Statistical Machine Learning

Statistical Machine Learning is a subset of artificial intelligence that leverages statistical techniques to enable machines to improve at tasks. Coursera's Statistical Machine Learning catalogue equips you with the ability to develop and apply predictive algorithms based on statistical concepts. You'll learn to build models, interpret results, and make predictions using machine learning techniques. Further, you'll gain an understanding of various statistical learning methods such as regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. This skill set can be used in various fields like data science, finance and banking, healthcare, retail, and more where predictive analysis is crucial.

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Results for "Statistical Machine Learning"

  • Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Statistical Machine Learning, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms

  • Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Probability, Statistical Inference, Statistics, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Correlation Analysis, Histogram, Statistical Visualization, Box Plots

  • Skills you'll gain: Anomaly Detection, Feature Engineering, Fraud detection, Unsupervised Learning, Continuous Monitoring, Autoencoders, MLOps (Machine Learning Operations), Machine Learning Methods, Statistical Machine Learning, Model Training, Time Series Analysis and Forecasting, System Monitoring, Applied Machine Learning, Model Deployment, Statistical Analysis, Taxonomy

  • Skills you'll gain: Supervised Learning, Model Optimization, PyTorch (Machine Learning Library), Fine-tuning, Generative Model Architectures, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Generative AI, Deep Learning, Model Training, Applied Machine Learning, Statistical Machine Learning, Classification And Regression Tree (CART), Autoencoders, Machine Learning Methods, Machine Learning Software, Machine Learning, MLOps (Machine Learning Operations), Machine Learning Algorithms, Artificial Intelligence and Machine Learning (AI/ML)

  • Skills you'll gain: Statistical Machine Learning, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Statistical Modeling, Python Programming, Supervised Learning, Machine Learning, Agentic systems, Artificial Intelligence, Model Optimization, Algorithms, AI literacy

  • Skills you'll gain: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Convolutional Neural Networks, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Statistical Inference

  • Skills you'll gain: Generative AI, Prompt Engineering, AI literacy, Artificial Intelligence, Deep Learning, Statistical Machine Learning

  • Skills you'll gain: Investment Management, Portfolio Management, Text Mining, Portfolio Risk, Applied Machine Learning, Asset Management, Network Analysis, Investments, Data Visualization Software, Machine Learning Methods, Return On Investment, Statistical Machine Learning, Financial Statement Analysis, Financial Data, Market Data, Financial Management, Unstructured Data, Predictive Modeling, Web Scraping, Risk Management

  • University of Washington

    Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Applied Machine Learning, Machine Learning Methods, Feature Engineering, Machine Learning, Image Analysis, Machine Learning Algorithms, AI Personalization, Unsupervised Learning, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Machine Learning, Model Training, Logistic Regression, Statistical Modeling, Data Mining

  • University of London

    Skills you'll gain: Model Training, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Feature Engineering, Machine Learning, Artificial Intelligence, Statistical Machine Learning, Model Evaluation, Data Literacy, Machine Learning Algorithms, AI literacy, Data Ethics, Data Collection

  • Skills you'll gain: Responsible AI, LLM Application, AI literacy, AI Product Strategy, Deep Learning, Statistical Machine Learning

  • University of Colorado Boulder

    Skills you'll gain: Reinforcement Learning, Deep Learning, Machine Learning Methods, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Markov Model, Artificial Intelligence, Responsible AI, Computational Logic, Machine Learning Algorithms, AI Workflows, Agentic systems, Decision Intelligence, Statistical Machine Learning, Applied Machine Learning, Artificial Neural Networks, Model Optimization, Theoretical Computer Science, Algorithms, Applied Mathematics