Feature Engineering Courses
Feature engineering courses can help you learn techniques for transforming raw data into meaningful features, selecting relevant variables, and creating new features to improve model performance. You can build skills in data preprocessing, handling missing values, and using domain knowledge to enhance feature sets.
Popular Feature Engineering Courses and Certifications
Google Cloud
Skills you'll gain: Feature Engineering, Data Preprocessing, Tensorflow, MLOps (Machine Learning Operations), Data Pipelines, Keras (Neural Network Library), Data Processing, Data Transformation, Data Modeling, Data Store, Real Time Data, Machine Learning, Data Storage
Skills you'll gain: Feature Engineering, Data Ethics, Unsupervised Learning, Dimensionality Reduction, Responsible AI, Text Mining, Data Preprocessing, Data Transformation, MLOps (Machine Learning Operations), Anomaly Detection, Exploratory Data Analysis, Machine Learning Methods, Machine Learning, Model Evaluation, Natural Language Processing, Data Science, Quality Assurance, Data Pipelines, Data Visualization, Python Programming
Skills you'll gain: Feature Engineering, Data Preprocessing, AWS SageMaker, Data Cleansing, Apache Spark, Extract, Transform, Load, Data Pipelines, Data Transformation, Amazon Web Services, Responsible AI, Data Quality, Data Integrity, Amazon S3, Personally Identifiable Information, Data Security
Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Statistical Methods, Data Preprocessing, Statistical Inference, Statistical Hypothesis Testing, Applied Machine Learning, Data Access, Anomaly Detection, Statistical Analysis, Data Analysis, Data Cleansing, Data Manipulation, Data Science, Machine Learning, Probability & Statistics, Data Import/Export
Coursera
Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting, Decision Tree Learning, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling
Skills 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
What brings you to Coursera today?
Multiple 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
Stanford University
Skills you'll gain: Feature Engineering, Healthcare Ethics, Pharmaceuticals, Data Ethics, Clinical Research, Clinical Data Management, Health Systems, Healthcare Industry Knowledge, Clinical Research Ethics, Unstructured Data, Health Care, Model Deployment, Health Informatics, Data Mining, Managed Care, Model Evaluation, Responsible AI, Applied Machine Learning, Machine Learning, Artificial Intelligence
Skills you'll gain: Model Deployment, Model Evaluation, Unsupervised Learning, Transfer Learning, Tensorflow, Keras (Neural Network Library), Dimensionality Reduction, Deep Learning, Recurrent Neural Networks (RNNs), Applied Machine Learning, BeeAI, Data Preprocessing, Convolutional Neural Networks, PyTorch (Machine Learning Library), Responsible AI, Python Programming, Agentic systems, Artificial Intelligence, Artificial Neural Networks, Feature Engineering
Skills you'll gain: Responsible AI, MLOps (Machine Learning Operations), Model Deployment, Feature Engineering, Product Requirements, Prompt Engineering, Data Ethics, Prompt Patterns, LLM Application, Kubernetes, AI Security, Systems Architecture, Large Language Modeling, Software Architecture, Test Automation, Model Evaluation, PyTorch (Machine Learning Library), Apache Airflow, Data Pipelines, SQL
Skills you'll gain: MLOps (Machine Learning Operations), Feature Engineering, AWS Kinesis, Fraud detection, Amazon Web Services, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Cloud Deployment, Data Cleansing, Data Processing, Data Wrangling, Data Integrity, Machine Learning, Machine Learning Algorithms, Data Modeling, Supervised Learning, Data Mining, Random Forest Algorithm, Data Management, Unsupervised Learning
Coursera
Skills you'll gain: Apache Airflow, Data Validation, Image Analysis, Transfer Learning, Data Preprocessing, Data Integrity, Model Evaluation, Debugging, Computer Vision, PyTorch (Machine Learning Library), Data Pipelines, Feature Engineering, MLOps (Machine Learning Operations), Tensorflow, Algorithms, Embeddings, Applied Machine Learning, Performance Tuning, Deep Learning, Digital Signal Processing
In summary, here are 10 of our most popular feature engineering courses
- Feature Engineering: Google Cloud
- AI Workflow: Feature Engineering and Bias Detection: IBM
- AWS: Feature Engineering Data Transformation & Integrity : Whizlabs
- Exploratory Data Analysis for Machine Learning: IBM
- Foundations of Machine Learning: Coursera
- AI Engineering Masterclass: From Zero to AI Hero: Packt
- Machine Learning: DeepLearning.AI
- AI in Healthcare: Stanford University
- AI Engineer Associate: Packt
- LLM Engineering That Works: Prompting, Tuning, and Retrieval: Coursera
