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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

    • U

      University of Michigan

      Applied Machine Learning in Python

      Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Dimensionality Reduction, Random Forest Algorithm

      4.6
      Rating, 4.6 out of 5 stars
      ·
      8.6K reviews

      Intermediate · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Applied Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Unsupervised Learning, Computer Vision, Machine Learning Algorithms, Applied Machine Learning, Image Analysis, Dimensionality Reduction, Supervised Learning, Reinforcement Learning, Feature Engineering, Regression Analysis, Data Cleansing, Machine Learning, Data Mining, Scikit Learn (Machine Learning Library), Statistical Machine Learning, Advanced Analytics, Deep Learning, Artificial Neural Networks, Decision Tree Learning

      3.7
      Rating, 3.7 out of 5 stars
      ·
      7 reviews

      Intermediate · Specialization · 3 - 6 Months

    • D
      S

      Multiple educators

      Machine Learning

      Skills you'll gain: Unsupervised Learning, Supervised Learning, Machine Learning Methods, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), Artificial Intelligence, NumPy, Predictive Modeling, Deep Learning, Reinforcement Learning, Random Forest Algorithm, Feature Engineering

      Build toward a degree

      4.9
      Rating, 4.9 out of 5 stars
      ·
      33K reviews

      Beginner · Specialization · 1 - 3 Months

    • I

      IBM

      Machine Learning with Python

      Skills you'll gain: Supervised Learning, Feature Engineering, Jupyter, Unsupervised Learning, Scikit Learn (Machine Learning Library), Python Programming, Predictive Modeling, Machine Learning, Dimensionality Reduction, Classification And Regression Tree (CART), Matplotlib, NumPy, Regression Analysis, Statistical Modeling

      4.7
      Rating, 4.7 out of 5 stars
      ·
      17K reviews

      Intermediate · Course · 1 - 3 Months

    • A

      Alberta Machine Intelligence Institute

      Introduction to Applied Machine Learning

      Skills you'll gain: Data Ethics, Applied Machine Learning, Data Processing, Machine Learning, Machine Learning Algorithms, Product Lifecycle Management, Supervised Learning, Data Modeling, Business Requirements, Business Analysis, Unsupervised Learning, Artificial Intelligence, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      739 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      IBM Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Feature Engineering, Generative AI, Dimensionality Reduction, Reinforcement Learning, Data Cleansing, Data Access, Deep Learning, Data Analysis, Regression Analysis, Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Statistical Analysis, Statistical Inference, Statistical Hypothesis Testing, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library)

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • U

      University of Washington

      Machine Learning

      Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      DeepLearning.AI

      Machine Learning in Production

      Skills you'll gain: MLOps (Machine Learning Operations), Application Deployment, Continuous Deployment, Software Development Life Cycle, Machine Learning, Applied Machine Learning, Data Quality, Debugging, Continuous Monitoring, Data Pipelines

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Deep Learning

      Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Tensorflow, Supervised Learning, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Debugging, Performance Tuning, Keras (Neural Network Library), Python Programming, Machine Learning Algorithms, Analysis, Data Processing

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      146K reviews

      Intermediate · Specialization · 3 - 6 Months

    • D

      Duke University

      MLOps | Machine Learning Operations

      Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Data Ethics, Application Deployment, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, Software Testing, Data Import/Export, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Docker (Software), Rust (Programming Language)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      449 reviews

      Advanced · Specialization · 3 - 6 Months

    • D

      Duke University

      Introduction to Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Image Analysis, Applied Machine Learning, Deep Learning, Machine Learning, Natural Language Processing, Supervised Learning, Unsupervised Learning, Artificial Neural Networks, Computer Vision, Medical Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • M

      Microsoft

      Microsoft Azure Machine Learning

      Skills you'll gain: Unsupervised Learning, Microsoft Azure, Applied Machine Learning, Regression Analysis, Predictive Modeling, Machine Learning Methods, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Artificial Intelligence, Automation, Supervised Learning

      4.4
      Rating, 4.4 out of 5 stars
      ·
      229 reviews

      Beginner · Course · 1 - 4 Weeks

    Applied Machine Learning learners also search

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    1234…447

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

    • Applied Machine Learning in Python: University of Michigan
    • Applied Machine Learning: Johns Hopkins University
    • Machine Learning: DeepLearning.AI
    • Machine Learning with Python: IBM
    • Introduction to Applied Machine Learning: Alberta Machine Intelligence Institute
    • IBM Machine Learning: IBM
    • Machine Learning: University of Washington
    • Machine Learning in Production: DeepLearning.AI
    • Deep Learning: DeepLearning.AI
    • MLOps | Machine Learning Operations: Duke 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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