Filter by
SubjectRequired
LanguageRequired
The language used throughout the course, in both instruction and assessments.
Learning ProductRequired
LevelRequired
DurationRequired
SkillsRequired
SubtitlesRequired
EducatorRequired
Results for "using machine learning in science and engineering"
Multiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming
DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Machine Learning, Jupyter, Python Programming, Data Manipulation, Data Science
Imperial College London
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Data Transformation, Jupyter, Data Science, Advanced Mathematics, Statistics, Machine Learning Algorithms, Geometry, Statistical Analysis, Machine Learning Methods, Artificial Neural Networks, Algorithms, Data Manipulation, Mathematical Modeling
DeepLearning.AI
Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Supervised Learning, Keras (Neural Network Library), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Debugging, Performance Tuning, Machine Learning Methods, Python Programming, Data-Driven Decision-Making, Text Mining, Network Architecture
Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), Apache Airflow, Cloud Infrastructure, Artificial Intelligence and Machine Learning (AI/ML), Data Pipelines, Systems Design, Data Management, Data Governance, Hybrid Cloud Computing, Workflow Management, Artificial Intelligence, Application Deployment, Cloud Management, DevOps, Systems Architecture
Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Feature Engineering, Dimensionality Reduction, Data Cleansing, Applied Machine Learning, Data Access, Regression Analysis, Data Analysis, Machine Learning, Statistical Inference, Statistical Hypothesis Testing, Statistical Machine Learning, Data Quality, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Probability & Statistics, Predictive Modeling
Duke University
Skills you'll gain: MLOps (Machine Learning Operations), Pandas (Python Package), AWS SageMaker, NumPy, Microsoft Azure, Unit Testing, Data Ethics, Application Deployment, Data Manipulation, Exploratory Data Analysis, Containerization, Data Pipelines, CI/CD, Software Testing, Data Import/Export, Amazon Web Services, Feature Engineering, Artificial Intelligence and Machine Learning (AI/ML), Docker (Software), Rust (Programming Language)
- Status: New
Skills you'll gain: Generative AI, Data Wrangling, Unit Testing, Supervised Learning, Feature Engineering, Keras (Neural Network Library), Deep Learning, ChatGPT, Natural Language Processing, Data Cleansing, Jupyter, Data Analysis, Unsupervised Learning, Data Manipulation, PyTorch (Machine Learning Library), Artificial Intelligence, Data Import/Export, Data Ethics, Exploratory Data Analysis, Predictive Analytics
University of Washington
Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Text Mining, Machine Learning Algorithms, Big Data, Statistical Inference, Data Cleansing
University of Michigan
Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Unsupervised Learning, Classification And Regression Tree (CART), Dimensionality Reduction, Random Forest Algorithm, Regression Analysis, Artificial Neural Networks
DeepLearning.AI
Skills you'll gain: Supervised Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Feature Engineering, Artificial Intelligence, Classification And Regression Tree (CART), Python Programming, Regression Analysis, Unsupervised Learning, Data-Driven Decision-Making
DeepLearning.AI
Skills you'll gain: Linear Algebra, NumPy, Dimensionality Reduction, Jupyter, Data Manipulation, Data Science, Machine Learning Algorithms, Applied Mathematics, Python Programming
In summary, here are 10 of our most popular using machine learning in science and engineering courses
- Machine Learning: DeepLearning.AI
- Mathematics for Machine Learning and Data Science: DeepLearning.AI
- Mathematics for Machine Learning: Imperial College London
- Deep Learning: DeepLearning.AI
- Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
- IBM Introduction to Machine Learning: IBM
- MLOps | Machine Learning Operations: Duke University
- IBM Generative AI Engineering: IBM
- Machine Learning: University of Washington
- Applied Machine Learning in Python: University of Michigan