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    • Unsupervised Learning

    Unsupervised Learning Courses Online

    Study unsupervised learning for machine learning. Learn about clustering, dimensionality reduction, and anomaly detection techniques.

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    Explore the Unsupervised Learning Course Catalog

    • U

      Universidade de São Paulo

      Introdução à Ciência da Computação com Python Parte 2

      Skills you'll gain: Object Oriented Programming (OOP), Computer Programming, Performance Testing, Algorithms, Computer Science, Data Structures, Python Programming, Computational Thinking, Performance Tuning, Software Testing

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      MathWorks

      Introduction to Deep Learning for Computer Vision

      Skills you'll gain: Computer Vision, Image Analysis, Matlab, Artificial Neural Networks, Deep Learning, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Machine Learning Methods, Performance Tuning, Classification And Regression Tree (CART), Data Processing

      4.9
      Rating, 4.9 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 4 Weeks

    • E

      Erasmus University Rotterdam

      Assessment in Higher Education: Professional Development for Teachers

      Skills you'll gain: Constructive Feedback, Higher Education, Instructional Design, Program Standards, Planning, Reliability, Analytical Skills, Decision Making

      4.8
      Rating, 4.8 out of 5 stars
      ·
      410 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California, Davis

      Big Data, Artificial Intelligence, and Ethics

      Skills you'll gain: Data Ethics, Artificial Intelligence, Research, Natural Language Processing, Big Data, Research Methodologies, Social Sciences, Machine Learning, Data Mining, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      610 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Geneva

      Simulation and modeling of natural processes

      Skills you'll gain: Simulations, Python Programming, Differential Equations, Numerical Analysis, Mathematical Modeling, Probability, Artificial Intelligence and Machine Learning (AI/ML), Computational Thinking, Visualization (Computer Graphics), Mechanics, Algorithms

      4.3
      Rating, 4.3 out of 5 stars
      ·
      398 reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      C

      Columbia University

      First Principles of Computer Vision

      Skills you'll gain: Computer Vision, Image Analysis, Computer Graphics, Dimensionality Reduction, 3D Modeling, Photography, Artificial Neural Networks, Virtual Reality, Medical Imaging, Visualization (Computer Graphics), Color Theory, Unsupervised Learning, Deep Learning, Graph Theory, Automation Engineering, Mathematical Modeling, Machine Learning Algorithms, Estimation, Electronic Components, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      215 reviews

      Beginner · Specialization · 3 - 6 Months

    • S

      Siemens

      Applied Computational Fluid Dynamics

      Skills you'll gain: Engineering Analysis, Thermal Management, Hydraulics, Mechanical Engineering, Simulations, Numerical Analysis, Engineering Calculations, Mathematical Modeling, Engineering, Chemical Engineering, Civil Engineering, Physics, Test Case

      4.7
      Rating, 4.7 out of 5 stars
      ·
      161 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Minnesota

      Introduction to Recommender Systems: Non-Personalized and Content-Based

      Skills you'll gain: Taxonomy, AI Personalization, Spreadsheet Software, Machine Learning, Predictive Analytics, Statistical Methods, Persona Development, Descriptive Statistics, Data Collection, Algorithms, Java Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      651 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Introduction to NoSQL Databases

      Skills you'll gain: NoSQL, MongoDB, Databases, Apache Cassandra, Distributed Computing, Database Management, Database Architecture and Administration, IBM Cloud, Query Languages, Data Modeling, JSON, Scalability, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      350 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Alberta

      Problem Solving, Python Programming, and Video Games

      Skills you'll gain: Computational Thinking, Video Game Development, Game Design, Programming Principles, Animation and Game Design, Software Quality (SQA/SQC), Computer Programming, Program Development, Software Engineering, Python Programming, Algorithms, Pseudocode, Application Development, Debugging, Problem Management, Functional Testing, Test Planning

      4.3
      Rating, 4.3 out of 5 stars
      ·
      233 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      AI Workflow: Feature Engineering and Bias Detection

      Skills you'll gain: Feature Engineering, Data Ethics, Unsupervised Learning, Dimensionality Reduction, Text Mining, Applied Machine Learning, Data Transformation, Anomaly Detection, Exploratory Data Analysis, Natural Language Processing, Quality Assurance, Data Validation, Machine Learning Algorithms, Data Visualization

      4.4
      Rating, 4.4 out of 5 stars
      ·
      72 reviews

      Advanced · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Introduction to Machine Learning in Sports Analytics

      Skills you'll gain: Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Statistical Machine Learning, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Analytics, Machine Learning, Data Analysis, Random Forest Algorithm

      4.8
      Rating, 4.8 out of 5 stars
      ·
      24 reviews

      Intermediate · Course · 1 - 4 Weeks

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

    • Introdução à Ciência da Computação com Python Parte 2: Universidade de São Paulo
    • Introduction to Deep Learning for Computer Vision: MathWorks
    • Assessment in Higher Education: Professional Development for Teachers: Erasmus University Rotterdam
    • Big Data, Artificial Intelligence, and Ethics: University of California, Davis
    • Simulation and modeling of natural processes: University of Geneva
    • First Principles of Computer Vision: Columbia University
    • Applied Computational Fluid Dynamics: Siemens
    • Introduction to Recommender Systems: Non-Personalized and Content-Based: University of Minnesota
    • Introduction to NoSQL Databases: IBM
    • Problem Solving, Python Programming, and Video Games: University of Alberta

    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 Unsupervised Learning

    Unsupervised learning is a type of AI-based machine learning that lets people get information from untargeted data sets. The machines find and manage unlabeled data so people are able to take advantage of complex tools, such as dimension reduction algorithms and clustering. The result of unsupervised learning is that users are able to identify patterns and results that emerge from a raw data set. Instead of entering a data set or goal, someone using unsupervised learning gets to let the data sets and patterns emerge to find the algorithm that makes the most sense.‎

    If you enjoy solving complex puzzles and detecting hidden information to answer questions, learning about unsupervised learning puts it within your grasp to identify and present data in a coherent, usable manner. Learning how tools like dimensionality reduction algorithms and clustering let you break raw data into subsets and categories or clusters that can be used to create models. This makes the information usable for decision-making purposes as well as for directing supervised AI to explore specific data subsets. The categorized information becomes more relevant, and the characteristics of data clusters become more recognizable.‎

    Data scientists and machine learning (AI) specialists are two career opportunities that can emerge from picking up the study of unsupervised learning. Before studying unsupervised learning, it helps to have Python programming knowledge and know the basics of calculus, data cleaning, probability, statistics, linear algebra, and exploratory data analysis because unsupervised learning builds upon these skills. You might work exclusively in the field of IBM machine learning strategies, or you may work in another field, such as engineering, customer market segmentation, data mining, or predictive analysis. Studying unsupervised learning helps you stay on top of developments in machine learning to stay relevant as well as advance in your career if you're already in the field.‎

    The online unsupervised learning courses on Coursera give you the knowledge and practical experience about machine learning so you're able to use tools like k-means clustering, cluster analysis, and principle component analysis (PCA) to apply unsupervised machine learning techniques in a business setting. Apply these new skills and newly learned information to real-life business situations. Our online unsupervised learning courses provide the information and opportunity for you to develop a skill set that helps you reach your career goals or earn college credits at your own pace, and on your own terms.‎

    Online Unsupervised Learning courses offer a convenient and flexible way to enhance your knowledge or learn new Unsupervised Learning skills. Choose from a wide range of Unsupervised Learning courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Unsupervised Learning, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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