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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

    • M

      Microsoft

      Foundations of AI and Machine Learning

      Skills you'll gain: Data Management, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure Architecture, Cloud Infrastructure, MLOps (Machine Learning Operations), Application Deployment, Data Processing, Data Cleansing, Artificial Intelligence, Data Security, Application Frameworks, PyTorch (Machine Learning Library), Machine Learning, Tensorflow, Data Pipelines, Scikit Learn (Machine Learning Library), Scalability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      101 reviews

      Intermediate · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      AI For Medical Treatment

      Skills you'll gain: Deep Learning, Statistical Analysis, Clinical Trials, Feature Engineering, Treatment Planning, Data Analysis, Precision Medicine, Applied Machine Learning, Patient Treatment, Machine Learning Methods, AI Personalization, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Predictive Modeling, Medical Science and Research, Text Mining, Health Informatics, Large Language Modeling, Medical Terminology, Natural Language Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      523 reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Linear Algebra for Machine Learning and Data Science

      Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Machine Learning Methods, Jupyter, Data Manipulation, Data Science, Applied Mathematics, Python Programming, Image Analysis, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Preparing for Google Cloud Certification: Machine Learning Engineer

      Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Prompt Engineering, Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), Apache Airflow, Cloud Infrastructure, CI/CD, Artificial Intelligence and Machine Learning (AI/ML), Data Pipelines, Dataflow, Systems Design, Cloud Platforms, Data Management, Data Governance, Hybrid Cloud Computing, Workflow Management, Application Deployment

      4.4
      Rating, 4.4 out of 5 stars
      ·
      4.8K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Generative AI for Data Scientists

      Skills you'll gain: Prompt Engineering, ChatGPT, Generative AI, Exploratory Data Analysis, Data Ethics, OpenAI, Feature Engineering, Predictive Modeling, Large Language Modeling, Artificial Intelligence, Data Storytelling, Program Development, Data Modeling, Data Presentation, Data Synthesis, Data Analysis, Data Cleansing, Data Visualization Software, Data Manipulation, Image Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.5K reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free
      Free
      E

      Edge Impulse

      Introduction to Embedded Machine Learning

      Skills you'll gain: Applied Machine Learning, Embedded Systems, Data Processing, Machine Learning, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Data Ethics, Deep Learning, Feature Engineering, Performance Tuning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      719 reviews

      Intermediate · Course · 1 - 4 Weeks

    • A

      Amazon Web Services

      Introduction to Machine Learning on AWS

      Skills you'll gain: AWS SageMaker, Artificial Intelligence and Machine Learning (AI/ML), Amazon Web Services, Natural Language Processing, Artificial Intelligence, Image Analysis, Computer Vision, Text Mining, Machine Learning, Data Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      136 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      Imperial College London

      TensorFlow 2 for Deep Learning

      Skills you'll gain: Tensorflow, Generative AI, Data Pipelines, Keras (Neural Network Library), Deep Learning, Image Analysis, Computer Programming, Bayesian Statistics, Supervised Learning, Natural Language Processing, Data Processing, Computer Vision, Machine Learning Methods, Artificial Neural Networks, Machine Learning, Unsupervised Learning, Probability & Statistics, Time Series Analysis and Forecasting, Jupyter, Dimensionality Reduction

      4.8
      Rating, 4.8 out of 5 stars
      ·
      709 reviews

      Intermediate · Specialization · 3 - 6 Months

    • G

      Google

      The Nuts and Bolts of Machine Learning

      Skills you'll gain: Feature Engineering, Applied Machine Learning, Statistical Machine Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Unsupervised Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Random Forest Algorithm, Data Analysis, Performance Tuning, Python Programming

      4.8
      Rating, 4.8 out of 5 stars
      ·
      508 reviews

      Advanced · Course · 1 - 3 Months

    • I

      IBM

      Deep Learning and Reinforcement Learning

      Skills you'll gain: Generative AI, Reinforcement Learning, Deep Learning, Unsupervised Learning, Artificial Neural Networks, PyTorch (Machine Learning Library), Keras (Neural Network Library), Machine Learning Algorithms, Tensorflow, Computer Vision, Dimensionality Reduction, Natural Language Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      253 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      A

      Amazon Web Services

      Developing Machine Learning Solutions

      Skills you'll gain: MLOps (Machine Learning Operations), AWS SageMaker, Amazon Web Services, Cloud Management, Machine Learning, Applied Machine Learning, Cloud Development, Predictive Modeling

      4.5
      Rating, 4.5 out of 5 stars
      ·
      48 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Foundations of AI and Machine Learning: Microsoft
    • AI For Medical Treatment: DeepLearning.AI
    • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
    • Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
    • Generative AI for Data Scientists: IBM
    • Introduction to Embedded Machine Learning: Edge Impulse
    • Introduction to Machine Learning on AWS: Amazon Web Services
    • TensorFlow 2 for Deep Learning: Imperial College London
    • The Nuts and Bolts of Machine Learning: Google
    • Deep Learning and Reinforcement Learning: IBM

    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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