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    • Applied Machine Learning

    Applied Machine Learning Courses Online

    Explore applied machine learning for practical applications. Learn to implement models using scikit-learn, TensorFlow, and real-world datasets.

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    Explore the Applied Machine Learning Course Catalog

    • Status: Free Trial
      Free Trial
      I

      IBM

      Supervised Machine Learning: Regression

      Skills you'll gain: Supervised Learning, Regression Analysis, Predictive Modeling, Machine Learning, Statistical Modeling, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Feature Engineering, Statistical Analysis, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      740 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Corporate & Commercial Law I: Contracts & Employment Law

      Skills you'll gain: Certified Public Accountant, Labor Law, Commercial Laws, Regulation and Legal Compliance, Bankruptcies, Organizational Structure, Business, Legal Writing, Contract Management, Sales

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      B

      Berklee

      Guitar for Beginners

      Skills you'll gain: Music Theory, Music, Instrumental Music, Music Performance, Creativity

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2.3K reviews

      Mixed · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      MLOps Platforms: Amazon SageMaker and Azure ML

      Skills you'll gain: AWS SageMaker, MLOps (Machine Learning Operations), Microsoft Azure, Exploratory Data Analysis, Data Pipelines, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Data Analysis, Predictive Modeling, Serverless Computing, Machine Learning, Machine Learning Algorithms, Containerization

      3.6
      Rating, 3.6 out of 5 stars
      ·
      48 reviews

      Advanced · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      IA Para Todos (Español)

      Skills you'll gain: Market Opportunities, Artificial Intelligence, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Strategic Thinking, Artificial Neural Networks, Data Science, Business Intelligence, Deep Learning, Machine Learning, Business Transformation, Computer Vision

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

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of California, Irvine

      IELTS Listening and Speaking Sections Skills Mastery

      Skills you'll gain: Time Management, Oral Comprehension, Active Listening, Language Competency, Public Speaking, Verbal Communication Skills, Learning Strategies, English Language, Vocabulary, Composure, Communication, Grammar, Detail Oriented, Adaptability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      598 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      S

      SAS

      Getting Started with SAS Programming

      Skills you'll gain: SAS (Software), Data Import/Export, Data Validation, Data Access, Data Manipulation, Exploratory Data Analysis, Data Analysis, SQL, Data Presentation, Microsoft Excel, Descriptive Statistics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.1K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Applied Text Mining in Python

      Skills you'll gain: Text Mining, Natural Language Processing, Data Processing, Unstructured Data, Feature Engineering, Data Manipulation, Data Cleansing, Unsupervised Learning, Machine Learning Algorithms, Supervised Learning

      4.2
      Rating, 4.2 out of 5 stars
      ·
      3.8K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University at Buffalo

      ADHD: Everyday Strategies for Elementary Students

      Skills you'll gain: Psychological Evaluations, Classroom Management, Teaching, Instructional Strategies, Student Engagement, Parent Communication, Mental and Behavioral Health, Behavior Management, Positive Behavior Support, Working With Children, Pediatrics, Mental Health Diseases and Disorders, Treatment Planning, Child Development, Disabilities

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • N

      National Taiwan University

      機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations

      Skills you'll gain: Supervised Learning, Machine Learning, Machine Learning Algorithms, Data Validation, Classification And Regression Tree (CART), Applied Machine Learning, Algorithms, Regression Analysis, Predictive Modeling, Verification And Validation, Feature Engineering, Statistical Methods, Data Transformation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      331 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of London

      Foundations of Data Science: K-Means Clustering in Python

      Skills you'll gain: Data Visualization, Matplotlib, Probability & Statistics, Data Science, Unsupervised Learning, Statistics, NumPy, Python Programming, Pandas (Python Package), Data Analysis, Machine Learning Algorithms, Descriptive Statistics, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      718 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Mathematical Thinking in Computer Science

      Skills you'll gain: Logical Reasoning, Computational Logic, Deductive Reasoning, Computational Thinking, Theoretical Computer Science, Algorithms, Python Programming, Computer Programming, Computer Science, Program Development

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.3K reviews

      Beginner · Course · 1 - 3 Months

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

    • Supervised Machine Learning: Regression: IBM
    • Corporate & Commercial Law I: Contracts & Employment Law: University of Illinois Urbana-Champaign
    • Guitar for Beginners: Berklee
    • MLOps Platforms: Amazon SageMaker and Azure ML: Duke University
    • IA Para Todos (Español): DeepLearning.AI
    • IELTS Listening and Speaking Sections Skills Mastery: University of California, Irvine
    • Getting Started with SAS Programming: SAS
    • Applied Text Mining in Python: University of Michigan
    • ADHD: Everyday Strategies for Elementary Students: University at Buffalo
    • 機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations: National Taiwan 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 Applied Machine Learning

    It's important to learn about applied machine learning if you want to pursue a career in it or if you want to know how to use it in data analysis. Applied machine learning can be used to solve problems and collect insights from big data sets. When you learn machine learning fundamentals, you will be able to do predictive analysis, data analysis, and text mining. You'll be able to apply different programming languages and platforms to the data problems faced in your organization. Applied machine learning can help you pull insights and make decisions from the information that has been collecting for a long time.‎

    Career opportunities that arise from learning applied machine learning are mostly in computer programming. Applied machine learning, also known as automatic machine learning or AutoML, involves using computer languages for data analysis of large data. Being able to create the programs to do this is important. It is also useful to understand the power and limitations of applied machine learning if you will be using reports and making decisions based on applied machine learning. More and more management information systems include aspects of applied machine learning. This makes the field more useful to those who use data in their daily work.‎

    Online courses on Coursera can help you learn applied machine learning in several languages and platforms, including Python, Matlab, Google Cloud, H20 in R, and TensorFlow. Some courses cover programming languages, and others look at how machine learning is applied to decision making in specific fields. Most courses are at an intermediate level, but a few offer a beginner-level introduction to the fundamentals of applied machine learning and how to chart, plot, and mine text to make big data usable. The courses include lectures, readings, and projects so that you can apply what you learn. Some courses stand alone, and others are part of Specializations and Professional Certificates.‎

    Online Applied Machine Learning courses offer a convenient and flexible way to enhance your existing knowledge or learn new Applied Machine Learning skills. With a wide range of Applied Machine Learning classes, you can conveniently learn at your own pace to advance your Applied Machine Learning career skills.‎

    When looking to enhance your workforce's skills in Applied Machine 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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