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    Results for "machine learning"

    1 active filter
    • Status: Free Trial
      Free Trial

      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
      ·
      35K reviews

      Beginner · Specialization · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      DeepLearning.AI

      Supervised Machine Learning: Regression and Classification

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

      4.9
      Rating, 4.9 out of 5 stars
      ·
      29K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Jupyter, Python Programming, Data Structures, Web Scraping, Data Manipulation, Programming Principles, Pandas (Python Package), Computer Programming, Object Oriented Programming (OOP), Restful API, NumPy, Application Programming Interface (API), Data Analysis, Data Import/Export, File Management

      4.6
      Rating, 4.6 out of 5 stars
      ·
      42K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      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, Jupyter, Data Science, Advanced Mathematics, Statistics, Machine Learning Algorithms, Statistical Analysis, Artificial Neural Networks, Algorithms, Python Programming, Machine Learning, Derivatives

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

      Beginner · Specialization · 3 - 6 Months

    • Status: New
      New

      O.P. Jindal Global University

      Machine Learning

      Skills you'll gain: Tensorflow, Supervised Learning, Scikit Learn (Machine Learning Library), Applied Machine Learning, Python Programming, NumPy, Artificial Neural Networks, Deep Learning, Image Analysis, Matplotlib, Unstructured Data, Predictive Modeling, Machine Learning, Natural Language Processing, Pandas (Python Package), Computer Vision, Feature Engineering, Text Mining, Regression Analysis, Performance Tuning

      Build toward a degree

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial

      IBM

      Introduction to Artificial Intelligence (AI)

      Skills you'll gain: Generative AI, ChatGPT, Natural Language Processing, Market Opportunities

      4.7
      Rating, 4.7 out of 5 stars
      ·
      20K reviews

      Beginner · Course · 1 - 4 Weeks

    What brings you to Coursera today?

    • University of London

      Machine Learning for All

      Skills you'll gain: Feature Engineering, Machine Learning, Data Processing, Artificial Intelligence, Supervised Learning, Data Analysis, Computer Vision, Data Collection

      Build toward a degree

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

      Beginner · Course · 1 - 4 Weeks

    • Status: Free
      Free

      Coursera Project Network

      Machine Learning Pipelines with Azure ML Studio

      Skills you'll gain: Applied Machine Learning, Classification And Regression Tree (CART), Predictive Modeling, Microsoft Azure, Machine Learning, Supervised Learning, Feature Engineering, Data Pipelines, Data Science, Data Analysis, Data Processing, Data Cleansing, Application Deployment

      4.5
      Rating, 4.5 out of 5 stars
      ·
      806 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • IBM

      Machine Learning Introduction for Everyone

      Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Applied Machine Learning, Deep Learning, Supervised Learning, IBM Cloud, Classification And Regression Tree (CART), Predictive Modeling, Unsupervised Learning, Reinforcement Learning, Software Development Life Cycle

      4.5
      Rating, 4.5 out of 5 stars
      ·
      285 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial

      Microsoft

      Generative AI for Data Scientists

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

      4.6
      Rating, 4.6 out of 5 stars
      ·
      49 reviews

      Beginner · Specialization · 1 - 3 Months

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

      IBM

      IBM Data Science

      Skills you'll gain: Dashboard, Data Visualization Software, Data Visualization, SQL, Predictive Modeling, Unsupervised Learning, Plotly, Interactive Data Visualization, Supervised Learning, Exploratory Data Analysis, Jupyter, Data Wrangling, Data Literacy, Data Analysis, Data Mining, Matplotlib, Regression Analysis, Scikit Learn (Machine Learning Library), Generative AI, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      145K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • Status: Free
      Free

      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
      ·
      62 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Machine Learning: DeepLearning.AI
    • Supervised Machine Learning: Regression and Classification : DeepLearning.AI
    • Python for Data Science, AI & Development: IBM
    • Mathematics for Machine Learning: Imperial College London
    • Machine Learning: O.P. Jindal Global University
    • Introduction to Artificial Intelligence (AI): IBM
    • Machine Learning for All: University of London
    • Machine Learning Pipelines with Azure ML Studio: Coursera Project Network
    • Machine Learning Introduction for Everyone: IBM
    • Generative AI for Data Scientists: Microsoft

    Frequently Asked Questions about Machine Learning

    Machine learning courses on Coursera cover a range of essential skills including:

    • Supervised learning and unsupervised learning methodologies
    • Neural networks and deep learning architectures
    • Algorithmic foundations such as regression, classification, and clustering
    • Data preprocessing, feature engineering, and data augmentation techniques
    • Model evaluation and optimization methods
    • Practical applications of machine learning in various industries
    • Implementation of machine learning algorithms using Python and libraries like TensorFlow and PyTorch‎

    Yes. You can start learning machine learning on Coursera for free in two ways:

    • Preview the first module of many machine learning courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
    • Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

    If you want to keep learning, earn a certificate in machine learning, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

    No prior programming experience is required to begin beginner machine learning courses, but having some foundational knowledge in programming (especially Python) can be very beneficial. The curriculum is structured to accommodate learners at all levels:

    • Beginners can start with introductory courses that cover basic programming and data handling.
    • Intermediate learners can advance to applying machine learning algorithms on real data.
    • Advanced professionals can explore specialized areas such as deep learning, reinforcement learning, or natural language processing.‎

    Machine learning courses on Coursera offer a variety of credentialing options:

    • Professional certificates that demonstrate a more comprehensive understanding of machine learning concepts and techniques.
    • Specialized course certificates in areas such as artificial intelligence, data science, or specific technologies like TensorFlow.
    • Certifications from leading tech companies and universities that can help enhance your professional credibility and career prospects.‎

    Skills in machine learning can open doors to numerous high-demand roles in technology and research, including:

    • Machine Learning Engineer
    • Data Scientist
    • AI Research Scientist
    • Robotics Engineer
    • Quantitative Analyst in finance
    • Software Developer specializing in AI
    • Professionals in these roles utilize machine learning techniques to create innovative solutions, improve data-driven decision-making, and push the boundaries of artificial intelligence.

    Discover which machine learning role suits you best by taking our career quiz!‎

    Online learning algorithms are machine learning methods that update models continuously as new data arrives, rather than training on a fixed dataset. They’re useful for real-time applications like fraud detection or recommendation systems. You can explore these concepts in courses like Machine Learning by Stanford University on Coursera, which introduces foundational techniques used in adaptive models.‎

    Causal inference in machine learning focuses on identifying cause-and-effect relationships rather than just correlations. It’s used in fields like healthcare, economics, and policy to make more reliable predictions and decisions. Courses like A Crash Course in Causality: Inferring Causal Effects from Observational Data from the University of Pennsylvania on Coursera offer a strong introduction to these methods.‎

    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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