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    • Machine Learning Andrew Ng

    Andrew Ng Machine Learning Courses Online

    Study machine learning with Andrew Ng for foundational knowledge. Learn about supervised learning, neural networks, and model evaluation.

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    Explore the Andrew Ng Machine Learning Course Catalog

    • Status: Free Trial
      Free Trial
      I

      IBM

      IBM Machine Learning

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

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • D

      DeepLearning.AI

      Machine Learning in Production

      Skills you'll gain: MLOps (Machine Learning Operations), Application Deployment, Continuous Deployment, Software Development Life Cycle, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Applied Machine Learning, Data Validation, Feature Engineering, Data Quality, Debugging, Continuous Monitoring, Data Pipelines

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      I

      IBM

      Python for Data Science, AI & Development

      Skills you'll gain: Jupyter, Automation, Web Scraping, Python Programming, Data Manipulation, Data Import/Export, Scripting, Data Processing, Data Structures, Data Collection, Application Programming Interface (API), Pandas (Python Package), Programming Principles, NumPy, Object Oriented Programming (OOP), Computer Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      41K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Azure Machine Learning

      Skills you'll gain: Unsupervised Learning, Microsoft Azure, Applied Machine Learning, Regression Analysis, Predictive Modeling, Machine Learning Methods, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Artificial Intelligence, Automation, Supervised Learning

      4.5
      Rating, 4.5 out of 5 stars
      ·
      232 reviews

      Beginner · Course · 1 - 4 Weeks

    • 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
      U

      University of Washington

      Machine Learning

      Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      16K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Structuring Machine Learning Projects

      Skills you'll gain: Deep Learning, Applied Machine Learning, Machine Learning, Tensorflow, PyTorch (Machine Learning Library), Debugging, Artificial Intelligence, Keras (Neural Network Library), Data Quality, Performance Tuning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      50K reviews

      Beginner · Course · 1 - 4 Weeks

    • 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

      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
      G

      Google

      The Nuts and Bolts of Machine Learning

      Skills you'll gain: Feature Engineering, Statistical Machine Learning, Advanced Analytics, Predictive Modeling, Unsupervised Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Data Analysis, Performance Tuning, Python Programming

      4.8
      Rating, 4.8 out of 5 stars
      ·
      517 reviews

      Advanced · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      DeepLearning.AI

      Neural Networks and Deep Learning

      Skills you'll gain: Deep Learning, Artificial Neural Networks, Supervised Learning, Artificial Intelligence, Machine Learning, Python Programming, Linear Algebra, Performance Tuning, Calculus

      4.9
      Rating, 4.9 out of 5 stars
      ·
      123K reviews

      Intermediate · 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

    Machine Learning Andrew Ng learners also search

    Python Machine Learning
    Python for Machine Learning
    Mathematics for Machine Learning
    Computational Science
    Machine Learning
    MATLAB
    Applied Machine Learning
    Beginner Machine Learning
    1234…420

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

    • IBM Machine Learning: IBM
    • Machine Learning in Production: DeepLearning.AI
    • Python for Data Science, AI & Development: IBM
    • Microsoft Azure Machine Learning: Microsoft
    • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
    • Machine Learning: University of Washington
    • Structuring Machine Learning Projects: DeepLearning.AI
    • IBM Data Science: IBM
    • TensorFlow 2 for Deep Learning: Imperial College London
    • The Nuts and Bolts of Machine Learning: Google

    Frequently Asked Questions about Machine Learning Andrew Ng

    Advanced machine learning is a field of computer science that looks at how to improve computing power by allowing programs to learn as they run, without additional programming. It is a form of artificial intelligence. Advanced machine learning calls for sophisticated programming that includes statistical analysis and generative adversarial networks to find the best path to learning.‎

    Typical careers that use advanced machine learning are in data engineering, data science, and computer programming. These are fields where work with big data sets is expected to increase. Advanced machine learning is also widely used in algorithmic trading and finance, so people who want to work in financial markets may want to learn it. Advanced machine learning is a field that is expected to grow as more computing environments include some aspects of machine learning. Management careers that involve data analysis, strategic planning, and prediction are easier when the programs can learn about the data involved.‎

    Online courses can help you learn advanced machine learning through courses, Specializations, and Professional Certificates offered by universities and by software companies. Courses in Apache Spark, Keras, TensorFlow, MongoDb, and PySpark, among other packages, can help you learn how machine learning works in specific programming environments. Other classes cover the math and statistics needed to understand the underlying logic. Despite the name, not all courses are at an advanced level, although beginner courses in advanced machine learning call for background knowledge. Specializations and Guided Projects help you demonstrate your knowledge and test what you know.‎

    You'll want to make sure you have a strong foundation of machine learning fundamentals before moving onto advanced concepts and classes. It's helpful to know the fundamentals of scalable data science and mathematics, including linear algebra and multivariate calculus. Programming, especially in Python, is also recommended, as is basic knowledge of SQL. ‎

    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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