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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

      IBM Introduction to Machine Learning

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

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.9K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Introduction to Generative AI Learning Path

      Skills you'll gain: Large Language Modeling, Generative AI, Prompt Engineering, Data Ethics, Google Cloud Platform, Business Ethics, Application Development, Artificial Intelligence, Accountability, Compliance Training, Ethical Standards And Conduct, Artificial Intelligence and Machine Learning (AI/ML), Governance, Organizational Effectiveness, Machine Learning Methods, Decision Making, Corporate Strategy

      4.6
      Rating, 4.6 out of 5 stars
      ·
      9.1K reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Applied Data Science with Python

      Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Data Visualization Software, Interactive Data Visualization, Scientific Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Visualization (Computer Graphics), Statistical Visualization, Scikit Learn (Machine Learning Library), Network Model, Jupyter, NumPy, Graph Theory, Data Manipulation, Natural Language Processing, Data Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      34K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      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
      ·
      24 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM AI Developer

      Skills you'll gain: Prompt Engineering, HTML and CSS, Software Development Life Cycle, Software Architecture, Large Language Modeling, Unit Testing, Generative AI, Artificial Intelligence, Software Design, ChatGPT, Jupyter, Scrum (Software Development), Software Engineering, Agile Methodology, Bootstrap (Front-End Framework), Web Design, Application Deployment, Automation, Interviewing Skills, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      69K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • D

      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Data Ethics, Market Opportunities, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Team Building, Machine Learning, Strategic Thinking, Data Science, Needs Assessment, Deep Learning, Business Ethics, Artificial Neural Networks, Engineering Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      48K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Feature Engineering, Data Transformation, Jupyter, Data Science, Advanced Mathematics, Statistics, Machine Learning Algorithms, Machine Learning Methods, Statistical Analysis, Artificial Neural Networks, Algorithms, Data Manipulation, Python Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      15K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      Status: AI skills
      AI skills
      I

      IBM

      IBM Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Data Wrangling, Data Visualization, SQL, Supervised Learning, Feature Engineering, Plotly, Interactive Data Visualization, Jupyter, Data Literacy, Exploratory Data Analysis, Data Mining, Data Cleansing, Matplotlib, Data Analysis, Unsupervised Learning, Generative AI, Pandas (Python Package), Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      143K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM DevOps and Software Engineering

      Skills you'll gain: CI/CD, Istio, Open Web Application Security Project (OWASP), Continuous Integration, Software Development Life Cycle, Software Architecture, Linux Commands, Agile Software Development, Unit Testing, Cloud Computing Architecture, Application Deployment, Test Driven Development (TDD), Gherkin (Scripting Language), Jenkins, Kubernetes, Bash (Scripting Language), Git (Version Control System), DevOps, Jupyter, Grafana

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      60K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      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

    • D

      DeepLearning.AI

      Generative AI for Everyone

      Skills you'll gain: Prompt Engineering, Generative AI, Large Language Modeling, OpenAI, ChatGPT, Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Business Process Automation, Automation, Ethical Standards And Conduct, Cloud Applications

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.6K reviews

      Beginner · Course · 1 - 4 Weeks

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

    • IBM Introduction to Machine Learning: IBM
    • Introduction to Generative AI Learning Path: Google Cloud
    • Applied Data Science with Python: University of Michigan
    • AI and Machine Learning Essentials with Python: University of Pennsylvania
    • IBM AI Developer: IBM
    • AI For Everyone: DeepLearning.AI
    • Mathematics for Machine Learning: Imperial College London
    • IBM Data Science: IBM
    • IBM DevOps and Software Engineering: IBM
    • Practical Machine Learning: Johns Hopkins 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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