7 Best Feature Engineering Courses You Should Check

Best Feature Engineering Courses

Are you looking for Best Feature Engineering Courses? If yes, then this article is for you. In this article, you will find the 7 Best Feature Engineering Courses from various platforms. These feature engineering courses will help you to learn the process of feature engineering.

So give few minutes and find out the best feature engineering courses for you. Now without any further ado, let’s get started-

Best Feature Engineering Courses

1. Feature Engineering– Coursera

Rating- 4.5/5

Time to Complete- 18 hours

Provider- Google Cloud

This course is offered by Google Cloud. In this course, you will understand what makes a good feature and how to represent them in your Machine learning model.

You will also learn pre-processing and feature creation. These are data processing techniques that can help you prepare a feature set for a machine learning system.

This course also covers feature crosses and TensorFlow Transform. TensorFlow Transform is a library for preprocessing data with TensorFlow. 

Extra Benefits-

  1. You will earn a Shareable Certificate.
  2. Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

  • Those who have previous programming experience.

Interested to Enroll?

If yes, then check out the details here- Feature Engineering

2. Feature Engineering for Machine Learning in Python– DataCamp

Time to Complete- 4 hours

This is another best course to learn feature engineering. In this 4 hours long course, you will learn feature engineering fundamentals and how to create new features from both categorical and continuous columns using the pandas package.

This course also teaches how to deal with messy data and how to deal with skewed data and situations where outliers may be negatively impacting your analysis.

In this course, you will work with unstructured text data.

Who Should Enroll?

  • Those who know Data Manipulation with pandas and Supervised learning.

Interested to Enroll?

If yes, then check out the details here- Feature Engineering for Machine Learning in Python

3. Feature Engineering for Machine Learning– Udemy

Rating- 4.7/5

Time to Complete- 10.5 hours

In this Udemy course, you will learn various techniques for missing data imputation and how to deal with infrequent, rare, and unseen categories.

You will also learn how to convert your numerical variables into discrete intervals, how to remove outliers, how to handle date and time variables, how to work with different time zones, and how to handle mixed variables which contain strings and numbers.

Extra Benefits-

  • You will get a Certificate of Completion.
  • Along with that, you will get lifetime access to the course material.

Who Should Enroll?

  • Those who have some experience with Numpy and Pandas and familiar with Machine Learning algorithms and Scikit-Learn.

Interested to Enroll?

If yes, then check out the details here- Feature Engineering for Machine Learning

4. Data Processing and Feature Engineering with MATLAB– Coursera

Rating- 4.7/5

Time to Complete- 18 hours

Provider- MathWorks

In this course, you will merge data from different data sets and handle common scenarios, such as missing data. At the beginning of the course, you will explore different types of distributions and calculate quantities like the skewness and interquartile range.

Then you will learn how to prepare data for analysis and how to clean messy data. In the last module, you will create and evaluate features using time-based signals such as accelerometer data from a cell phone. 

Extra Benefits-

  1. You will earn a Shareable Certificate.
  2. Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

  • Those who have domain knowledge and some exposure to computational tools.
  • Some background in basic statistics and Exploratory Data Analysis with MATLAB is also good.

Interested to Enroll?

If yes, then check out the details here- Data Processing and Feature Engineering with MATLAB

5. Feature Engineering in R– Datacamp

Time to Complete- 4 hours

This course use R programming for feature engineering. In this course, you will learn how to change categorical features into numerical representations and a one-hot encoding technique.

This course also teaches how to work with dates in the context of feature engineering. You will learn transformation techniques, like Box-Cox and Yeo-Johnson.

In the last module, you will learn feature crossing to create features from two or more variables and principal component analysis.

Who Should Enroll?

  • Those who have prior knowledge of Exploratory Data Analysis in R.

Interested to Enroll?

If yes, then check out the details here- Feature Engineering in R

6. Feature Engineering with PySpark– Datacamp

Time to Complete- 4 hours

This is another feature engineering course by Datacamp. In this course, you will learn how to prepare and clean data and how to create new features for your machine learning model. Then you will learn how to build a machine learning model and how to evaluate the model.

Who Should Enroll?

  • Those who have prior knowledge PySpark and Supervised learning.

Interested to Enroll?

If yes, then check out the details here- Feature Engineering with PySpark

7. Feature Engineering– Kaggle

This course is available on Kaggle. In this course, you will learn the feature engineering process. Throughout this course, you will learn how to identify important features with mutual information.

You will also invent new features in several real-world problem domains and create segmentation features with k-means clustering.

At the end of this course, you can apply your knowledge in the feature engineering project for the House Prices – Advanced Regression Techniques competition.

Who Should Enroll?

  • Those who have Intermediate level Machine Learning knowledge.

Interested to Enroll?

If yes, then check out the details here- Feature Engineering

And here the list ends. I hope these Best Feature Engineering Courses will help you to learn feature engineering. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up.

Conclusion

In this article, I tried to cover the 7 Best Feature Engineering Courses. If you have any doubt or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

Thank YOU!

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