Results for "using machine learning in engineering"
Status: NewStatus: Free TrialCoursera
Skills you'll gain: Model Deployment, Natural Language Processing, Debugging, Containerization, Kubernetes, Transfer Learning, Docker (Software), MLOps (Machine Learning Operations), Distributed Computing, Applied Machine Learning, PyTorch (Machine Learning Library), Vision Transformer (ViT), Tensorflow, Cloud Computing, Deep Learning, Performance Tuning, Model Evaluation, Artificial Neural Networks, Data Pipelines, Computer Vision
Status: Free TrialMultiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Transfer Learning, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Data Preprocessing
Status: Free TrialDeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Machine Learning Algorithms, Data Preprocessing, Machine Learning, Machine Learning Methods
Status: Free TrialImperial College London
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives
Status: Free TrialSkills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Classification Algorithms, Regression Analysis, Dimensionality Reduction, Statistical Methods, Data Preprocessing, Applied Machine Learning, Model Evaluation, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Access, Anomaly Detection, Logistic Regression, Scikit Learn (Machine Learning Library), Machine Learning, Machine Learning Algorithms
Status: NewStatus: Free TrialSkills you'll gain: Model Evaluation, Feature Engineering, Data Preprocessing, Financial Data, Predictive Modeling, Customer Demand Planning, Data-Driven Decision-Making, Exploratory Data Analysis, R Programming, Customer Analysis, Predictive Analytics, Profit and Loss (P&L) Management, Risk Modeling, Inventory Management System, Analytics, Advanced Analytics, Supply Chain Management, Business Analytics, Machine Learning, Business
What brings you to Coursera today?
Status: Free TrialSkills you'll gain: Feature Engineering, Model Evaluation, Advanced Analytics, Statistical Machine Learning, Unsupervised Learning, Machine Learning, Data Ethics, Supervised Learning, Decision Tree Learning, Random Forest Algorithm, Classification Algorithms, Python Programming, Performance Tuning
Status: NewStatus: Free TrialSkills you'll gain: Recurrent Neural Networks (RNNs), Model Evaluation, Supervised Learning, Feature Engineering, Transfer Learning, NumPy, Matplotlib, Convolutional Neural Networks, Statistical Methods, Deep Learning, Applied Machine Learning, Data Visualization, Keras (Neural Network Library), Python Programming, Pandas (Python Package), Seaborn, Applied Mathematics, Machine Learning, Machine Learning Algorithms, Tensorflow
Status: Free TrialSkills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Classification Algorithms, Feature Engineering
Status: Free TrialSkills you'll gain: Prompt Engineering, Large Language Modeling, Generative AI, Retrieval-Augmented Generation, Generative Model Architectures, PyTorch (Machine Learning Library), Vector Databases, LLM Application, Generative Adversarial Networks (GANs), Embeddings, Natural Language Processing, Hugging Face, Transfer Learning, Data Pipelines, Recurrent Neural Networks (RNNs), Text Mining, Data Ethics, Data Preprocessing, Artificial Intelligence, Performance Tuning
Status: Free TrialAlberta Machine Intelligence Institute
Skills you'll gain: Supervised Learning, Data Preprocessing, Feature Engineering, Responsible AI, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Model Evaluation, Data Quality, Classification Algorithms, MLOps (Machine Learning Operations), Model Deployment, Jupyter, Data Validation, Machine Learning, Decision Tree Learning, Business Operations, Data Cleansing, Product Lifecycle Management, Project Management
DeepLearning.AI
Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Cloud Deployment, Continuous Deployment, Model Evaluation, Data Preprocessing, Machine Learning, Applied Machine Learning, Data Validation, Feature Engineering, Data Quality, Debugging, Continuous Monitoring, Data Pipelines
In summary, here are 10 of our most popular using machine learning in engineering courses
- Deep Learning Engineering:Â Coursera
- Machine Learning:Â DeepLearning.AI
- Mathematics for Machine Learning and Data Science:Â DeepLearning.AI
- Mathematics for Machine Learning:Â Imperial College London
- IBM Introduction to Machine Learning:Â IBM
- Apply Machine Learning for Predictive Business Analytics:Â EDUCBA
- The Nuts and Bolts of Machine Learning:Â Google
- AI Engineering Masterclass: From Zero to AI Hero:Â Packt
- Machine Learning with Python:Â IBM
- Generative AI Engineering with LLMs:Â IBM
