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  • Advanced Machine Learning

Results for "advanced machine learning"


  • Status: Free Trial
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    G

    Google Cloud

    Advanced Machine Learning on Google Cloud

    Skills you'll gain: Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Hybrid Cloud Computing, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Pandas (Python Package)

    4.5
    Rating, 4.5 out of 5 stars
    ·
    1.5K reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    D
    S

    Multiple educators

    Machine Learning

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Responsible AI, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming

    4.9
    Rating, 4.9 out of 5 stars
    ·
    37K reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Advanced Machine Learning Techniques

    Skills you'll gain: Data Processing

    Intermediate · Course · 1 - 3 Months

  • 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, 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, Big Data

    4.6
    Rating, 4.6 out of 5 stars
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    16K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    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, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Machine Learning, Machine Learning Methods, Data Transformation

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

    Intermediate · Specialization · 1 - 3 Months

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

    University of Pennsylvania

    AI and Machine Learning Essentials with Python

    Skills you'll gain: Statistical Machine Learning, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Deep Learning, Probability Distribution, Python Programming, Supervised Learning, Statistics, Machine Learning Methods, Machine Learning, Regression Analysis, Data Processing, Agentic systems, Data Science, Artificial Intelligence, Artificial Neural Networks, Algorithms

    4.5
    Rating, 4.5 out of 5 stars
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    40 reviews

    Intermediate · Specialization · 3 - 6 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Advanced Learning Algorithms

    Skills you'll gain: Classification And Regression Tree (CART), Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Responsible AI, Supervised Learning, Deep Learning, Random Forest Algorithm, Artificial Neural Networks, Performance Tuning

    4.9
    Rating, 4.9 out of 5 stars
    ·
    8.5K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google

    The Nuts and Bolts of Machine Learning

    Skills you'll gain: Feature Engineering, Applied Machine Learning, Advanced Analytics, Machine Learning, Unsupervised Learning, Workflow Management, Data Ethics, Supervised Learning, Data Validation, Classification And Regression Tree (CART), Random Forest Algorithm, Decision Tree Learning, Python Programming, Performance Tuning

    4.8
    Rating, 4.8 out of 5 stars
    ·
    580 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Deep Learning

    Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Tensorflow, Generative AI, Supervised Learning, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Keras (Neural Network Library), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, MLOps (Machine Learning Operations), Debugging, Performance Tuning, Python Programming, Data-Driven Decision-Making

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    147K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Applied Machine Learning

    Skills you'll gain: Computer Vision, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Regression Analysis, Data Processing, Machine Learning, Predictive Modeling, Data Mining, Data Cleansing, Statistical Machine Learning, Deep Learning, Artificial Neural Networks, Decision Tree Learning

    3.5
    Rating, 3.5 out of 5 stars
    ·
    14 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    A

    Alberta Machine Intelligence Institute

    Machine Learning: Algorithms in the Real World

    Skills you'll gain: Supervised Learning, Feature Engineering, Responsible AI, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Data Quality, Data Processing, MLOps (Machine Learning Operations), Jupyter, Data Validation, Machine Learning, Business Operations, Data Cleansing, Product Lifecycle Management, Machine Learning Methods, Ethical Standards And Conduct, Classification And Regression Tree (CART), Test Data, Project Management

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.1K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Applied Machine Learning in Python

    Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Dimensionality Reduction, Random Forest Algorithm, Regression Analysis

    4.6
    Rating, 4.6 out of 5 stars
    ·
    8.6K reviews

    Intermediate · Course · 1 - 4 Weeks

Searches related to advanced machine learning

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1234…673

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

  • Advanced Machine Learning on Google Cloud: Google Cloud
  • Machine Learning: DeepLearning.AI
  • Advanced Machine Learning Techniques: Coursera
  • Machine Learning: University of Washington
  • Mathematics for Machine Learning and Data Science: DeepLearning.AI
  • AI and Machine Learning Essentials with Python: University of Pennsylvania
  • Advanced Learning Algorithms: DeepLearning.AI
  • The Nuts and Bolts of Machine Learning: Google
  • Deep Learning: DeepLearning.AI
  • Applied Machine Learning: Johns Hopkins University

Frequently Asked Questions about Advanced Machine Learning

It depends on your learning style and whether you want to focus more on theory or hands-on skills using Python:

  • The original Supervised Machine Learning: Regression and Classification course is great if you want a deep, math-focused understanding of ML algorithms and don’t mind using Octave/MATLAB.
  • The Machine Learning Specialization is better if you want modern, Python-based training that’s more applied and modular.
  • If you’re not a developer or want to understand what machine learning is and how it impacts work and society, start with AI For Everyone—Andrew Ng’s non-technical introduction to AI concepts, business use cases, and ethical considerations.
  • Interested in building real-world applications with language models like ChatGPT? Consider ChatGPT Prompt Engineering for Developers (Guided Project) by DeepLearning.AI and OpenAI—it’s a fast, practical way to understand LLM behavior and prompt design. ‎

Try Andrew Ng's Machine Learning Specialization for learners who want to use practical tools right away. ‎

A course teaches one focused topic—offering concise, standalone learning experiences.

  • Machine Learning (Octave/MATLAB; foundational algorithms and math)
  • AI For Everyone (non-technical intro to AI impacts and strategy)
  • Neural Networks and Deep Learning (part of a larger specialization)

A Specialization is a curated series of courses—designed to build expertise through a structured progression.

  • Machine Learning Specialization (3 courses; Python-based, covering supervised & unsupervised methods)
  • Deep Learning Specialization (5 courses; focused on neural networks, CNNs, RNNs, and project structure)

A Professional Certificate is a career-ready program—often including hands-on projects and aligned with industry roles.

  • DeepLearning.AI TensorFlow Developer Professional Certificate (covers TensorFlow, model building, deployment workflows) ‎

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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