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    Results for "advanced machine learning"

    • F

      Fractal Analytics

      Advanced Machine Learning Algorithms

      Skills you'll gain: Feature Engineering, Machine Learning Algorithms, Random Forest Algorithm, Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Classification And Regression Tree (CART), Supervised Learning, Predictive Modeling, Decision Tree Learning, Performance Tuning, Regression Analysis

      3.6
      Rating, 3.6 out of 5 stars
      ·
      8 reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Alberta

      Reinforcement Learning

      Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Simulations, Solution Architecture, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Supervised Learning, Algorithms, Performance Testing, Artificial Neural Networks, Pseudocode, Linear Algebra, Probability Distribution, Debugging

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

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      A

      Amazon Web Services

      Fundamentals of Machine Learning and Artificial Intelligence

      Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, Artificial Intelligence, AWS SageMaker, Amazon Web Services, Applied Machine Learning, Machine Learning, Digital Transformation

      4.5
      Rating, 4.5 out of 5 stars
      ·
      390 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free
      Free
      C

      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 Processing, Data Cleansing, Application Deployment

      4.5
      Rating, 4.5 out of 5 stars
      ·
      801 reviews

      Beginner · Guided Project · Less Than 2 Hours

    • D

      DeepLearning.AI

      Mathematics for Machine Learning and Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Python Programming, Jupyter, Data Manipulation

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.7K reviews

      Intermediate · Specialization · 1 - 3 Months

    • D

      Duke University

      MLOps | Machine Learning Operations

      Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Data Ethics, Application Deployment, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, Software Testing, Data Import/Export, Amazon Web Services, Feature Engineering, Cloud Solutions, Artificial Intelligence and Machine Learning (AI/ML), Docker (Software), Rust (Programming Language)

      4.2
      Rating, 4.2 out of 5 stars
      ·
      449 reviews

      Advanced · Specialization · 3 - 6 Months

    • 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 Structures, Data Processing, 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: 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
      ·
      142K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • 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

    • G

      Google

      Google Advanced Data Analytics

      Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Statistical Hypothesis Testing, Data Ethics, Data Presentation, Data Visualization Software, Sampling (Statistics), Regression Analysis, Feature Engineering, Data Transformation, Descriptive Statistics, Data Visualization, Tableau Software, Data Manipulation, Statistical Analysis, Probability Distribution, Statistical Methods, Applied Machine Learning, Object Oriented Programming (OOP), Data Analysis

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6K reviews

      Advanced · Professional Certificate · 3 - 6 Months

    • Status: New AI skills
      New AI skills
      G

      Google

      Google Data Analytics

      Skills you'll gain: Data Storytelling, Data Literacy, Data Visualization, Data Presentation, Data Ethics, Rmarkdown, Interactive Data Visualization, Interviewing Skills, Data Cleansing, Data Validation, Ggplot2, Tableau Software, Presentations, Spreadsheet Software, Data Analysis, Data Visualization Software, Stakeholder Communications, Dashboard, Sampling (Statistics), R Programming

      Build toward a degree

      4.8
      Rating, 4.8 out of 5 stars
      ·
      167K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • I

      IBM

      Introduction to Artificial Intelligence (AI)

      Skills you'll gain: Large Language Modeling, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Deep Learning, Artificial Neural Networks, Governance, Prompt Engineering, Machine Learning, Automation, Digital Transformation, Business Transformation, Business Technologies, Ethical Standards And Conduct, Computer Vision, Emerging Technologies, Natural Language Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      19K reviews

      Beginner · Course · 1 - 4 Weeks

    Searches related to advanced machine learning

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    1234…501

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

    • Advanced Machine Learning Algorithms: Fractal Analytics
    • Reinforcement Learning: University of Alberta
    • Fundamentals of Machine Learning and Artificial Intelligence: Amazon Web Services
    • Machine Learning Pipelines with Azure ML Studio: Coursera Project Network
    • Mathematics for Machine Learning and Data Science: DeepLearning.AI
    • MLOps | Machine Learning Operations: Duke University
    • Python for Data Science, AI & Development: IBM
    • IBM Data Science: IBM
    • Machine Learning: University of Washington
    • Google Advanced Data Analytics: Google

    Frequently Asked Questions about Advanced Machine Learning

    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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