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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


  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Feature Engineering

    Skills you'll gain: Feature Engineering, Data Preprocessing, Model Optimization, Dataflow, Tensorflow, Data Pipelines, Keras (Neural Network Library), Data Processing, Data Transformation, Applied Machine Learning, Data Modeling, Data Store, Real Time Data, Machine Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    1.8K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    AI Workflow: Feature Engineering and Bias Detection

    Skills you'll gain: Feature Engineering, Data Ethics, Unsupervised Learning, Dimensionality Reduction, Responsible AI, Text Mining, Data Preprocessing, Data Transformation, Anomaly Detection, Exploratory Data Analysis, Machine Learning, Scikit Learn (Machine Learning Library), Natural Language Processing, Data Science, Quality Assurance, Data Pipelines, Machine Learning Algorithms, Classification Algorithms, Design Thinking, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    80 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Train ML Models

    Skills you'll gain: Random Forest Algorithm, Model Evaluation, Feature Engineering, Model Training, Applied Machine Learning, Supervised Learning, Geospatial Mapping, Predictive Modeling, Image Analysis, Verification And Validation, Data Science, Environmental Engineering

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Exploratory Data Analysis for Machine Learning

    Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Statistical Methods, Data Preprocessing, Statistical Inference, Statistical Hypothesis Testing, Data Processing, Applied Machine Learning, Data Access, Statistics, Statistical Analysis, Data Analysis, Data Cleansing, Data Manipulation, Data Science, Data Wrangling, Machine Learning, Probability & Statistics, Data Import/Export, Data Transformation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.6K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    C

    Coursera

    Foundations of Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Model Training, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Machine Learning Software, Dimensionality Reduction, Machine Learning, Predictive Modeling, Data Wrangling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting

    4.5
    Rating, 4.5 out of 5 stars
    ·
    15 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    G

    Google Cloud

    Feature Engineering en Español

    Skills you'll gain: Feature Engineering, Data Preprocessing, Dataflow, Tensorflow, Data Transformation, Data Processing, Data Store, Keras (Neural Network Library), Machine Learning Methods, Statistical Machine Learning, Data Modeling, Classification Algorithms, Machine Learning, Python Programming, Statistical Methods

    4.4
    Rating, 4.4 out of 5 stars
    ·
    37 reviews

    Intermediate · Course · 1 - 3 Months

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    W

    Whizlabs

    AWS: Feature Engineering Data Transformation & Integrity

    Skills you'll gain: Feature Engineering, Data Preprocessing, Data Cleansing, Apache Spark, Extract, Transform, Load, Data Processing, Data Pipelines, Data Transformation, Amazon Web Services, Data Wrangling, Responsible AI, Data Quality, Data Integrity, Data Validation, Model Training, Personally Identifiable Information

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Train, Tune, & Ship: End-to-End Machine Learning Engineering

    Skills you'll gain: Model Training, Fine-tuning, Model Evaluation, Model Optimization, Machine Learning Methods, Predictive Modeling, Tensorflow, Statistical Machine Learning, Machine Learning Software, MLOps (Machine Learning Operations), Computer Vision, Performance Testing, Transfer Learning, Feature Engineering, Scikit Learn (Machine Learning Library), Verification And Validation, Network Architecture, Deep Learning, Benchmarking, PyTorch (Machine Learning Library)

    Intermediate · Specialization · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    B

    Board Infinity

    Apply AI & Machine Learning to Financial Forecasting

    Skills you'll gain: Financial Forecasting, Feature Engineering, Model Evaluation, Applied Machine Learning, Statistical Machine Learning, Forecasting, Machine Learning Methods, Machine Learning, Machine Learning Algorithms, Financial Data, Predictive Modeling, Financial Modeling, Advanced Analytics, Decision Intelligence, Generative AI, Risking, Time Series Analysis and Forecasting, Market Data, Regression Analysis, Data Preprocessing

    Beginner · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    LLM Engineering That Works: Prompting, Tuning, and Retrieval

    Skills you'll gain: Responsible AI, MLOps (Machine Learning Operations), Model Optimization, Model Deployment, Feature Engineering, Product Requirements, Prompt Engineering, Data Ethics, Prompt Patterns, LLM Application, Model Training, Kubernetes, AI Security, Systems Architecture, Large Language Modeling, Model Evaluation, PyTorch (Machine Learning Library), Apache Airflow, Data Pipelines, SQL

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    G

    Google Cloud

    Machine Learning Operations (MLOps) on Google Cloud

    Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Model Deployment, AI Orchestration, AI Workflows, Generative AI, Google Cloud Platform, Data Modeling, Continuous Monitoring, Data Pipelines, Model Training, Feature Engineering, Model Optimization, DevOps, Agentic Workflows, Generative AI Agents, Data Store, Continuous Deployment, Forecasting, Metadata Management

    4
    Rating, 4 out of 5 stars
    ·
    496 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Statistical Thinking & Predictive Modeling

    Skills you'll gain: Descriptive Statistics, Data Analysis, Predictive Modeling, Predictive Analytics, Data Literacy, Statistical Modeling, Business Analytics, Statistical Hypothesis Testing, Exploratory Data Analysis, Data-Driven Decision-Making, Customer Analysis, Statistical Machine Learning, Data Science, Model Evaluation, Scikit Learn (Machine Learning Library), Statistical Analysis, Feature Engineering, Data Visualization, Statistical Inference, Supervised Learning

    Intermediate · Course · 1 - 3 Months

1234…25

In summary, here are 10 of our most popular feature engineering courses

  • Feature Engineering: Google Cloud
  • AI Workflow: Feature Engineering and Bias Detection: IBM
  • Train ML Models: Coursera
  • Exploratory Data Analysis for Machine Learning: IBM
  • Foundations of Machine Learning: Coursera
  • Feature Engineering en Español: Google Cloud
  • AWS: Feature Engineering Data Transformation & Integrity : Whizlabs
  • Train, Tune, & Ship: End-to-End Machine Learning Engineering: Coursera
  • Apply AI & Machine Learning to Financial Forecasting: Board Infinity
  • LLM Engineering That Works: Prompting, Tuning, and Retrieval: Coursera

Skills you can learn in Machine Learning

Python Programming (33)
Tensorflow (32)
Deep Learning (30)
Artificial Neural Network (24)
Big Data (18)
Statistical Classification (17)
Reinforcement Learning (13)
Algebra (10)
Bayesian (10)
Linear Algebra (10)
Linear Regression (9)
Numpy (9)

Frequently Asked Questions about Feature Engineering

Feature engineering is the process of using domain knowledge to extract features from raw data, making it suitable for machine learning models. It plays a crucial role in improving model performance by transforming data into a format that algorithms can understand. Effective feature engineering can lead to better predictions and insights, making it a vital skill in data science and analytics.‎

Jobs in feature engineering typically include roles such as data scientist, machine learning engineer, and data analyst. These positions often require a strong understanding of data manipulation and modeling techniques, as well as the ability to work with large datasets. Companies across various industries seek professionals who can enhance their data-driven decision-making processes.‎

To excel in feature engineering, you should develop skills in data analysis, programming (especially in Python or R), and familiarity with machine learning algorithms. Understanding statistical methods and data visualization techniques is also beneficial. Additionally, knowledge of tools and libraries such as Pandas, NumPy, and Scikit-learn can enhance your capabilities in this field.‎

Some of the best online courses for feature engineering include Feature Engineering and AWS: Feature Engineering Data Transformation & Integrity. These courses provide practical insights and hands-on experience, helping you build a solid foundation in feature engineering.‎

Yes. You can start learning feature engineering on Coursera for free in two ways:

  1. Preview the first module of many feature engineering courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in feature engineering, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn feature engineering, start by taking introductory courses that cover the basics of data science and machine learning. Engage in hands-on projects to practice your skills. Additionally, participating in online forums and communities can provide support and resources as you progress in your learning journey.‎

Typical topics covered in feature engineering courses include data preprocessing, feature selection, feature extraction, and techniques for handling missing data. Courses may also explore the impact of feature engineering on model performance and provide case studies to illustrate real-world applications.‎

For training and upskilling employees in feature engineering, consider programs like the IBM AI Engineering Professional Certificate and the DeepLearning.AI Data Engineering Professional Certificate. These professional certificates offer comprehensive training that can enhance the skills of your workforce.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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