Applied Machine Learning

Applied Machine Learning is a multidisciplinary approach to constructing algorithms that can learn from and predict future data. Coursera's Applied Machine Learning catalogue provides you with the necessary knowledge and skills to effectively use machine learning in a range of practical applications. You'll learn how to process and analyze large-scale data, build predictive models using supervised and unsupervised learning techniques, and apply these models to real-world problems such as image and speech recognition, autonomous driving, and predictive analytics. Enhance your problem-solving abilities and gain a competitive edge in fields like data science, artificial intelligence, and software engineering by mastering machine learning techniques such as decision trees, neural networks, regression, and clustering.
119credentials
431courses

Explore the Applied Machine Learning Course Catalog

  • Skills you'll gain: Big Data, Analytics, Data Analysis, Applied Machine Learning, MLOps (Machine Learning Operations), Google Cloud Platform, Machine Learning, Predictive Modeling, SQL

  • Skills you'll gain: MLOps (Machine Learning Operations), Data Processing, Google Cloud Platform, Data Modeling, Data Management, Data Storage, Data Import/Export, Applied Machine Learning, Scalability

  • Status: Preview

    University of Maryland, College Park

    Skills you'll gain: Pay Per Click Advertising, Marketing Analytics, Search Engine Optimization, Analytics, Big Data, Google Analytics, Digital Marketing, Search Engine Marketing, Paid media, Web Analytics, Web Analytics and SEO, Online Advertising, Digital Advertising, Marketing Effectiveness, A/B Testing, Applied Machine Learning, Marketing Automation, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML)

  • Skills you'll gain: Large Language Modeling, Semantic Web, Generative AI, Artificial Intelligence, Google Cloud Platform, Applied Machine Learning, Natural Language Processing, Algorithms

  • Skills you'll gain: Data Ethics, Responsible AI, Applied Machine Learning, MLOps (Machine Learning Operations), Machine Learning, Software Visualization, Data Integrity, Artificial Intelligence

  • Status: Free Trial

    Skills you'll gain: Keras (Neural Network Library), Tensorflow, Generative Model Architectures, Natural Language Processing, Machine Learning Methods, Applied Machine Learning, Deep Learning, Artificial Neural Networks, Text Mining

  • Skills you'll gain: Predictive Analytics, Big Data, Predictive Modeling, Advanced Analytics, Analytics, Applied Machine Learning, Google Cloud Platform, MLOps (Machine Learning Operations), Data Analysis, Machine Learning Methods, Data Modeling

  • Status: New
    Status: Preview

    Skills you'll gain: Feature Engineering, SAS (Software), Classification And Regression Tree (CART), Predictive Modeling, Statistical Modeling, Regression Analysis, Predictive Analytics, Applied Machine Learning, Statistical Methods, Data Processing, Data Manipulation, Data Cleansing, Data Transformation, Statistical Analysis, Exploratory Data Analysis

  • Skills you'll gain: Google Gemini, Customer Relationship Management, Generative AI, Applied Machine Learning, Big Data, Predictive Modeling, Artificial Intelligence, Query Languages, Data Analysis

  • University of Colorado Boulder

    Skills you'll gain: Data Mining, Unsupervised Learning, Supervised Learning, Deep Learning, Machine Learning Algorithms, Statistical Modeling, Probability, Statistical Inference, Service Level, Performance Testing, Statistical Hypothesis Testing, Dimensionality Reduction, Applied Machine Learning, Data Warehousing, Data Pipelines, Data Processing, Software Engineering, Data Science, Bash (Scripting Language), Statistical Methods

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