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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
      V

      Vanderbilt University

      Innovative Teaching with ChatGPT

      Skills you'll gain: ChatGPT, Creative Problem-Solving, AI Personalization, Innovation, Brainstorming, Game Design, Education Software and Technology, Prompt Engineering, Interactive Design

      4.8
      Rating, 4.8 out of 5 stars
      ·
      541 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      T

      Tableau Learning Partner

      Business Analysis Process

      Skills you'll gain: Requirements Elicitation, Business Analysis, Business Metrics, Key Performance Indicators (KPIs), Requirements Analysis, Business Requirements, Process Analysis, Stakeholder Management, Business Process Modeling, Tableau Software, Data Visualization, Business Consulting, Solution Delivery

      4.6
      Rating, 4.6 out of 5 stars
      ·
      124 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Toronto

      Visual Perception for Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Computer Graphics, Artificial Neural Networks, Visualization (Computer Graphics), Artificial Intelligence and Machine Learning (AI/ML), Python Programming, Linear Algebra

      4.7
      Rating, 4.7 out of 5 stars
      ·
      581 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Gemini for Google Workspace

      Skills you'll gain: Storytelling, Video Production, Workflow Management, Photo/Video Production and Technology, Prompt Engineering, Video Editing, Google Workspace, Generative AI, Productivity Software, Google Sheets, Gmail, Project Planning, Multimedia, Media Production, Spreadsheet Software, Operational Efficiency, Process Improvement, AI Personalization, Google Docs, Collaborative Software

      4.5
      Rating, 4.5 out of 5 stars
      ·
      143 reviews

      Beginner · Specialization · 1 - 3 Months

    • D

      Duke University

      The Brain and Space

      Skills you'll gain: Spatial Analysis, Neurology, Human Learning, Experimentation, Laboratory Research, Physics, Biology, General Science and Research, Magnetic Resonance Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      652 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University at Buffalo

      Computer Vision Basics

      Skills you'll gain: Computer Vision, Image Analysis, Computer Graphics, Visualization (Computer Graphics), Data Processing, Digital Design, Artificial Intelligence, Matlab, Linear Algebra, Algorithms, Calculus, Probability & Statistics

      4.2
      Rating, 4.2 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      GPU Programming

      Skills you'll gain: Artificial Neural Networks, Image Analysis, Event-Driven Programming, C and C++, Scalability, Deep Learning, Software Development, Machine Learning Methods, Performance Tuning, Linear Algebra, Distributed Computing, System Programming, Computer Graphics, Computer Hardware, Computer Vision, Numerical Analysis, Computer Architecture, Data Processing, Data Structures, Performance Testing

      Build toward a degree

      2.7
      Rating, 2.7 out of 5 stars
      ·
      151 reviews

      Intermediate · Specialization · 3 - 6 Months

    • É

      École Nationale des Ponts et Chaussées

      The hidden value – Lean in manufacturing and services

      Skills you'll gain: Lean Manufacturing, Lean Methodologies, Business Transformation, Continuous Improvement Process, Process Improvement, Manufacturing Operations, Service Improvement, Operational Efficiency, Value Engineering, Waste Minimization, Competitive Intelligence, Business Technologies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      818 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      AI and Public Health

      Skills you'll gain: Data Analysis, Jupyter, Exploratory Data Analysis, Data Ethics, Artificial Intelligence, Machine Learning, Predictive Modeling, Applied Machine Learning, Information Privacy, Deep Learning, Environmental Monitoring, Public Health

      4.8
      Rating, 4.8 out of 5 stars
      ·
      225 reviews

      Beginner · Course · 1 - 4 Weeks

    • C

      Coursera

      Use Generative AI as Your Thought Partner

      Skills you'll gain: Prompt Engineering, Generative AI, Leadership, Strategic Decision-Making, Business Strategy, Workforce Development, Business Ethics, Change Management, Large Language Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Smart Analytics, Machine Learning, and AI on Google Cloud

      Skills you'll gain: Google Cloud Platform, MLOps (Machine Learning Operations), Tensorflow, Unstructured Data, Applied Machine Learning, Data Pipelines, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Machine Learning, Jupyter, Natural Language Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Basic Image Classification with TensorFlow

      Skills you'll gain: Keras (Neural Network Library), Tensorflow, Image Analysis, Artificial Neural Networks, Deep Learning, Machine Learning Methods, Computer Vision

      4.6
      Rating, 4.6 out of 5 stars
      ·
      844 reviews

      Beginner · Guided Project · Less Than 2 Hours

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    1…686970…440

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

    • Innovative Teaching with ChatGPT: Vanderbilt University
    • Business Analysis Process: Tableau Learning Partner
    • Visual Perception for Self-Driving Cars: University of Toronto
    • Gemini for Google Workspace: Google Cloud
    • The Brain and Space: Duke University
    • Computer Vision Basics: University at Buffalo
    • GPU Programming: Johns Hopkins University
    • The hidden value – Lean in manufacturing and services: École Nationale des Ponts et Chaussées
    • AI and Public Health: DeepLearning.AI
    • Use Generative AI as Your Thought Partner: Coursera

    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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