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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

    • D
      S

      Multiple educators

      Machine Learning

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), Artificial Intelligence, NumPy, Predictive Modeling, Deep Learning, Reinforcement Learning, Random Forest Algorithm, Feature Engineering

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      34K reviews

      Beginner · Specialization · 1 - 3 Months

    • I

      Illinois Tech

      Deep Learning

      Skills you'll gain: Deep Learning, Generative AI, Image Analysis, Artificial Neural Networks, Keras (Neural Network Library), Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Tensorflow, Computer Vision, Natural Language Processing, Machine Learning

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      21 reviews

      Beginner · Course · 1 - 3 Months

    • M

      MathWorks

      Deep Learning for Computer Vision

      Skills you'll gain: Computer Vision, Anomaly Detection, Image Analysis, Matlab, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Application Deployment, PyTorch (Machine Learning Library), Data Visualization, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Predictive Modeling, Data Synthesis, Performance Tuning, Classification And Regression Tree (CART), Data Analysis, Data Processing, Medical Imaging

      4.9
      Rating, 4.9 out of 5 stars
      ·
      20 reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free
      Free
      Y

      Yonsei University

      Deep Learning for Business

      Skills you'll gain: Deep Learning, Tensorflow, Artificial Neural Networks, Business Strategy, Image Analysis, Natural Language Processing, Artificial Intelligence, Machine Learning, Reinforcement Learning, Unsupervised Learning, Supervised Learning

      4.4
      Rating, 4.4 out of 5 stars
      ·
      680 reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Data Ethics, Market Opportunities, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Team Building, Machine Learning, Strategic Thinking, Data Science, Needs Assessment, Deep Learning, Business Ethics, Artificial Neural Networks, Engineering Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      48K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Introduction to Artificial Intelligence (AI)

      Skills you'll gain: Large Language Modeling, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), ChatGPT, Deep Learning, Machine Learning, Artificial Neural Networks, Prompt Engineering, Governance, Automation, Business Transformation, Applied Machine Learning, Computer Vision, Ethical Standards And Conduct, Natural Language Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      IBM Generative AI Engineering

      Skills you'll gain: Prompt Engineering, Data Wrangling, Large Language Modeling, Unit Testing, Supervised Learning, Feature Engineering, Generative AI, Keras (Neural Network Library), Deep Learning, Artificial Intelligence, ChatGPT, Natural Language Processing, Data Cleansing, Jupyter, Data Analysis, Unsupervised Learning, Data Manipulation, PyTorch (Machine Learning Library), Data Import/Export, Exploratory Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      86K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • P

      Packt

      Deep Learning with Real-World Projects

      Skills you'll gain: Matplotlib, Data Visualization, Deep Learning, Linear Algebra, Artificial Neural Networks, NumPy, Image Analysis, Keras (Neural Network Library), Seaborn, Pandas (Python Package), Tensorflow, Machine Learning, Applied Machine Learning, Computer Vision, Scikit Learn (Machine Learning Library), Supervised Learning, Python Programming, Jupyter, Machine Learning Methods, Data Analysis

      4.2
      Rating, 4.2 out of 5 stars
      ·
      6 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Supervised Learning, Feature Engineering, Plotly, Interactive Data Visualization, Jupyter, Data Literacy, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Unsupervised Learning, Generative AI, Pandas (Python Package), Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      143K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Feature Engineering, Data Transformation, Jupyter, Data Science, Advanced Mathematics, Statistics, Machine Learning Algorithms, Machine Learning Methods, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New
      S

      Simplilearn

      AI & Deep Learning Concepts and Applications

      Skills you'll gain: Artificial Intelligence, Tensorflow, Machine Learning, Deep Learning, Applied Machine Learning, Artificial Neural Networks, Supervised Learning, Data Ethics, Algorithms, Unsupervised Learning, Emerging Technologies, Natural Language Processing, Digital Transformation, Reinforcement Learning, Data Processing, Business Ethics

      Beginner · Course · 1 - 4 Weeks

    • M

      MathWorks

      Deep Learning for Object Detection

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Matlab, Data Visualization, Applied Machine Learning, Machine Learning Methods, Data Analysis, Performance Tuning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      10 reviews

      Beginner · Course · 1 - 4 Weeks

    Deep Learning learners also search

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    1234…212

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

    • Machine Learning: DeepLearning.AI
    • Deep Learning: Illinois Tech
    • Deep Learning for Computer Vision: MathWorks
    • Deep Learning for Business: Yonsei University
    • AI For Everyone: DeepLearning.AI
    • Introduction to Artificial Intelligence (AI): IBM
    • IBM Generative AI Engineering: IBM
    • Deep Learning with Real-World Projects: Packt
    • IBM Data Science: IBM
    • Mathematics for Machine Learning: Imperial College London

    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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