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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

    • M

      MathWorks

      Computer Vision for Engineering and Science

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Matlab, Applied Machine Learning, Machine Learning, Motion Graphics, Data Mapping, Artificial Intelligence and Machine Learning (AI/ML), Visualization (Computer Graphics), Geospatial Information and Technology, Feature Engineering, Medical Imaging, Machine Learning Algorithms, Data Validation, Geometric Dimensioning And Tolerancing, Performance Testing, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      85 reviews

      Intermediate · Specialization · 1 - 3 Months

    • W

      Wesleyan University

      Data Management and Visualization

      Skills you'll gain: Descriptive Statistics, Data Manipulation, Data Presentation, Data Management, Data Literacy, Graphing, SAS (Software), Peer Review, Data Analysis, Statistics, Research Reports, Exploratory Data Analysis, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      937 reviews

      Mixed · Course · 1 - 3 Months

    • N

      New York University

      Fundamentals of Machine Learning in Finance

      Skills you'll gain: Supervised Learning, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Machine Learning Algorithms, Decision Tree Learning, Machine Learning, Predictive Modeling, Financial Trading, Financial Market, Reinforcement Learning, Scikit Learn (Machine Learning Library), Correlation Analysis, Exploratory Data Analysis, Portfolio Management, Python Programming, Artificial Neural Networks, Jupyter

      3.7
      Rating, 3.7 out of 5 stars
      ·
      338 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      COBOL Programming with VSCode

      Skills you'll gain: COBOL (Programming Language), Integrated Development Environments, IBM Cloud, Mainframe Computing, Programming Principles, Computer Programming Tools, Development Environment, Data Management, Debugging, File Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      185 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      S

      Sapienza University of Rome

      Recovering the Humankind's Past and Saving the Universal Heritage

      Skills you'll gain: Ancient History, 3D Modeling, Scientific Methods, Anthropology, Investigation, Data Modeling, Cultural Diversity, Art History, Research, Timelines, Data Management, Data Collection

      4.4
      Rating, 4.4 out of 5 stars
      ·
      300 reviews

      Mixed · Course · 1 - 3 Months

    • A

      Amazon Web Services

      Migrating to the AWS Cloud

      Skills you'll gain: Amazon Web Services, Data Migration, Cloud Management, Cloud Infrastructure, Cloud Security, Data Import/Export, Cloud Computing, Cloud Applications, Infrastructure Architecture

      4.5
      Rating, 4.5 out of 5 stars
      ·
      233 reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      Meta

      Ingeniero en base de datos de Meta

      Skills you'll gain: MySQL, MySQL Workbench, Database Management, Relational Databases, Data Modeling, SQL, Database Design, Version Control, Data Warehousing, Database Management Systems, Database Theory, Unix Commands, Extract, Transform, Load, Databases, Git (Version Control System), Django (Web Framework), Algorithms, Test Driven Development (TDD), Unit Testing, Pseudocode

      4.8
      Rating, 4.8 out of 5 stars
      ·
      312 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • K

      KodeKloud

      DevOps Mastery

      Skills you'll gain: Jenkins, Terraform, Infrastructure as Code (IaC), Linux Administration, Kubernetes, Docker (Software), CI/CD, Version Control, Ansible, Continuous Integration, Microservices, Git (Version Control System), Devops Tools, GitHub, General Networking, Containerization, Systems Administration, IT Automation, Python Programming, Programming Principles

      4.6
      Rating, 4.6 out of 5 stars
      ·
      137 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free
      Free
      T

      The Hong Kong University of Science and Technology

      Understanding Modern Physics I: Relativity and Cosmology

      Skills you'll gain: Physics, Calculus, Mechanics, Physical Science, Advanced Mathematics, Energy and Utilities, Mathematical Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      154 reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Data Pipelines with TensorFlow Data Services

      Skills you'll gain: Extract, Transform, Load, Data Pipelines, Data Import/Export, Tensorflow, Data Processing, MLOps (Machine Learning Operations), Feature Engineering, Data Transformation, Data Sharing, Data Management, Data Validation, Performance Tuning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      533 reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      Meta

      Statistics Foundations

      Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Data Modeling, Statistics, Probability & Statistics, Statistical Analysis, Statistical Methods, Data Analysis Software, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Quantitative Research, Analytics, Descriptive Analytics, Time Series Analysis and Forecasting

      4.7
      Rating, 4.7 out of 5 stars
      ·
      326 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Designing Effective Science Communication

      Skills you'll gain: Oral Expression, Human Learning, Education Software and Technology, Technical Communication, Education and Training, Writing, Learning Theory, Community Outreach, Pedagogy, Research, Technical Writing, Scientific Methods, Media and Communications, Science and Research, Persuasive Communication, Interviewing Skills, Photography, Infographics, Storytelling, Psychology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      117 reviews

      Beginner · Course · 1 - 3 Months

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

    • Computer Vision for Engineering and Science: MathWorks
    • Data Management and Visualization: Wesleyan University
    • Fundamentals of Machine Learning in Finance: New York University
    • COBOL Programming with VSCode: IBM
    • Recovering the Humankind's Past and Saving the Universal Heritage: Sapienza University of Rome
    • Migrating to the AWS Cloud: Amazon Web Services
    • Ingeniero en base de datos de Meta: Meta
    • DevOps Mastery: KodeKloud
    • Understanding Modern Physics I: Relativity and Cosmology: The Hong Kong University of Science and Technology
    • Data Pipelines with TensorFlow Data Services: 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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