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.
120credentials
432courses

Explore the Applied Machine Learning Course Catalog

  • Status: Preview

    Skills you'll gain: Generative AI, Image Analysis, Deep Learning, Generative Model Architectures, Computer Vision, Applied Machine Learning

  • Status: Free Trial

    Skills you'll gain: AWS SageMaker, AWS Kinesis, Data Integration, Data Lakes, Business Intelligence, Apache Hive, Apache Spark, Amazon Web Services, Extract, Transform, Load, Big Data, Apache Hadoop, Real Time Data, Applied Machine Learning, Data Pipelines, Data Processing, Serverless Computing

  • Skills you'll gain: Anomaly Detection, Image Analysis, Google Cloud Platform, Computer Vision, Data Import/Export, Applied Machine Learning, Predictive Modeling, Data Management

  • Skills you'll gain: Feature Engineering, Tensorflow, MLOps (Machine Learning Operations), Data Pipelines, Data Processing, Keras (Neural Network Library), Data Transformation, Applied Machine Learning, Machine Learning, Statistical Methods

  • Status: Free Trial

    Fundação Instituto de Administração

    Skills you'll gain: Customer Relationship Management, Customer Data Management, Big Data, Data Mining, Data-Driven Decision-Making, Predictive Analytics, Sales Management, Ggplot2, Data Visualization Software, Plot (Graphics), Data Modeling, R Programming, Customer Insights, Customer Acquisition Management, Customer experience strategy (CX), Customer Retention, Data Science, Data Analysis, Data Manipulation, Applied Machine Learning

  • Skills you'll gain: Real Time Data, Scalability, Data Pipelines, Applied Machine Learning, MLOps (Machine Learning Operations), Machine Learning

  • Status: New
    Status: Preview

    Skills you'll gain: Supervised Learning, Random Forest Algorithm, Applied Machine Learning, Data Processing, Classification And Regression Tree (CART), Decision Tree Learning, Feature Engineering, Machine Learning Algorithms, Predictive Modeling, Performance Testing, Data Analysis, Scikit Learn (Machine Learning Library), Python Programming

  • Skills you'll gain: Customer Analysis, Predictive Modeling, Predictive Analytics, Analytics, E-Commerce, Big Data, Google Cloud Platform, Applied Machine Learning, Machine Learning Methods, Data Analysis, Statistical Modeling

  • Status: Preview

    Skills you'll gain: Data Ethics, Responsible AI, Machine Learning, Game Theory, Algorithms, Applied Machine Learning, Artificial Intelligence, Predictive Modeling, Data Quality

  • Status: Free Trial

    Skills you'll gain: Google Gemini, Generative AI, Predictive Modeling, Applied Machine Learning, Google Cloud Platform, Big Data, Artificial Intelligence and Machine Learning (AI/ML), SQL, Python Programming, Customer Relationship Management

  • Status: Free Trial

    Skills you'll gain: Google Cloud Platform, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Business Transformation, Responsible AI, Business Intelligence, Data Quality, Machine Learning, Natural Language Processing, Applied Machine Learning, Cloud API, Data Analysis

  • Status: Free Trial

    Skills you'll gain: Apache Spark, Scala Programming, Data Processing, Big Data, Applied Machine Learning, IntelliJ IDEA, Real Time Data, Graph Theory, Data Transformation, Development Environment, Distributed Computing, Build Tools, Regression Analysis, Performance Tuning