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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

      University of Washington

      Data Manipulation at Scale: Systems and Algorithms

      Skills you'll gain: Big Data, Relational Databases, Database Systems, Dataflow, Data Science, Data Manipulation, Data Processing, NoSQL, Apache Spark, Analytics, Distributed Computing, Apache Hadoop, SQL, Data Analysis, Query Languages, Cloud Computing, Scalability, Graph Theory, Algorithms

      4.3
      Rating, 4.3 out of 5 stars
      ·
      767 reviews

      Mixed · Course · 1 - 3 Months

    • S

      Starweaver

      Business Analysis Mastery: Planning, Skills, and Perspective

      Skills you'll gain: Stakeholder Engagement, Business Analysis, Business Intelligence, Business Process, Business Planning, Business Process Management, Stakeholder Communications, Enterprise Architecture, Business Consulting, Requirements Analysis, Information Technology, Agile Methodology, Governance, Information Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      52 reviews

      Intermediate · Course · 1 - 4 Weeks

    • K

      Kennesaw State University

      The Define Phase for the 6 σ Black Belt

      Skills you'll gain: Six Sigma Methodology, Lean Six Sigma, Analysis, Process Improvement, Project Documentation, Quality Improvement, Process Capability, Customer Analysis, Continuous Quality Improvement (CQI), Project Management, Business Process

      4.4
      Rating, 4.4 out of 5 stars
      ·
      95 reviews

      Mixed · Course · 1 - 3 Months

    • M

      Michigan State University

      Planning: Principled, Proposing, Proofing, and Practicing to a Success Plan

      Skills you'll gain: Value Propositions, Business Planning, Business Modeling, Entrepreneurship, Business Development, Business Strategy, Product Development, Financial Forecasting, New Business Development, Financial Analysis, Customer Analysis, Innovation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      178 reviews

      Mixed · Course · 1 - 3 Months

    • B

      Board Infinity

      C# for .NET Developers

      Skills you'll gain: C# (Programming Language), ASP.NET, .NET Framework, Object Oriented Programming (OOP), Computer Programming, Web Applications, Programming Principles, Debugging, Development Environment

      4.1
      Rating, 4.1 out of 5 stars
      ·
      270 reviews

      Intermediate · Course · 1 - 4 Weeks

    • T

      Tecnológico de Monterrey

      Modelos de diseño instruccional para ambientes digitales

      Skills you'll gain: Education Software and Technology, Instructional Design, Learning Management Systems, Planning, Design Strategies, Quality Assurance, Virtual Environment, Innovation, Emerging Technologies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      393 reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Getting Started with Rstudio

      Skills you'll gain: Interactive Data Visualization, Data Visualization, Software Installation, Package and Software Management, R Programming, Integrated Development Environments, Cloud Development, Cloud Hosting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      141 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free
      Free
      S

      Sapienza University of Rome

      Paesaggi di Roma Antica. Archeologia e storia del Palatino.

      Skills you'll gain: Ancient History, Scientific Methods, Research, Research Methodologies, Investigation, Spatial Analysis, Art History, Geographic Information Systems, World History, Data Integration, Culture, Information Systems

      4.8
      Rating, 4.8 out of 5 stars
      ·
      144 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Introduction to Robotics with Webots

      Skills you'll gain: Robotic Process Automation, Data Mapping, Control Systems, Artificial Intelligence, Automation, Graph Theory, Algorithms, Real-Time Operating Systems, Mechanics, Simulation and Simulation Software, Global Positioning Systems, Simulations, Image Analysis, Computer Science, Data Structures, Programming Principles, Linear Algebra, Estimation

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      55 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California San Diego

      Finding Mutations in DNA and Proteins (Bioinformatics VI)

      Skills you'll gain: Bioinformatics, Markov Model, Molecular Biology, Machine Learning Methods, Computational Thinking, Algorithms, Computer Programming Tools, Data Structures, Probability & Statistics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      60 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      U

      Universitat Autònoma de Barcelona

      Primeros Auxilios Psicológicos (PAP). Edición especial COVID-19

      Skills you'll gain: Crisis Intervention, Stress Management, Psychosocial Assessments, Mental Health Diseases and Disorders, Personal Care, Psychological Evaluations, Community Mental Health Services, Caregiving, Community Outreach, Working With Children, Mindfulness, Adult Learning Principles, Interpersonal Communications

      4.7
      Rating, 4.7 out of 5 stars
      ·
      846 reviews

      Mixed · Course · 1 - 4 Weeks

    • M

      Microsoft

      Modern Data Warehouse Analytics in Microsoft Azure

      Skills you'll gain: Azure Synapse Analytics, Power BI, Databricks, Microsoft Azure, Database Administration, Cloud Services, Data Warehousing, Dashboard, Data Architecture, Apache Spark, Database Systems, Cloud Storage, Databases, Data Lakes, Business Intelligence, Big Data, Extract, Transform, Load, Data Visualization Software, Data Integration, Apache Hadoop

      4.5
      Rating, 4.5 out of 5 stars
      ·
      117 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Data Manipulation at Scale: Systems and Algorithms: University of Washington
    • Business Analysis Mastery: Planning, Skills, and Perspective: Starweaver
    • The Define Phase for the 6 σ Black Belt: Kennesaw State University
    • Planning: Principled, Proposing, Proofing, and Practicing to a Success Plan: Michigan State University
    • C# for .NET Developers: Board Infinity
    • Modelos de diseño instruccional para ambientes digitales : Tecnológico de Monterrey
    • Getting Started with Rstudio: Coursera Project Network
    • Paesaggi di Roma Antica. Archeologia e storia del Palatino.: Sapienza University of Rome
    • Introduction to Robotics with Webots: University of Colorado Boulder
    • Finding Mutations in DNA and Proteins (Bioinformatics VI): University of California San Diego

    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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