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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
      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: Free
      Free
      A

      Amazon Web Services

      Fundamentals of Machine Learning and Artificial Intelligence

      Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, Artificial Intelligence, AWS SageMaker, Amazon Web Services, Applied Machine Learning, Machine Learning, Digital Transformation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      515 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      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

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

      Illinois Tech

      Data Analytics and Deep Learning

      Skills you'll gain: NoSQL, Machine Learning Algorithms, Big Data, Apache Hadoop, Deep Learning, Statistical Analysis, Data Visualization, Data Analysis, Exploratory Data Analysis, Apache Spark, Data Presentation, Generative AI, Data Infrastructure, Data Cleansing, Real Time Data, Apache Kafka, Image Analysis, Artificial Neural Networks, Keras (Neural Network Library), Artificial Intelligence and Machine Learning (AI/ML)

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      25 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      I

      IBM

      IBM Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Visualization, Predictive Modeling, Generative AI, SQL, Interactive Data Visualization, Exploratory Data Analysis, Data Wrangling, Data Analysis, Jupyter, Big Data, Matplotlib, Statistical Analysis, Pandas (Python Package), IBM Cognos Analytics, Excel Formulas, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      92K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      D

      Duke University

      MLOps | Machine Learning Operations

      Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Data Ethics, Application Deployment, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, Software Testing, Data Import/Export, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Docker (Software), Rust (Programming Language)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      465 reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      M

      MathWorks

      Introduction to Deep Learning for Computer Vision

      Skills you'll gain: Computer Vision, Image Analysis, Matlab, Artificial Neural Networks, Deep Learning, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Machine Learning Methods, Performance Tuning, Classification And Regression Tree (CART), Data Processing

      4.9
      Rating, 4.9 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      N
      G
      N
      G

      Multiple educators

      Machine Learning for Trading

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Machine Learning, Google Cloud Platform, Applied Machine Learning, Financial Trading, Reinforcement Learning, Supervised Learning, Data Pipelines, Time Series Analysis and Forecasting, Statistical Machine Learning, Technical Analysis, Deep Learning, Portfolio Management, Machine Learning Methods, Artificial Neural Networks, Market Trend, Securities Trading, Artificial Intelligence and Machine Learning (AI/ML), Financial Market

      3.9
      Rating, 3.9 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Developer

      Skills you'll gain: Prompt Engineering, Software Development Life Cycle, HTML and CSS, Large Language Modeling, Software Architecture, Development Environment, Flask (Web Framework), Generative AI, Unit Testing, ChatGPT, Jupyter, Artificial Intelligence, Bootstrap (Front-End Framework), Software Design, Software Development Tools, OpenAI, Front-End Web Development, Python Programming, Interviewing Skills, Engineering Software

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      70K reviews

      Beginner · Professional Certificate · 3 - 6 Months

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

    • Mathematics for Machine Learning: Imperial College London
    • Fundamentals of Machine Learning and Artificial Intelligence: Amazon Web Services
    • Structuring Machine Learning Projects: DeepLearning.AI
    • Data Analytics and Deep Learning: Illinois Tech
    • IBM Data Analyst: IBM
    • Deep Learning Essentials: University of Pennsylvania
    • MLOps | Machine Learning Operations: Duke University
    • Introduction to Deep Learning for Computer Vision: MathWorks
    • Machine Learning for Trading: New York Institute of Finance
    • Sequence Models: DeepLearning.AI

    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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