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

  • Status: Preview

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Applied Machine Learning, Generative AI, Machine Learning Methods, Deep Learning, Natural Language Processing

  • Status: Preview

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

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    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 Analysis, Big Data, Applied Machine Learning, Statistical Inference, Google Cloud Platform, Machine Learning Methods, SQL

  • Skills you'll gain: Data Ethics, Responsible AI, Data Analysis, Data Visualization Software, Artificial Intelligence, Machine Learning, Applied Machine Learning

  • Status: Free Trial

    University of Minnesota

    Skills you'll gain: Predictive Analytics, Simulations, Exploratory Data Analysis, Experimentation, Research Design, Business Analytics, Operations Research, Project Design, Customer Analysis, A/B Testing, Data Mining, Business Analysis, Analytical Skills, Ideation, Advanced Analytics, Applied Machine Learning, Design Thinking, Process Mapping, Problem Solving, Critical Thinking

  • Status: Preview

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

  • 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

  • Status: Preview

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

  • 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

    Skills you'll gain: Machine Learning Methods, Applied Machine Learning, Artificial Neural Networks, Text Mining, Natural Language Processing