

      Skills you'll gain: Keras (Neural Network Library), Generative AI, PyTorch (Machine Learning Library), Image Analysis, Exploratory Data Analysis, Predictive Modeling, Deep Learning, Matplotlib, Artificial Intelligence, Pandas (Python Package), Python Programming, NumPy, Data Processing, Data Analysis, Artificial Neural Networks, Programming Principles, Classification And Regression Tree (CART), Regression Analysis, Data Manipulation, Tensorflow

      Intermediate · Specialization · 3 - 6 Months

    • G

      Google Cloud

      Introduction to Generative AI Learning Path

      Skills you'll gain: Large Language Modeling, Generative AI, Prompt Engineering, Data Ethics, Google Cloud Platform, Business Ethics, Application Development, Artificial Intelligence, Accountability, Compliance Training, Ethical Standards And Conduct, Artificial Intelligence and Machine Learning (AI/ML), Governance, Organizational Effectiveness, Machine Learning Methods, Decision Making, Corporate Strategy

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.1K reviews

      Intermediate · Specialization · 1 - 3 Months

    • I

      IBM

      IBM AI Developer

      Skills you'll gain: Prompt Engineering, HTML and CSS, Software Development Life Cycle, Software Architecture, Large Language Modeling, Unit Testing, Generative AI, Artificial Intelligence, Software Design, ChatGPT, Jupyter, Scrum (Software Development), Software Engineering, Agile Methodology, Bootstrap (Front-End Framework), Web Design, Application Deployment, Automation, Interviewing Skills, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      69K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      S

      Simplilearn

      AI ML with Deep Learning and Supervised Models

      Skills you'll gain: Supervised Learning, Data Modeling, Data Analysis, Regression Analysis, Unsupervised Learning, Artificial Intelligence, Classification And Regression Tree (CART), Machine Learning Algorithms, Tensorflow, Deep Learning, Keras (Neural Network Library), Machine Learning, Applied Machine Learning, Artificial Neural Networks, Predictive Modeling, Predictive Analytics, Data Ethics, Algorithms, Random Forest Algorithm, Computer Vision

      Beginner · Specialization · 1 - 3 Months

    • U

      University of Colorado Boulder

      Introduction to Deep Learning

      Skills you'll gain: Deep Learning, Unsupervised Learning, Keras (Neural Network Library), Computer Vision, Image Analysis, Artificial Neural Networks, Generative AI, Natural Language Processing, Python Programming

      Build toward a degree

      3.6
      Rating, 3.6 out of 5 stars
      ·
      31 reviews

      Intermediate · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Structuring Machine Learning Projects

      Skills you'll gain: Deep Learning, Applied Machine Learning, Machine Learning, Tensorflow, PyTorch (Machine Learning Library), Debugging, Artificial Intelligence, Keras (Neural Network Library), Data Quality, Performance Tuning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      50K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California, Irvine

      Learn English: Beginning Grammar

      Skills you'll gain: Grammar, Vocabulary, English Language, Language Learning, Language Competency

      4.9
      Rating, 4.9 out of 5 stars
      ·
      4.6K reviews

      Beginner · Specialization · 1 - 3 Months

    • D

      DeepLearning.AI

      Sequence Models

      Skills you'll gain: Natural Language Processing, Artificial Neural Networks, Tensorflow, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Deep Learning, Applied Machine Learning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      31K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Pennsylvania

      Deep Learning Essentials

      Skills you'll gain: PyTorch (Machine Learning Library), Deep Learning, Data Processing, Artificial Neural Networks, Computer Vision, Machine Learning Algorithms, Machine Learning, Artificial Intelligence

      Intermediate · Course · 1 - 4 Weeks

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

    • Reinforcement Learning: University of Alberta
    • Deep Learning for Healthcare: University of Illinois Urbana-Champaign
    • Machine Learning: University of Washington
    • Keras Deep Learning & Generative Adversarial Networks (GAN): Packt
    • Introduction to Generative AI Learning Path: Google Cloud
    • IBM AI Developer: IBM
    • AI ML with Deep Learning and Supervised Models: Simplilearn
    • Introduction to Deep Learning: University of Colorado Boulder
    • Structuring Machine Learning Projects: DeepLearning.AI
    • Learn English: Beginning Grammar: University of California, Irvine

    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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