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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

    • D

      DeepLearning.AI

      Sequences, Time Series and Prediction

      Skills you'll gain: Tensorflow, Time Series Analysis and Forecasting, Applied Machine Learning, Deep Learning, Predictive Modeling, Artificial Neural Networks, Forecasting, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.1K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Analyst

      Skills you'll gain: Data Storytelling, Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, SQL, Generative AI, Interactive Data Visualization, Exploratory Data Analysis, Data Cleansing, Big Data, Jupyter, Matplotlib, Data Analysis, Statistical Analysis, Pandas (Python Package), Data Manipulation, Excel Formulas, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      91K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      IBM AI Developer

      Skills you'll gain: Generative AI, Prompt Engineering, Large Language Modeling, Software Development Life Cycle, Unit Testing, ChatGPT, HTML and CSS, Development Environment, Web Design and Development, Jupyter, Hypertext Markup Language (HTML), Software Engineering, Artificial Intelligence, Cascading Style Sheets (CSS), Software Development Tools, Web Development, Application Deployment, Automation, Interviewing Skills, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      68K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New AI skills
      New AI skills
      G

      Google

      Google Cybersecurity

      Skills you'll gain: Threat Modeling, Network Security, Threat Management, Incident Response, Vulnerability Management, Computer Security Incident Management, Hardening, Intrusion Detection and Prevention, Cyber Threat Intelligence, Cyber Attacks, Cybersecurity, Network Protocols, Cloud Security, Vulnerability Assessments, Threat Detection, Bash (Scripting Language), Operating Systems, Security Controls, Debugging, Python Programming

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      50K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: New
      New
      S

      Simplilearn

      Deep Learning Frameworks and Neural Networks Simplified

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

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      IBM AI Foundations for Business

      Skills you'll gain: Large Language Modeling, Data Literacy, Data Mining, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Information Architecture, Strategic Decision-Making, Enterprise Architecture, Cloud Computing, Applied Machine Learning, Data Analysis, Data Science, Deep Learning, Digital Transformation, Data Strategy, Business Strategy, Business Process Automation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      93K reviews

      Beginner · Specialization · 1 - 3 Months

    • U

      University of Michigan

      Python for Everybody

      Skills you'll gain: Web Scraping, Data Processing, Relational Databases, JSON, Database Design, SQL, Network Protocols, Databases, Web Services, Restful API, Data Modeling, Programming Principles, Data Structures, Data Collection, Data Visualization Software, Data Manipulation, Computer Programming, Python Programming, Data Import/Export, Software Installation

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      277K reviews

      Beginner · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      AI for Medical Prognosis

      Skills you'll gain: Risk Modeling, Decision Tree Learning, Predictive Modeling, Feature Engineering, Applied Machine Learning, Random Forest Algorithm, Forecasting, Machine Learning, Statistical Methods, Statistical Analysis, Probability & Statistics, Data Analysis, Regression Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      786 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Statistical Inference, Data Processing, Data Access, Anomaly Detection, Statistical Analysis, Data Analysis, Data Cleansing, Data Manipulation, Machine Learning, Probability & Statistics, Data Transformation, Workflow Management, Scalability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.2K reviews

      Intermediate · Course · 1 - 3 Months

    • D

      Duke University

      MLOps | Machine Learning Operations

      Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Data Ethics, Application Deployment, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, Software Testing, Data Import/Export, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Docker (Software), Rust (Programming Language)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      448 reviews

      Advanced · Specialization · 3 - 6 Months

    • U

      University of Illinois Urbana-Champaign

      e-Learning Ecologies: Innovative Approaches to Teaching and Learning for the Digital Age

      Skills you'll gain: Differentiated Instruction, Collaborative Software, Education Software and Technology, Pedagogy, Learning Management Systems, Digital Transformation, Emerging Technologies, Innovation, Multimedia, Digital Communications

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.5K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      D

      Deep Teaching Solutions

      Aprendiendo a aprender: Poderosas herramientas mentales con las que podrás dominar temas difíciles (Learning How to Learn)

      Skills you'll gain: Learning Strategies, Critical Thinking and Problem Solving, Learning Theory, Time Management, Prioritization, Cognitive flexibility, Productivity, Growth Mindedness, Stress Management, Planning, Self-Awareness, Persistence

      4.9
      Rating, 4.9 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 3 Months

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    1…101112…425

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

    • Sequences, Time Series and Prediction: DeepLearning.AI
    • IBM Data Analyst: IBM
    • IBM AI Developer: IBM
    • Google Cybersecurity: Google
    • Deep Learning Frameworks and Neural Networks Simplified: Simplilearn
    • IBM AI Foundations for Business: IBM
    • Python for Everybody: University of Michigan
    • AI for Medical Prognosis : DeepLearning.AI
    • Exploratory Data Analysis for Machine Learning: IBM
    • MLOps | Machine Learning Operations: Duke 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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