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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, 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

    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, 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

    4.4
    Rating, 4.4 out of 5 stars
    ·
    79 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    S

    Simplilearn

    DevOps & Site Reliability Engineering Mastery Certification

    Skills you'll gain: Git (Version Control System), Version Control, DevSecOps, Devops Tools, DevOps, CI/CD, Open Web Application Security Project (OWASP), Continuous Delivery, Infrastructure as Code (IaC), Continuous Integration, Agile Methodology, Secure Coding, Application Security, Continuous Deployment, Kubernetes, Agile Software Development, Terraform, Site Reliability Engineering, Cloud Infrastructure, Multi-Cloud

    Beginner · Specialization · 3 - 6 Months

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

    Coursera

    Deep Learning Engineering

    Skills you'll gain: Model Deployment, PyTorch (Machine Learning Library), Vision Transformer (ViT), Model Evaluation, Transfer Learning, MLOps (Machine Learning Operations), Natural Language Processing, Debugging, Containerization, Kubernetes, Docker (Software), Distributed Computing, Performance Tuning, Applied Machine Learning, Dataflow, Tensorflow, Deep Learning, Cloud Computing, Data Pipelines, Computer Vision

    Advanced · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    W

    Whizlabs

    AWS: Feature Engineering Data Transformation & Integrity

    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

    Intermediate · Course · 1 - 4 Weeks

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

    Coursera

    Embedded Firmware Engineering

    Skills you'll gain: Embedded Software, Real-Time Operating Systems, Embedded Systems, Software Architecture, Pseudocode, Systems Architecture, Software Systems, Hardware Architecture, Computer Hardware, System Programming, Computer Architecture, Software Design, Cross Platform Development, Application Design, Systems Design, Software Design Patterns, Internet Of Things, Systems Integration, Maintainability, Peripheral Devices

    Intermediate · Specialization · 1 - 3 Months

What brings you to Coursera today?

  • Status: New
    New
    Status: Preview
    Preview
    M

    MathWorks

    AI for Engineering: An Overview

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, PyTorch (Machine Learning Library), Large Language Modeling, Retrieval-Augmented Generation, Transfer Learning, Model Evaluation, Computer Vision, Unsupervised Learning, Generative Model Architectures, Generative AI, PySpark, Vision Transformer (ViT), Keras (Neural Network Library), Supervised Learning, Generative AI Agents, Deep Learning, Machine Learning, Python Programming, Data Science

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    22K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • 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 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

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Introduction to Software Engineering

    Skills you'll gain: Software Development Life Cycle, Software Architecture, Software Design, Software Development Methodologies, Software Design Patterns, Development Environment, Unified Modeling Language, Software Engineering, Web Applications, Software Development, Application Deployment, Programming Principles, Front-End Web Development, Back-End Web Development, Python Programming, Software Versioning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    4.6K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    K

    Khalifa University

    Health, Safety, and Environmental (HSE) Engineering

    Skills you'll gain: Environmental Management Systems, Environment Health And Safety, Environmental Monitoring, Accident Reporting, Safety Training, Fire And Life Safety, Accident Prevention, Hazardous Waste Operations And Emergency Response Standard (HAZWOPER), Environmental Regulations, Occupational Health, Environmental Engineering, Environmental Laws, Environmental Resource Management, Risk Management, Risk Management Framework, Environmental Engineering and Restoration, Risk Analysis, Environment and Resource Management, Engineering Management, Engineering

    4.7
    Rating, 4.7 out of 5 stars
    ·
    225 reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    E

    EDUCBA

    Design and Assemble an IC Engine Using SolidWorks

    Skills you'll gain: SolidWorks (CAD), 3D Modeling, Assembly Drawing, Engineering Design Process, Mechanical Design, Computer-Aided Design, Mechanical Engineering, Engineering Drawings, Torque (Physics), Functional Testing

    Beginner · Course · 1 - 4 Weeks

1234…442

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

  • Feature Engineering: Google Cloud
  • AI Workflow: Feature Engineering and Bias Detection: IBM
  • DevOps & Site Reliability Engineering Mastery Certification: Simplilearn
  • Deep Learning Engineering: Coursera
  • AWS: Feature Engineering Data Transformation & Integrity : Whizlabs
  • Embedded Firmware Engineering: Coursera
  • AI for Engineering: An Overview: MathWorks
  • IBM AI Engineering: IBM
  • LLM Engineering That Works: Prompting, Tuning, and Retrieval: Coursera
  • Introduction to Software Engineering: IBM

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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