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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

    • G

      Google Cloud

      Advanced Machine Learning on Google Cloud

      Skills you'll gain: Natural Language Processing, MLOps (Machine Learning Operations), Tensorflow, Large Language Modeling, Reinforcement Learning, Computer Vision, Google Cloud Platform, Keras (Neural Network Library), Systems Design, Image Analysis, Hybrid Cloud Computing, Applied Machine Learning, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms, Distributed Computing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • Status: New
      New
      I

      IBM

      IBM Generative AI Engineering

      Skills you'll gain: Prompt Engineering, Generative AI, Data Wrangling, Large Language Modeling, Unit Testing, Supervised Learning, Feature Engineering, Keras (Neural Network Library), Deep Learning, ChatGPT, Natural Language Processing, Data Cleansing, Jupyter, Data Analysis, Unsupervised Learning, Data Manipulation, PyTorch (Machine Learning Library), Artificial Intelligence, Data Import/Export, Data Ethics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      85K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: AI skills
      AI skills
      U

      University of Pennsylvania

      AI and Machine Learning Essentials with Python

      Skills you'll gain: Statistical Machine Learning, PyTorch (Machine Learning Library), Probability, Probability & Statistics, Sampling (Statistics), Deep Learning, Probability Distribution, Python Programming, Supervised Learning, Statistics, Machine Learning, Regression Analysis, Data Processing, Agentic systems, Data Science, Artificial Intelligence, Artificial Neural Networks, Algorithms, Computer Vision, Theoretical Computer Science

      4.6
      Rating, 4.6 out of 5 stars
      ·
      19 reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Cleansing, Data Access, Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Data Science, Probability & Statistics, Jupyter, Machine Learning, Data Manipulation, Pandas (Python Package), Statistical Analysis, Data Transformation, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.2K reviews

      Intermediate · Course · 1 - 3 Months

    • M

      Microsoft

      Microsoft Copilot for Data Science

      Skills you'll gain: Generative AI, Microsoft Copilot, Natural Language Processing, Data Quality, Anomaly Detection, Data Storytelling, Data Ethics, Data-Driven Decision-Making, Interactive Data Visualization, Data Presentation, OpenAI, Data Pipelines, Prompt Engineering, Data Cleansing, Data Visualization Software, Data Synthesis, Data Analysis, Communication, Data Validation, Large Language Modeling

      4.6
      Rating, 4.6 out of 5 stars
      ·
      43 reviews

      Beginner · Specialization · 1 - 3 Months

    • U

      University of London

      Machine Learning for All

      Skills you'll gain: Machine Learning, Artificial Intelligence, Supervised Learning, Data Analysis, Computer Vision, Data Collection, Development Testing

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

      Beginner · Course · 1 - 4 Weeks

    • J

      Johns Hopkins University

      Practical Machine Learning

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

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.3K reviews

      Mixed · Course · 1 - 4 Weeks

    • 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
      ·
      505 reviews

      Advanced · Course · 1 - 3 Months

    • Status: New
      New
      I

      IBM

      IBM Deep Learning with PyTorch, Keras and Tensorflow

      Skills you'll gain: PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Unsupervised Learning, Image Analysis, Data Manipulation, Tensorflow, Verification And Validation, Generative AI, Artificial Neural Networks, Data Processing, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Artificial Intelligence, Scientific Visualization, Time Series Analysis and Forecasting, Predictive Modeling, Natural Language Processing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • N

      New York University

      Machine Learning and Reinforcement Learning in Finance

      Skills you'll gain: Supervised Learning, Reinforcement Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Artificial Neural Networks, Decision Tree Learning, Predictive Modeling, Financial Trading, Financial Market, Derivatives, Scikit Learn (Machine Learning Library), Markov Model, Regression Analysis, Deep Learning, Market Liquidity, Financial Services

      3.7
      Rating, 3.7 out of 5 stars
      ·
      814 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      A

      Amazon Web Services

      Fundamentals of Machine Learning and Artificial Intelligence

      Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, Artificial Intelligence, AWS SageMaker, Amazon Web Services, Applied Machine Learning, Machine Learning, Digital Transformation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      390 reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      IBM

      IBM AI Developer

      Skills you'll gain: Generative AI, Prompt Engineering, Large Language Modeling, Software Development Life Cycle, Unit Testing, ChatGPT, HTML and CSS, Development Environment, Web Design and Development, Jupyter, Hypertext Markup Language (HTML), Software Engineering, Artificial Intelligence, Cascading Style Sheets (CSS), Software Development Tools, Web Development, Application Deployment, Automation, Interviewing Skills, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      68K reviews

      Beginner · Professional Certificate · 3 - 6 Months

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

    • Advanced Machine Learning on Google Cloud: Google Cloud
    • IBM Generative AI Engineering: IBM
    • AI and Machine Learning Essentials with Python: University of Pennsylvania
    • Exploratory Data Analysis for Machine Learning: IBM
    • Microsoft Copilot for Data Science: Microsoft
    • Machine Learning for All: University of London
    • Practical Machine Learning: Johns Hopkins University
    • The Nuts and Bolts of Machine Learning: Google
    • IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
    • Machine Learning and Reinforcement Learning in Finance: New York 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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