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    Results for "machine learning"

    • A

      Alberta Machine Intelligence Institute

      Introduction to Applied Machine Learning

      Skills you'll gain: Data Ethics, Applied Machine Learning, Data Processing, Machine Learning, Machine Learning Algorithms, Product Lifecycle Management, Supervised Learning, Data Modeling, Business Requirements, Business Analysis, Unsupervised Learning, Artificial Intelligence, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      739 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      Imperial College London

      Mathematics for Machine Learning: PCA

      Skills you'll gain: Dimensionality Reduction, NumPy, Probability & Statistics, Feature Engineering, Jupyter, Data Science, Statistics, Linear Algebra, Python Programming, Advanced Mathematics, Machine Learning, Calculus

      4
      Rating, 4 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Smart Analytics, Machine Learning, and AI on Google Cloud

      Skills you'll gain: Google Cloud Platform, MLOps (Machine Learning Operations), Tensorflow, Unstructured Data, Applied Machine Learning, Data Pipelines, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Machine Learning, Jupyter, Natural Language Processing

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.2K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Illinois Urbana-Champaign

      Machine Learning for Accounting with Python

      Skills you'll gain: Machine Learning Algorithms, Unsupervised Learning, Scikit Learn (Machine Learning Library), Machine Learning, Text Mining, Applied Machine Learning, Time Series Analysis and Forecasting, Data Processing, Supervised Learning, Predictive Modeling, Python Programming, Regression Analysis, Feature Engineering, Jupyter, Pandas (Python Package), Natural Language Processing, Statistical Analysis, Performance Metric

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      43 reviews

      Intermediate · Course · 1 - 3 Months

    • N

      New York University

      Fundamentals of Machine Learning in Finance

      Skills you'll gain: Supervised Learning, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Machine Learning Algorithms, Decision Tree Learning, Machine Learning, Predictive Modeling, Financial Trading, Financial Market, Reinforcement Learning, Scikit Learn (Machine Learning Library), Correlation Analysis, Exploratory Data Analysis, Portfolio Management, Python Programming, Artificial Neural Networks, Jupyter

      3.7
      Rating, 3.7 out of 5 stars
      ·
      338 reviews

      Intermediate · Course · 1 - 4 Weeks

    • N

      New York University

      Guided Tour of Machine Learning in Finance

      Skills you'll gain: Supervised Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Artificial Neural Networks, Predictive Modeling, Scikit Learn (Machine Learning Library), Regression Analysis, Deep Learning, Financial Services, Finance, Tensorflow, Jupyter, Reinforcement Learning

      3.8
      Rating, 3.8 out of 5 stars
      ·
      679 reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Washington

      Machine Learning: Classification

      Skills you'll gain: Classification And Regression Tree (CART), Applied Machine Learning, Supervised Learning, Predictive Modeling, Text Mining, Machine Learning Algorithms, Data Cleansing, Scalability, Machine Learning, Natural Language Processing, Big Data, Probability & Statistics, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Washington

      Machine Learning: Clustering & Retrieval

      Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Big Data, Statistical Inference, Text Mining, Statistical Modeling, Machine Learning Algorithms, Unstructured Data, Machine Learning, Sampling (Statistics), Scalability, Probability Distribution, Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.4K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Washington

      Machine Learning: Regression

      Skills you'll gain: Regression Analysis, Predictive Modeling, Supervised Learning, Statistical Modeling, Applied Machine Learning, Predictive Analytics, Feature Engineering, Machine Learning, Statistical Methods, Python Programming, Data Manipulation, Linear Algebra, Algorithms

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.6K reviews

      Mixed · Course · 1 - 3 Months

    • T

      The University of Chicago

      Machine Learning: Concepts and Applications

      Skills you'll gain: Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Classification And Regression Tree (CART), Decision Tree Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Supervised Learning, Regression Analysis, Random Forest Algorithm, Dimensionality Reduction, Statistical Methods, Tensorflow, Feature Engineering, Artificial Neural Networks, Pandas (Python Package)

      3.9
      Rating, 3.9 out of 5 stars
      ·
      22 reviews

      Intermediate · Course · 1 - 3 Months

    • A

      Alberta Machine Intelligence Institute

      Machine Learning Algorithms: Supervised Learning Tip to Tail

      Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Jupyter, Machine Learning, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Business Solutions, Python Programming, Regression Analysis, Performance Analysis, Feature Engineering, Data Processing, Performance Metric

      4.7
      Rating, 4.7 out of 5 stars
      ·
      413 reviews

      Mixed · Course · 1 - 4 Weeks

    • D

      Duke University

      Managing Machine Learning Projects

      Skills you'll gain: MLOps (Machine Learning Operations), Data Management, Data Quality, Technical Management, Applied Machine Learning, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), Software Development Life Cycle, Machine Learning, Data Cleansing, Data Pipelines, Technology Solutions, Data Collection, Data Science, Systems Architecture, Feature Engineering, Solution Design, Software Versioning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      245 reviews

      Beginner · Course · 1 - 3 Months

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    1…8910…410

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

    • Introduction to Applied Machine Learning: Alberta Machine Intelligence Institute
    • Mathematics for Machine Learning: PCA: Imperial College London
    • Smart Analytics, Machine Learning, and AI on Google Cloud: Google Cloud
    • Machine Learning for Accounting with Python: University of Illinois Urbana-Champaign
    • Fundamentals of Machine Learning in Finance: New York University
    • Guided Tour of Machine Learning in Finance: New York University
    • Machine Learning: Classification: University of Washington
    • Machine Learning: Clustering & Retrieval: University of Washington
    • Machine Learning: Regression: University of Washington
    • Machine Learning: Concepts and Applications: The University of Chicago

    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

    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!‎

    Yes, Coursera offers a variety of free courses across many topics, including machine learning. While you can access most course materials for free by auditing the courses, this does not include graded assignments or a completion certificate. For those looking to obtain a certificate to showcase their learning or enhance their professional profile, Coursera provides the option to purchase the course. Additionally, Coursera offers free trials or financial aid to learners who qualify, making certifications more accessible to everyone.‎

    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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