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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

    • I

      IBM

      Cybersecurity Architecture

      Skills you'll gain: Identity and Access Management, Endpoint Security, Network Security, Cybersecurity, Threat Detection, Cyber Attacks, Data Security, Cyber Security Strategy, Secure Coding, Firewall, Application Security, Authentications, Infrastructure Security, Security Controls, Authorization (Computing), Security Information and Event Management (SIEM), Data Governance, Security Testing, Virtual Private Networks (VPN)

      4.9
      Rating, 4.9 out of 5 stars
      ·
      102 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      M

      Microsoft

      Data Analysis and Visualization with Python

      Skills you'll gain: Generative AI, Matplotlib, Plotly, Data Ethics, Data Cleansing, Data Manipulation, Exploratory Data Analysis, Pandas (Python Package), Data Transformation, Interactive Data Visualization, Data Visualization Software, Data Storytelling, Data Analysis, Scikit Learn (Machine Learning Library), Jupyter, Python Programming, Machine Learning

      4
      Rating, 4 out of 5 stars
      ·
      25 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of California, Irvine

      Presentations: Speaking so that People Listen

      Skills you'll gain: Verbal Communication Skills, Presentations, Public Speaking, Non-Verbal Communication, Communication, Constructive Feedback, Stress Management, Organizational Skills, Planning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      376 reviews

      Intermediate · Course · 1 - 4 Weeks

    • A

      Amazon

      Data Structures and Algorithms

      Skills you'll gain: JUnit, Test Driven Development (TDD), Version Control, Git (Version Control System), GitHub, Performance Tuning, Unit Testing, Data Structures, Development Testing, Algorithms, Program Development, Software Testing, Java, Computer Programming, Programming Principles, Debugging, Scalability

      4.5
      Rating, 4.5 out of 5 stars
      ·
      25 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      N

      National Taiwan University

      用 Python 做商管程式設計(二)(Programming for Business Computing in Python (2))

      Skills you'll gain: Data Structures, Data Visualization Software, Financial Data, Financial Analysis, Data Analysis, Debugging, Programming Principles, Data Processing, Python Programming, Data Manipulation, File Management, Scripting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      261 reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      Duke University

      Spark, Hadoop, and Snowflake for Data Engineering

      Skills you'll gain: PySpark, Snowflake Schema, Databricks, Data Pipelines, Apache Spark, MLOps (Machine Learning Operations), Apache Hadoop, Big Data, Data Warehousing, Data Quality, Data Integration, Data Processing, DevOps, Data Transformation, SQL

      3.8
      Rating, 3.8 out of 5 stars
      ·
      51 reviews

      Advanced · Course · 1 - 4 Weeks

    • R

      Rice University

      An Introduction to Interactive Programming in Python (Part 2)

      Skills you'll gain: Application Development, Object Oriented Programming (OOP), Event-Driven Programming, Interactive Design, User Interface (UI), Program Development, Animations, Game Design, Programming Principles, Python Programming, Computer Programming, Data Structures, Debugging

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Learning Experience Design: Theories and Frameworks

      Skills you'll gain: Learning Theory, Instructional Design, Course Development, Brainstorming, Motivational Skills, Communication, Design, Student-Centred Learning, Creative Thinking

      4.9
      Rating, 4.9 out of 5 stars
      ·
      24 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free
      U

      Universidad Nacional Autónoma de México

      Cursos en línea: modelo para armar

      Skills you'll gain: Learning Management Systems, Education Software and Technology, Organizational Skills, End User Training and Support, Interactive Design, Content Management, Quality Assurance, Digital Communications

      4.9
      Rating, 4.9 out of 5 stars
      ·
      240 reviews

      Beginner · Course · 1 - 4 Weeks

    • P

      Politecnico di Milano

      Artificial Intelligence: An Overview

      Skills you'll gain: Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Computer Science, Computer Vision, Technology Strategies, Natural Language Processing, Innovation, Computer Hardware

      4.5
      Rating, 4.5 out of 5 stars
      ·
      164 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      C

      Coursera Project Network

      Create a Profile and Network on LinkedIn

      Skills you'll gain: LinkedIn, Professional Networking, Professional Development, General Networking, Professionalism

      4.6
      Rating, 4.6 out of 5 stars
      ·
      851 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • U

      Universidad de los Andes

      Introducción a la ciencia de datos aplicada

      Skills you'll gain: Exploratory Data Analysis, Statistical Hypothesis Testing, Correlation Analysis, Data Visualization Software, Data Science, Jupyter, Data Analysis, Business Analytics, Statistical Analysis, Probability & Statistics, Statistics, Python Programming, Descriptive Statistics, Data Modeling, Statistical Modeling, Design Thinking

      4.7
      Rating, 4.7 out of 5 stars
      ·
      399 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Cybersecurity Architecture: IBM
    • Data Analysis and Visualization with Python: Microsoft
    • Presentations: Speaking so that People Listen: University of California, Irvine
    • Data Structures and Algorithms: Amazon
    • 用 Python 做商管程式設計(二)(Programming for Business Computing in Python (2)): National Taiwan University
    • Spark, Hadoop, and Snowflake for Data Engineering: Duke University
    • An Introduction to Interactive Programming in Python (Part 2): Rice University
    • Learning Experience Design: Theories and Frameworks: University of Michigan
    • Cursos en línea: modelo para armar: Universidad Nacional Autónoma de México
    • Artificial Intelligence: An Overview: Politecnico di Milano

    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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