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    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: Free Trial
      Free Trial
      I

      IBM

      Generative AI and LLMs: Architecture and Data Preparation

      Skills you'll gain: Large Language Modeling, Generative AI, PyTorch (Machine Learning Library), Text Mining, Natural Language Processing, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Data Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      207 reviews

      Intermediate · Course · 1 - 4 Weeks

    • B

      Board Infinity

      Quality Improvement and Management

      Skills you'll gain: Quality Management, Statistical Process Controls, Quality Management Systems, ISO 9000 Series, Quality Improvement, Customer experience improvement, Quality Assurance, Quality Control, Continuous Quality Improvement (CQI), Continuous Improvement Process, Process Improvement, Customer Insights, Key Performance Indicators (KPIs)

      4.3
      Rating, 4.3 out of 5 stars
      ·
      227 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Graph Analytics for Big Data

      Skills you'll gain: Graph Theory, Database Design, Big Data, Network Analysis, Analytics, Data Management, Data Structures, Query Languages, Scalability, Unsupervised Learning, Distributed Computing, Algorithms

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.3K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      A

      Amazon

      Introduction to Software Development

      Skills you'll gain: Software Development Life Cycle, Object Oriented Programming (OOP), Java Programming, Java, Program Development, Software Development, Development Environment, Integrated Development Environments, Software Engineering, Programming Principles

      4.7
      Rating, 4.7 out of 5 stars
      ·
      200 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      T

      Tableau Learning Partner

      Data Analysis with Tableau

      Skills you'll gain: Exploratory Data Analysis, Tableau Software, Statistical Visualization, Data Analysis, Descriptive Statistics, Predictive Analytics, Data Processing, Box Plots, Statistical Analysis, Data Cleansing, Scatter Plots, Data Visualization Software, Trend Analysis, Histogram, Data Manipulation, Regression Analysis, Correlation Analysis

      4.4
      Rating, 4.4 out of 5 stars
      ·
      89 reviews

      Beginner · Course · 1 - 4 Weeks

    • K

      Kennesaw State University

      Writing Professional Email and Memos (Project-Centered Course)

      Skills you'll gain: Peer Review, Grammar, Business Writing, Business Correspondence, Writing, Writing and Editing, Editing, Proofreading, Concision, Taking Meeting Minutes, Professionalism, Business Communication, Report Writing, Administrative Support and Clerical Tasks, Target Audience, Communication, Constructive Feedback

      4.3
      Rating, 4.3 out of 5 stars
      ·
      450 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      V

      Voxy

      Low Intermediate English: Meet & Greet

      Skills you'll gain: Vocabulary, English Language, Oral Comprehension, Language Competency, Grammar

      4.6
      Rating, 4.6 out of 5 stars
      ·
      259 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      Universidad de los Andes

      Ciencia de datos​

      Skills you'll gain: Data Ethics, Data Integration, Exploratory Data Analysis, Statistical Hypothesis Testing, Predictive Modeling, Correlation Analysis, Data Visualization Software, Classification And Regression Tree (CART), Data Quality, Data Science, Jupyter, Data Analysis, Data Transformation, Data Cleansing, Business Analytics, Data Manipulation, Supervised Learning, Statistical Analysis, Regression Analysis, Applied Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      511 reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: New
      New
      Status: Free Trial
      Free Trial
      S

      Snowflake

      Snowflake Data Engineering

      Skills you'll gain: Data Pipelines, Database Management, Data Manipulation, Databases, Data Transformation, Extract, Transform, Load, Data Lakes, Data Warehousing, DevOps, Data Integration, SQL, Cloud Applications, CI/CD, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Real Time Data, Role-Based Access Control (RBAC), Data Import/Export, Stored Procedure, Command-Line Interface

      4.8
      Rating, 4.8 out of 5 stars
      ·
      183 reviews

      Beginner · Professional Certificate · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      N

      New York University

      Guided Tour of Machine Learning in Finance

      Skills you'll gain: Supervised Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Artificial Neural Networks, Predictive Modeling, Scikit Learn (Machine Learning Library), Regression Analysis, Deep Learning, Financial Services, Finance, Tensorflow, Jupyter, Reinforcement Learning

      3.8
      Rating, 3.8 out of 5 stars
      ·
      679 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      Coursera Project Network

      Introduction to Basic Game Development using Scratch

      Skills you'll gain: Event-Driven Programming, Debugging, Programming Principles, Algorithms, Video Game Development, Computer Programming Tools, Game Design, Computer Programming, Program Development, Animation and Game Design, Interactive Design, Integrated Development Environments, Computer Science

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.5K reviews

      Beginner · Guided Project · Less Than 2 Hours

    • Status: Free Trial
      Free Trial
      L

      LearnQuest

      Ethics in the Age of AI

      Skills you'll gain: Data Ethics, Predictive Modeling, OpenAI, Algorithms, Data Collection, Machine Learning, Predictive Analytics, Artificial Intelligence, Information Privacy, Game Theory, Large Language Modeling, Ethical Standards And Conduct, Personally Identifiable Information, Statistical Modeling, Analytical Skills, Analysis, Data Security, Business Ethics, Vulnerability Assessments, Risk Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      779 reviews

      Beginner · Specialization · 3 - 6 Months

    Deep Learning learners also search

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

    • Generative AI and LLMs: Architecture and Data Preparation: IBM
    • Quality Improvement and Management: Board Infinity
    • Graph Analytics for Big Data: University of California San Diego
    • Introduction to Software Development: Amazon
    • Data Analysis with Tableau: Tableau Learning Partner
    • Writing Professional Email and Memos (Project-Centered Course): Kennesaw State University
    • Low Intermediate English: Meet & Greet: Voxy
    • Ciencia de datos​: Universidad de los Andes
    • Snowflake Data Engineering: Snowflake
    • Guided Tour of Machine Learning in Finance: New York 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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