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  2. Feature Engineering

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


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  • E

    Edureka

    Feature Engineering and Feature Stores for AI and ML

    Skills you'll gain: Feature Engineering, Apache Airflow, Databricks, MLOps (Machine Learning Operations), Data Pipelines, AI Orchestration, Data Lakes, Apache Spark, Data Store, AI Workflows, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), Test Data, Data Transformation, Machine Learning, Data Collection, SQL, Data Storage, Machine Learning Algorithms, Warehouse Management

    Advanced · Course · 1 - 4 Weeks

    Category: New
    New
    Status: Free trial
    Free trial
  • M

    Microsoft

    Ranking Models & Feature Engineering

    Skills you'll gain: Model Training, Feature Engineering, Model Evaluation, Model Optimization, Databricks, MLOps (Machine Learning Operations), Deep Learning, PyTorch (Machine Learning Library), Model Deployment, Redis, Embeddings, Data Science, Data Pipelines, Real Time Data, Data Analysis, Computer Science, Software Development

    Advanced · Course · 1 - 3 Months

    Category: New
    New
    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, Data Transformation, Exploratory Data Analysis, Machine Learning Methods, Machine Learning, Scikit Learn (Machine Learning Library), Natural Language Processing, Data Science, Quality Assurance, Data Pipelines, Machine Learning Algorithms, Design Thinking, Python Programming

    4.4 stars, 87 reviews, Advanced, Course, 1 - 4 Weeks

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

    Status: Free trial
    Free trial
  • S

    Scrimba

    AI Engineering

    Skills you'll gain: Model Context Protocol, Prompt Engineering, Retrieval-Augmented Generation, LangChain, OpenAI API, Embeddings, Image Analysis, Responsible AI, AI Workflows, OpenAI, LLM Application, AI Integrations, Cloud Deployment, Memory Management, Hugging Face, Generative AI, Application Deployment, AI powered creativity, Vector Databases, Software Engineering

    4.5 stars, 442 reviews, Intermediate, Specialization, 3 - 6 Months

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

    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 Quality, Data Integrity, Data Validation, Personally Identifiable Information

    Intermediate · Course · 1 - 4 Weeks

    Status: Free trial
    Free trial
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  • G

    Google Cloud

    Feature Engineering en Español

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

    4.4 stars, 37 reviews, Intermediate, Course, 1 - 3 Months

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

    Status: Free trial
    Free trial
  • P

    Packt

    Prompt to Agent Engineering: The Next AI Skill

    Skills you'll gain: Prompt Engineering, Responsible AI, Multimodal Prompts, AI Workflows, Agentic systems, AI Personalization, Generative AI, Generative AI Agents, AI literacy, Context Engineering, ChatGPT, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Goal Setting, Verification And Validation

    Intermediate · Course · 1 - 3 Months

    Category: New
    New
  • D

    Dassault Systèmes

    CATIA - Perform as a Mechanical Designer

    Skills you'll gain: Computer Aided Three-Dimensional Interactive Application (CATIA), Drafting and Engineering Design, Mechanical Design, Engineering Drawings, Issue Tracking, Technical Drawing, Assembly Drawing, 3D Modeling, Computer-Aided Design, Mechanical Drawings, Collaborative Software, Document Management, Microsoft Office, Workflow Management, Innovation, Product Development, Engineering Analysis

    4.1 stars, 22 reviews, Beginner, Specialization, 1 - 3 Months

    ★ 4.1 (22) · Beginner · Specialization · 1 - 3 Months

    Status: Free trial
    Free trial
  • E

    Edureka

    Data Engineering for AI and ML Pipelines

    Skills you'll gain: Feature Engineering, Databricks, Data Engineering, PySpark, Data Lakes, Apache Airflow, Apache Spark, Data Pipelines, MLOps (Machine Learning Operations), Data Architecture, Data Processing, Artificial Intelligence and Machine Learning (AI/ML), Data Management, Data Storage, Python Programming, Artificial Intelligence, Machine Learning, SQL, Machine Learning Algorithms, Warehouse Management

    Beginner · Specialization · 1 - 3 Months

    Category: New
    New
    Status: Free trial
    Free trial
  • U

    University of Michigan

    AI for Mechanical Engineers

    Skills you'll gain: Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), AI powered creativity, Precision Medicine, Generative AI, Machine Learning, AI literacy, Artificial Intelligence, Machine Learning Algorithms, Transfer Learning, Control Systems, Image Analysis, Robotics, Deep Learning, Computer Vision, Medical Imaging, Reinforcement Learning, Bioinformatics, Drug Development, Applied Machine Learning

    4.5 stars, 217 reviews, Intermediate, Specialization, 1 - 3 Months

    ★ 4.5 (217) · Intermediate · Specialization · 1 - 3 Months

    Status: Free trial
    Free trial
  • I

    IBM

    IBM AI Engineering

    Skills you'll gain: Prompt Engineering, Apache Spark, Large Language Modeling, Retrieval-Augmented Generation, PyTorch (Machine Learning Library), Computer Vision, Unsupervised Learning, Generative Model Architectures, Generative AI, Model Optimization, Keras (Neural Network Library), Supervised Learning, LLM Application, Generative AI Agents, Model Evaluation, Vector Databases, Fine-tuning, Machine Learning, Python Programming, Data Science

    4.6 stars, 22K reviews, Intermediate, Professional Certificate, 3 - 6 Months

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

    Status: Top AI program
    Top AI program
    Status: Free trial
    Free trial
  • I

    IBM

    Generative AI for Data Scientists

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Generative AI, Exploratory Data Analysis, Data Ethics, ChatGPT, AI literacy, Feature Engineering, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Responsible AI, Data Science, Data Synthesis, Machine Learning, Data Analysis

    4.7 stars, 12K reviews, Intermediate, Specialization, 1 - 3 Months

    ★ 4.7 (12K) · Intermediate · Specialization · 1 - 3 Months

    Status: Free trial
    Free trial
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Best Feature Engineering courses from IBM

Top-rated Feature Engineering courses offered by IBM on Coursera.

  1. 1
    AI Workflow: Feature Engineering and Bias Detection
    IBMAdvanced1 - 4 Weeks4.4(87)IBM
  2. 2
    IBM AI Engineering
    IBMIntermediate3 - 6 Months4.6(22,359)IBM
  3. 3
    Generative AI for Data Scientists
    IBMIntermediate1 - 3 Months4.7(12,296)IBM

Best Feature Engineering certificate programs

Earn a certificate in Feature Engineering from top universities and companies.

  1. 1
    AI Engineering
    ScrimbaIntermediate3 - 6 Months4.5(442)Specialization
  2. 2
    CATIA - Perform as a Mechanical Designer
    Dassault SystèmesBeginner1 - 3 Months4.1(22)Specialization
  3. 3
    Data Engineering for AI and ML Pipelines
    EdurekaBeginner1 - 3 Months4.0(2)Specialization

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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