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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


  • G

    Google Cloud

    Feature Engineering

    ★ 4.5 (1.8K) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    AI Workflow: Feature Engineering and Bias Detection

    ★ 4.4 (80) · Advanced · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • C

    Coursera

    Deep Learning Engineering

    Advanced · Specialization · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • G

    Google Cloud

    Feature Engineering en Español

    ★ 4.4 (37) · Intermediate · Course · 1 - 3 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • W

    Whizlabs

    AWS: Feature Engineering Data Transformation & Integrity

    Intermediate · Course · 1 - 4 Weeks

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • M

    MathWorks

    Electrified Systems Design Engineer

    ★ 4.8 (78) · Beginner · Professional Certificate · 3 - 6 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered

What brings you to Coursera today?

  • C

    Coursera

    Embedded Firmware Engineering

    Intermediate · Specialization · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • S

    Scrimba

    AI Engineering

    ★ 4.5 (348) · Intermediate · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • I

    IBM

    IBM AI Engineering

    ★ 4.6 (22K) · Intermediate · Professional Certificate · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Build toward a degree
    Build toward a degree
  • G

    Google Cloud

    Machine Learning on Google Cloud

    ★ 4.4 (3.8K) · Intermediate · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • A

    Arizona State University

    Human Factors & Usability Engineering: Designing for Humans

    ★ 4.8 (53) · Intermediate · Specialization · 3 - 6 Months

    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
  • L

    LearnKartS

    Agentic AI Engineering: RAG, MCP & MERN

    Beginner · Specialization · 1 - 3 Months

    Category: New
    New
    Status: Free Trial
    Free Trial
    Category: Credit offered
    Credit offered
1234…273

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

  • Feature Engineering: Google Cloud
  • AI Workflow: Feature Engineering and Bias Detection: IBM
  • Deep Learning Engineering: Coursera
  • Feature Engineering en Español: Google Cloud
  • AWS: Feature Engineering Data Transformation & Integrity : Whizlabs
  • Electrified Systems Design Engineer: MathWorks
  • Embedded Firmware Engineering: Coursera
  • AI Engineering: Scrimba
  • IBM AI Engineering: IBM
  • Machine Learning on Google Cloud: Google Cloud

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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