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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

      Universidad de los Andes

      Modelos predictivos con aprendizaje automático

      Skills you'll gain: Data Ethics, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Regression Analysis, Applied Machine Learning, Predictive Analytics, Scikit Learn (Machine Learning Library), Machine Learning, Decision Tree Learning, Python Programming, Unsupervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      73 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Minnesota

      Nearest Neighbor Collaborative Filtering

      Skills you'll gain: AI Personalization, Machine Learning Algorithms, Predictive Modeling, Applied Machine Learning, Data Mining, Algorithms

      4.3
      Rating, 4.3 out of 5 stars
      ·
      304 reviews

      Mixed · Course · 1 - 3 Months

    • S

      Starweaver

      Introduction to Automotive Embedded Systems

      Skills you'll gain: Embedded Systems, Electronic Systems, Cybersecurity, Automation, Electronics, Control Systems, Internet Of Things, Software Development, Real-Time Operating Systems, Systems Integration, Artificial Intelligence

      4.4
      Rating, 4.4 out of 5 stars
      ·
      24 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Creating Interactive Learning Videos with Edpuzzle

      Skills you'll gain: Education Software and Technology

      4.7
      Rating, 4.7 out of 5 stars
      ·
      177 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • J

      Johns Hopkins University

      Teaching Writing

      Skills you'll gain: Lesson Planning, Peer Review, Editing, Student-Centred Learning, Writing, Syllabus Development, Student Engagement, Writing and Editing, Instructional Strategies, Literacy, Teaching, Developing Training Materials, Storytelling, Empowerment, Differentiated Instruction, Course Development, Mentorship, Language Competency, Creativity, Constructive Feedback

      4.5
      Rating, 4.5 out of 5 stars
      ·
      51 reviews

      Beginner · Specialization · 3 - 6 Months

    • A

      Arm

      Introduction to Microprocessors

      Skills you'll gain: Microarchitecture, Computer Architecture, Hardware Architecture, Computer Hardware, Computer Systems, System Programming, Embedded Systems, Data Storage, Computer Programming, C (Programming Language)

      4.7
      Rating, 4.7 out of 5 stars
      ·
      43 reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Adobe Photoshop for Beginners: Generative AI Images

      Skills you'll gain: Photo Editing, Adobe Photoshop, Generative AI, Adobe Creative Cloud, Data Import/Export, Editing, Graphic Design

      4.7
      Rating, 4.7 out of 5 stars
      ·
      30 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • S

      Scrimba

      Learn JavaScript

      Skills you'll gain: JSON, Event-Driven Programming, Javascript, Mobile Development, Data Structures, Object Oriented Programming (OOP), Web Applications, Programming Principles, Data Storage Technologies, Data Storage, User Interface (UI), Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      137 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Create a no-code responsive website with Webflow

      Skills you'll gain: Responsive Web Design, Content Management, Web Design and Development, Web Content

      4.4
      Rating, 4.4 out of 5 stars
      ·
      121 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • K

      Kennesaw State University

      The Measure Phase for the 6 σ Black Belt

      Skills you'll gain: Six Sigma Methodology, Lean Methodologies, Process Capability, Lean Six Sigma, Data Collection, Sampling (Statistics), Probability Distribution, Process Analysis, Descriptive Statistics, Performance Measurement, Quality Improvement, Continuous Quality Improvement (CQI), Statistics, Probability, Systems Of Measurement, Statistical Analysis

      4.3
      Rating, 4.3 out of 5 stars
      ·
      51 reviews

      Mixed · Course · 1 - 3 Months

    • P

      Packt

      The Complete Quantum Computing Course for Beginners

      Skills you'll gain: Object Oriented Programming (OOP), Python Programming, Data Structures, Data Manipulation, Computer Programming, Applied Mathematics, Algorithms, Mathematics and Mathematical Modeling, Data Processing, Scripting, Linear Algebra, Probability, Mathematical Modeling, IBM Cloud, Computer Science, Algebra, Software Installation, Probability & Statistics, Theoretical Computer Science, Artificial Intelligence and Machine Learning (AI/ML)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      29 reviews

      Beginner · Specialization · 3 - 6 Months

    • C

      Codio

      Tools for Security Specialists

      Skills you'll gain: Computer Security Incident Management, Endpoint Security, Incident Management, Incident Response, ISO/IEC 27001, Security Management, Vulnerability Scanning, Risk Management, Personally Identifiable Information, Vulnerability Assessments, Linux, Linux Administration, Infrastructure Security, Network Security, Authorization (Computing), Threat Management, Security Strategy, Enterprise Risk Management (ERM), Business Risk Management, Cyber Security Policies

      4.8
      Rating, 4.8 out of 5 stars
      ·
      49 reviews

      Beginner · Specialization · 1 - 3 Months

    Deep Learning learners also search

    Beginner Deep Learning
    Deep Learning Projects
    Advanced Deep Learning
    Machine Learning
    Applied Machine Learning
    Beginner Machine Learning
    Machine Learning Projects
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    1…146147148…431

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

    • Modelos predictivos con aprendizaje automático: Universidad de los Andes
    • Nearest Neighbor Collaborative Filtering: University of Minnesota
    • Introduction to Automotive Embedded Systems: Starweaver
    • Creating Interactive Learning Videos with Edpuzzle: Coursera Project Network
    • Teaching Writing: Johns Hopkins University
    • Introduction to Microprocessors: Arm
    • Adobe Photoshop for Beginners: Generative AI Images: Coursera Project Network
    • Learn JavaScript: Scrimba
    • Create a no-code responsive website with Webflow: Coursera Project Network
    • The Measure Phase for the 6 σ Black Belt: Kennesaw State University

    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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