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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: New
      New
      V

      Vanderbilt University

      AI Agents and Agentic AI with Python & Generative AI

      Skills you'll gain: Generative AI Agents, Python Programming, Agentic systems, Generative AI, Artificial Intelligence, OpenAI, ChatGPT, Prompt Engineering, Software Development Tools, Application Development, Prototyping, Automation, Large Language Modeling, Interoperability, Systems Integration, Software Documentation, Design Strategies, File Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      62 reviews

      Beginner · Course · 1 - 3 Months

    • N

      Novartis

      Fundamentals of Good Clinical Practice: Recruitment & Trial

      Skills you'll gain: Clinical Research, Clinical Trials, Healthcare Ethics, Record Keeping, Patient Education And Counseling, Regulatory Compliance, Patient Safety

      4.8
      Rating, 4.8 out of 5 stars
      ·
      126 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Introduction to Graph Theory

      Skills you'll gain: Graph Theory, Combinatorics, Network Analysis, Data Structures, Network Routing, Algorithms, Mathematical Theory & Analysis, Theoretical Computer Science, Program Development

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      AI and Climate Change

      Skills you'll gain: Image Analysis, Environmental Monitoring, Artificial Intelligence, Deep Learning, Data Processing, Forecasting, Machine Learning, Computer Vision, Environmental Science, Exploratory Data Analysis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      118 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Generative AI: Foundation Models and Platforms

      Skills you'll gain: Generative AI, OpenAI, Large Language Modeling, Prompt Engineering, IBM Cloud, Google Cloud Platform, Artificial Intelligence, Artificial Neural Networks, Deep Learning, Natural Language Processing, Application Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      200 reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      Politecnico di Milano

      Designing Learning Innovation

      Skills you'll gain: Pedagogy, Course Development, Instructional and Curriculum Design, Instructional Strategies, Student Engagement, Educational Materials, Innovation, Curriculum Planning, Student-Centred Learning, Learning Theory, Open Source Technology, Learning Strategies

      4.9
      Rating, 4.9 out of 5 stars
      ·
      676 reviews

      Beginner · Course · 1 - 3 Months

    • V

      VMware

      Networking and Security Architecture with VMware NSX

      Skills you'll gain: VMware ESX Servers, Virtualization, Network Architecture, Disaster Recovery, Software-Defined Networking, Network Security, Computer Networking, Virtual Machines, IT Automation, Firewall, Information Technology Operations, Cloud Management

      4.7
      Rating, 4.7 out of 5 stars
      ·
      462 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Learning Technologies Foundations and Applications

      Skills you'll gain: Education Software and Technology, Learning Theory, Instructional Design, Learning Management Systems, Technology Solutions, Disabilities, Human Computer Interaction, Technical Consulting, Technology Strategies, Emerging Technologies, Information Technology, Electronic Media, Innovation, Gerontology

      4.5
      Rating, 4.5 out of 5 stars
      ·
      185 reviews

      Mixed · Course · 1 - 3 Months

    • I

      IBM

      SQL: A Practical Introduction for Querying Databases

      Skills you'll gain: SQL, Stored Procedure, Relational Databases, MySQL, Microsoft SQL Servers, Query Languages, Database Management, Databases, Cloud Management, IBM DB2, Data Manipulation, Data Analysis, Transaction Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      580 reviews

      Beginner · Course · 1 - 3 Months

    • A

      Automatic Data Processing, Inc. (ADP)

      The Payroll Cycle

      Skills you'll gain: Payroll, Payroll Processing, Payroll Systems, Payroll Administration, Payroll Reporting, Data Entry, Employee Onboarding, Compensation Management, Record Keeping, Auditing, Tax Compliance, Timelines, Data Security

      4.7
      Rating, 4.7 out of 5 stars
      ·
      61 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Sports Performance Analytics

      Skills you'll gain: Forecasting, Statistical Methods, Regression Analysis, Data Cleansing, Scikit Learn (Machine Learning Library), Supervised Learning, Data Processing, Statistical Hypothesis Testing, Correlation Analysis, Predictive Analytics, Predictive Modeling, Matplotlib, Applied Machine Learning, Kinesiology, Injury Prevention, Statistical Machine Learning, Analytics, Data Analysis, Statistical Analysis, Probability & Statistics

      4.5
      Rating, 4.5 out of 5 stars
      ·
      255 reviews

      Intermediate · Specialization · 3 - 6 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

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

    • AI Agents and Agentic AI with Python & Generative AI: Vanderbilt University
    • Fundamentals of Good Clinical Practice: Recruitment & Trial: Novartis
    • Introduction to Graph Theory: University of California San Diego
    • AI and Climate Change: DeepLearning.AI
    • Generative AI: Foundation Models and Platforms: IBM
    • Designing Learning Innovation: Politecnico di Milano
    • Networking and Security Architecture with VMware NSX: VMware
    • Learning Technologies Foundations and Applications: University of Illinois Urbana-Champaign
    • SQL: A Practical Introduction for Querying Databases: IBM
    • The Payroll Cycle: Automatic Data Processing, Inc. (ADP)

    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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