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  • Unsupervised Learning

Unsupervised Learning Courses

Unsupervised learning courses can help you learn clustering techniques, dimensionality reduction, and anomaly detection. You can build skills in data preprocessing, feature extraction, and interpreting complex datasets. Many courses introduce tools like Python libraries such as Scikit-learn and TensorFlow, that support implementing these methods in projects. You'll also explore practical applications in areas like customer segmentation, image processing, and recommendation systems, enhancing your ability to derive insights from unlabelled data.

Popular Unsupervised Learning Courses and Certifications


  • Status: Free Trial
    Free Trial
    I

    IBM

    AI Workflow: Feature Engineering and Bias Detection

    Skills you'll gain: Feature Engineering, Data Ethics, Unsupervised Learning, Dimensionality Reduction, Responsible AI, Text Mining, Data Preprocessing, Data Transformation, Anomaly Detection, Exploratory Data Analysis, Machine Learning, Scikit Learn (Machine Learning Library), Natural Language Processing, Data Science, Quality Assurance, Data Pipelines, Machine Learning Algorithms, Classification Algorithms, Design Thinking, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    82 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Pearson

    Learning Deep Learning: Unit 1

    Skills you'll gain: Deep Learning, Convolutional Neural Networks, PyTorch (Machine Learning Library), Recurrent Neural Networks (RNNs), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Generative AI, Model Training, Model Optimization, Machine Learning Algorithms, Network Performance Management, Network Architecture

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    L

    LearnQuest

    Neural Networks and Random Forests

    Skills you'll gain: Model Evaluation, Random Forest Algorithm, Model Optimization, Keras (Neural Network Library), Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Decision Tree Learning, Machine Learning Methods, Applied Machine Learning, Predictive Modeling, Fine-tuning, Scikit Learn (Machine Learning Library), Regression Analysis, Classification Algorithms, Python Programming

    3.2
    Rating, 3.2 out of 5 stars
    ·
    18 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Advanced Machine Learning with R: Apply & Predict

    Skills you'll gain: Dimensionality Reduction, R Programming, Time Series Analysis and Forecasting, Statistical Machine Learning, Machine Learning Algorithms, Applied Machine Learning, Unsupervised Learning, Predictive Modeling, Machine Learning, Text Mining, Classification Algorithms, Artificial Neural Networks, Forecasting, Data Mining, Data Preprocessing, Model Optimization, Model Evaluation, Exploratory Data Analysis

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    Deep Learning: Convolutional Neural Networks with TensorFlow

    Skills you'll gain: Transfer Learning, Keras (Neural Network Library), Fine-tuning, Embeddings, Deep Learning, Image Analysis, Artificial Neural Networks, Computer Vision, Natural Language Processing, Data Preprocessing, Model Optimization, Model Training

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Unsupervised Text Classification for Marketing Analytics

    Skills you'll gain: Unsupervised Learning, Unstructured Data, Marketing Analytics, Text Mining, Deep Learning, Model Evaluation, Machine Learning, JSON, Data Processing, Natural Language Processing, Data Preprocessing, Model Training, Python Programming

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Packt

    Exploratory Data Analysis & Core ML Algorithms

    Skills you'll gain: Exploratory Data Analysis, Model Optimization, Model Training, Applied Machine Learning, Predictive Modeling, Decision Tree Learning, Data Analysis, Regression Analysis, Classification Algorithms, Supervised Learning, Machine Learning Algorithms, Data Wrangling, Model Evaluation, Data Preprocessing, Statistical Machine Learning, Feature Engineering

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    P

    Pearson

    Learning Deep Learning: Unit 2

    Skills you'll gain: Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Convolutional Neural Networks, Tensorflow, Transfer Learning, Natural Language Processing, Embeddings, Image Analysis, Deep Learning, Computer Vision, Artificial Neural Networks, Model Training, Time Series Analysis and Forecasting, Generative Model Architectures, Network Architecture

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    P

    Packt

    Foundations of Model Optimization and Deep Learning

    Skills you'll gain: Convolutional Neural Networks, Model Optimization, Model Evaluation, Keras (Neural Network Library), Image Analysis, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Computer Vision, Model Training, Dimensionality Reduction, PyTorch (Machine Learning Library), Tensorflow, Machine Learning Methods, Performance Tuning, Artificial Intelligence, Bayesian Statistics

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Introduction to Machine Learning in Sports Analytics

    Skills you'll gain: Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Model Evaluation, Machine Learning Methods, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Machine Learning Software, Analytics, Decision Tree Learning, Machine Learning, Logistic Regression, Data Analysis, Data Analysis Software, Classification Algorithms, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    27 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    N

    Northeastern University

    Statistical Learning for Engineering Part 2

    Skills you'll gain: PyTorch (Machine Learning Library), Applied Machine Learning, Unsupervised Learning, Reinforcement Learning, Supervised Learning, Machine Learning Algorithms, Machine Learning Methods, Dimensionality Reduction, Statistical Machine Learning, Machine Learning, Machine Learning Software, Convolutional Neural Networks, Artificial Neural Networks, Deep Learning, Decision Tree Learning, Classification Algorithms, Autoencoders, Predictive Modeling, Model Optimization

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    M

    Maven Analytics

    Complete Visual Guide to Machine Learning

    Skills you'll gain: Unsupervised Learning, Model Evaluation, Regression Analysis, Exploratory Data Analysis, Model Training, Applied Machine Learning, Time Series Analysis and Forecasting, Data Analysis, Model Optimization, Classification Algorithms, Statistical Analysis, Data Science, Machine Learning Methods, Forecasting, Statistical Methods, Data Preprocessing, Data Mining, Machine Learning, Supervised Learning, Business Intelligence

    Beginner · Course · 1 - 3 Months

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

  • AI Workflow: Feature Engineering and Bias Detection: IBM
  • Learning Deep Learning: Unit 1: Pearson
  • Neural Networks and Random Forests: LearnQuest
  • Advanced Machine Learning with R: Apply & Predict: EDUCBA
  • Deep Learning: Convolutional Neural Networks with TensorFlow: Packt
  • Unsupervised Text Classification for Marketing Analytics: University of Colorado Boulder
  • Exploratory Data Analysis & Core ML Algorithms: Packt
  • Learning Deep Learning: Unit 2: Pearson
  • Foundations of Model Optimization and Deep Learning: Packt
  • Introduction to Machine Learning in Sports Analytics: University of Michigan

Skills you can learn in Machine Learning

Python Programming (33)
Tensorflow (32)
Deep Learning (30)
Artificial Neural Network (24)
Big Data (18)
Statistical Classification (17)
Reinforcement Learning (13)
Algebra (10)
Bayesian (10)
Linear Algebra (10)
Linear Regression (9)
Numpy (9)

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