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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

      Introduction to Deep Learning & Neural Networks with Keras

      Skills you'll gain: Keras (Neural Network Library), Deep Learning, Unsupervised Learning, Artificial Neural Networks, PyTorch (Machine Learning Library), Tensorflow, Image Analysis, Computer Vision, Natural Language Processing, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Unsupervised Learning, Recommenders, Reinforcement Learning

      Skills you'll gain: Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Reinforcement Learning, Statistical Machine Learning, Artificial Neural Networks, Deep Learning, Anomaly Detection, Dimensionality Reduction, Algorithms, Collaborative Software

      4.9
      Rating, 4.9 out of 5 stars
      ·
      4.7K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Probability & Statistics for Machine Learning & Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      565 reviews

      Intermediate · Course · 1 - 4 Weeks

    • S

      Stanford University

      Introduction to Statistics

      Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Data Collection, Probability Distribution

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.1K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      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

    • P

      Peking University

      Chinese for Beginners

      Skills you'll gain: Language Learning, Language Competency, Vocabulary, Oral Expression, Oral Comprehension

      4.8
      Rating, 4.8 out of 5 stars
      ·
      20K reviews

      Mixed · Course · 1 - 3 Months

    • M

      McMaster University

      Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential

      Skills you'll gain: Lifelong Learning, Willingness To Learn, Learning Strategies, Growth Mindedness, Mentorship, Adaptability, Professional Development, Personal Development, Productivity, Open Mindset, Resilience, Stress Management, Overcoming Obstacles, Curiosity, Cognitive flexibility

      4.8
      Rating, 4.8 out of 5 stars
      ·
      13K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Pennsylvania

      English for Career Development

      Skills you'll gain: English Language, Vocabulary, Business Writing, Interviewing Skills, Verbal Communication Skills, Business Correspondence, Social Skills, Professional Networking, Professional Development, Business Communication

      4.8
      Rating, 4.8 out of 5 stars
      ·
      16K reviews

      Mixed · Course · 1 - 3 Months

    • N

      National Taiwan University

      機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations

      Skills you'll gain: Supervised Learning, Machine Learning, Classification And Regression Tree (CART), Theoretical Computer Science, Applied Mathematics, Mathematical Modeling, Probability & Statistics, Regression Analysis, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      932 reviews

      Beginner · Course · 1 - 3 Months

    • S

      Sungkyunkwan University

      Machine Learning Basics

      Skills you'll gain: Machine Learning Algorithms, Machine Learning, Python Programming, Supervised Learning, Scikit Learn (Machine Learning Library), Applied Machine Learning, Regression Analysis, Data Analysis, Statistical Methods, Linear Algebra, Probability

      4.3
      Rating, 4.3 out of 5 stars
      ·
      73 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      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

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Calculus for Machine Learning and Data Science

      Skills you'll gain: Applied Mathematics, Calculus, Numerical Analysis, Mathematical Modeling, Machine Learning, Python Programming, Regression Analysis, Artificial Neural Networks, Deep Learning, Derivatives

      4.8
      Rating, 4.8 out of 5 stars
      ·
      848 reviews

      Intermediate · Course · 1 - 4 Weeks

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

    • Introduction to Deep Learning & Neural Networks with Keras: IBM
    • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
    • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
    • Introduction to Statistics: Stanford University
    • Linear Algebra for Machine Learning and Data Science: DeepLearning.AI
    • Chinese for Beginners: Peking University
    • Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential: McMaster University
    • English for Career Development: University of Pennsylvania
    • 機器學習基石上 (Machine Learning Foundations)---Mathematical Foundations: National Taiwan University
    • Machine Learning Basics: Sungkyunkwan 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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