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    • Deep Learning

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    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
      U

      University of Minnesota

      Managing Employee Compensation

      Skills you'll gain: Compensation Management, Compensation Strategy, Compensation and Benefits, Compensation Analysis, Payroll, Benefits Administration, Labor Compliance, Employee Retention, Employee Performance Management, Employee Engagement, Labor Law

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.9K reviews

      Mixed · Course · 1 - 4 Weeks

    • U

      University of Michigan

      Social Work Practice: Advocating Social Justice and Change

      Skills you'll gain: Social Work, Community and Social Work, Social Justice, Advocacy, Cultural Sensitivity, Diversity Awareness, Research, Systems Thinking, Human Development, Policy Development, Ethical Standards And Conduct, Interpersonal Communications

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      413 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Introduction to Statistics & Data Analysis in Public Health

      Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Data Literacy, Data Analysis, Statistical Software, R Programming, Statistics, Public Health, Descriptive Statistics, Probability Distribution, Data Import/Export

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.5K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Alberta

      Prediction and Control with Function Approximation

      Skills you'll gain: Reinforcement Learning, Deep Learning, Machine Learning Algorithms, Machine Learning, Supervised Learning, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution

      4.8
      Rating, 4.8 out of 5 stars
      ·
      836 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Foundations of Public Health Practice

      Skills you'll gain: Public Health, Health Equity, Health Disparities, Microbiology, Health Assessment, Sanitation, Program Evaluation, Epidemiology, Infectious Diseases, Health Policy, Preventative Care, Behavioral Economics, Community Health, Data Literacy, Behavioral Health, Intelligence Collection and Analysis, Emergency Response, Health And Safety Standards, Public Health and Disease Prevention, Health Systems

      4.8
      Rating, 4.8 out of 5 stars
      ·
      640 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      K

      Kennesaw State University

      Career Discovery

      Skills you'll gain: Professional Networking, LinkedIn, Mentorship, Professional Development, Interviewing Skills, Social Media, Relationship Building, Social Media Strategy, Planning, Strategic Communication, Communication, Social Skills, Adaptability, Collaboration, Business Research, Negotiation, Leadership Development, Professionalism, Lifelong Learning, Goal Setting

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.7K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      Fundamentals of Management

      Skills you'll gain: Goal Setting, Professional Networking, Business Management, Staff Management, Leadership and Management, Operations Management, People Management, Business Administration, Business Planning, Customer Service, Organizational Leadership, Organizational Strategy, Leadership, Change Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.9K reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google

      Regression Analysis: Simplify Complex Data Relationships

      Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Advanced Analytics, Correlation Analysis, Data Analysis, Predictive Modeling, Statistical Modeling, Supervised Learning, Variance Analysis, Machine Learning Methods, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      531 reviews

      Advanced · Course · 1 - 3 Months

    • Y

      Yale University

      Health Behavior Change: From Evidence to Action

      Skills you'll gain: Public Health and Disease Prevention, Nutrition and Diet, Public Health, Behavioral Health, Mental Health, Mental and Behavioral Health, Behavioral Economics, Patient Education And Counseling, Program Evaluation, Preventative Care

      4.8
      Rating, 4.8 out of 5 stars
      ·
      453 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Minnesota

      Recommender Systems

      Skills you'll gain: AI Personalization, Machine Learning Algorithms, Taxonomy, Applied Machine Learning, Machine Learning, Dimensionality Reduction, Performance Metric, Spreadsheet Software, Data Collection, Performance Measurement, Benchmarking, Usability Testing, Exploratory Data Analysis, A/B Testing, Analysis, Artificial Intelligence and Machine Learning (AI/ML), Technical Design, Algorithms, System Design and Implementation, Predictive Modeling

      4.3
      Rating, 4.3 out of 5 stars
      ·
      823 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      K

      Keller Williams

      Keller Williams Real Estate Agent

      Skills you'll gain: Lead Generation, Administrative Support, Real Estate, Office Management, Real Estate Sales, Value Propositions, Property and Real Estate, Sales Process, Customer Relationship Building, Real Estate Transactions, Customer Acquisition Management, Sales Management, Organizational Skills, Sales Prospecting, Sales Presentation, Showrooms, Prospecting and Qualification, Closing (Sales), Branding, Prioritization

      4.7
      Rating, 4.7 out of 5 stars
      ·
      156 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • U

      University of Michigan

      Instructional Methods in Health Professions Education

      Skills you'll gain: Instructional Design, Adult Learning Principles, Education Software and Technology, Patient Education And Counseling, Learning Theory, Learning Styles, Creativity, Decision Making, Technology Strategies

      4.7
      Rating, 4.7 out of 5 stars
      ·
      520 reviews

      Intermediate · Course · 1 - 3 Months

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

    • Managing Employee Compensation: University of Minnesota
    • Social Work Practice: Advocating Social Justice and Change: University of Michigan
    • Introduction to Statistics & Data Analysis in Public Health: Imperial College London
    • Prediction and Control with Function Approximation: University of Alberta
    • Foundations of Public Health Practice: Imperial College London
    • Career Discovery: Kennesaw State University
    • Fundamentals of Management: University of California, Irvine
    • Regression Analysis: Simplify Complex Data Relationships: Google
    • Health Behavior Change: From Evidence to Action: Yale University
    • Recommender Systems: University of Minnesota

    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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