Free Data Preprocessing Course
Data Preprocessing
4.53
Beginner level
3.0 learning hrs
Learn Data Preprocessing for free through datasets, metrics, and analysis choices, with course examples that show what matters first and how beginners can start using the topic.
About this course
A free data preprocessing course helps you understand why data work starts before charts or machine learning models. Raw datasets often contain missing values, inconsistent formats, duplicates, outliers, and variables measured on different scales. This course introduces the preparation steps that make analysis more reliable, including data gathering, cleaning, transformation, and scaling, so you can judge whether a dataset is ready to use.
The course is useful for learners moving into data science, analytics, or machine learning because preprocessing affects every later result. You will see how collection choices, feature quality, and preparation methods influence model behavior and business interpretation. By the end, you should be able to explain common preprocessing tasks, recognize messy-data risks, and approach a dataset with a clearer sequence before analysis, visualization, or predictive modeling.
Course outline
Introduction to Data Collection
In this module we define data collection and its significance in the context of data analysis.
Definition and Types of Data
In this module we identify different types of data and their characteristics.
Overview and Importance of Data Collection
In this module we understand the importance of data collection in research, business, and various other domains.
Types of Data Collection Methods
In this module we explore various data collection methods and their applications.
Data Collection Tools
In this module we familiarize learners with data collection tools used to gather, store, and manage data.
Ethics in Data Collection
In this module we discuss ethical considerations related to data collection, privacy, and confidentiality.
Best Practices of Data Collection
In this module we introduce best practices for effective and reliable data collection.
Data Collection Summary
In this module we summarize the key concepts and principles of data collection for future reference.
Introduction to Data Preprocessing
This module runs through an overview of what data preprocessing is, why you should consider data preprocessing, and understand the three steps of data preprocessing.
The first things
This module focuses on a case study of data preprocessing using the 2019 FIFA dataset to comprehend the process of data preprocessing using hands-on sessions. You will go through loading libraries and loading and exploring the data.
Basic Summaries for Univariate Data
This module continues with the case study and provides a hands-on session on a basic summary of statistics like mean, median, etc., and their consequences.
Feature Engineering Basics
This module walks you through the basics of feature engineering. You will go through a hands-on session on combining a few more statistics to reduce the dimension and splitting the work rate into two columns.
Variable Scaling
Through the case study, you will learn about standardizing continuous features. You will go through a hands-on session explaining how standard deviation plays its role and comprehend Z and T transformations.
Variable Transformation
This module focuses on log transformation. You will gain hands-on knowledge of how various functions are used for various transformations and how they make a difference.
Missing Value Treatment
This module focuses on missing values. There are many ways of handling missing values, but here you will start by understanding the pattern in the missing values and understand it through hands-on code demonstration.
Binning and Lambda Function
This module gives you hands-on experience in implementing binning and lambda functions. You will understand how the bin function aids continuous features and go through the implementation of the cut function, changing units and making categorical into categorical types.
Correlation Checks for Bivariate Data
This module contains a hands-on session on correlation checks for bivariate data. Through the scatterplot implemented, you will see the representation of the bivariate data.
Outlier Treatment
This module contains a hands-on session focusing on handling outliers. This will help you understand how to replace or adjust the values of extreme outliers in a dataset. In return, it will help you make the data more accurate and prevent outliers from skewing results.
Outlier Identification
This module contains a hands-on session focusing on handling outliers. This will help you understand how to replace or adjust the values of extreme outliers in a dataset. In return, it will help you make the data more accurate and prevent outliers from skewing results.
Let's play more with Text Data
This module helps you understand text processing in-depth through the implementation of various scenarios through the hands-on demonstration.
Encoding Categorical Variables
This module gives you an overview of encoding categorical models and helps you comprehend the process of transforming categorical data into numerical data so that machine learning algorithms can interpret the data and make predictions. You will understand the concept better through the dummy variable encoding technique hands-on implementation.
Data Manipulation on Numerical, Categorical, and Strings
This module contains a hands-on session on processing columns to get a numeric data frame that can be ready for any modeling tasks.
Get access to the complete curriculum once you enroll in the course
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Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
What prerequisites are required to learn this Data Preprocessing course?
Enrolling in this free Data Preprocessing requires no prerequisites, and it is mainly designed for beginners to learn it from scratch.
How should I revise Data Preprocessing after finishing the course?
How long does it take to complete this free Data Preprocessing course?
This free Data Preprocessing course contains 2 hours of self-paced videos that learners can take up according to their convenience.
What learner problem does Data Preprocessing solve?
Will I have lifetime access to this free online course?
Yes. You will have lifetime access to this free online Data Preprocessing course.
What are my next learning options after this Data Preprocessing course?
You can enroll in Great Learning's Applied Data Science MIT Program to gain advanced and crucial Data Science skills and earn a certificate of course completion.
Does Data Preprocessing require prior experience?
How can Data Preprocessing improve interview preparation?
Is it worth learning Data Preprocessing?
Yes, it is worth learning data preprocessing, as it is an essential step in any data analysis process. Data preprocessing is used to prepare raw data for further analysis, and it is necessary to ensure the data is in a usable format. Preprocessing can also help to improve the accuracy of any machine learning algorithms that are used.
Data Preprocessing: what should I practice first?
What is Data Preprocessing used for?
Data preprocessing is preparing data for analysis by cleaning, transforming, and restructuring it into a more easily analyzed format. Preprocessing aims to make data easier to understand and reduce the amount of noise and irrelevant information that can interfere with the analysis. Standard preprocessing techniques include normalization, discretization, feature selection, and data transformation.
Is Data Preprocessing better for beginners or experienced learners?
Why is Data Preprocessing so popular?
Data preprocessing is popular because it improves the data quality and makes it easier to analyze. It also helps to reduce noise and outliers, which can lead to more accurate predictive models. It can reduce the data's complexity and make it easier to understand. It can also reduce the time and resources it takes to analyze data.
What comes after learning Data Preprocessing online?
How does Data Preprocessing connect with real work?
What jobs demand that you learn Data Preprocessing?
There are many jobs that demand that you learn Data Preprocessing, such as:
- Data Analyst
- Data Scientist
- Business Intelligence Analyst
- Data Engineer
- Database Administrator
- Machine Learning Engineer
Will I get a certificate after completing this Data Preprocessing course?
Yes, you will be rewarded with a free Data Preprocessing course completion certificate after completing all the modules and the quiz at the end of this free Data Preprocessing course.
What knowledge and skills will I gain upon completing this Data Preprocessing course?
By the end of this online Data Preprocessing course, you will be familiar with the basics of data preprocessing, feature engineering, variable scaling and transformation, correlation checks for bivariate data, outlier identification and treatment, and encoding categorical variables through hands-on demos.
How much does this Data Preprocessing course cost?
This Data Preprocessing online course is offered for free by Great Learning Academy.
Is there a limit on how many times I can take this online Data Preprocessing course?
No, there are no limits on the number of times you can attain this free Data Preprocessing course.
Can I sign up for multiple courses from Great Learning Academy at the same time?
Yes, you can sign up for more than one free course offered by Great Learning Academy that efficiently helps your career growth.
Why choose Great Learning for this Data Preprocessing course?
Great Learning Academy is an initiative taken by the leading e-learning platform, Great Learning. Great Learning Academy provides you with industry-relevant courses for free, and Data Preprocessing is one of the free courses that empowers you with the data preprocessing techniques essential for accurate data analysis.
Who is eligible to take this free Data Preprocessing course?
Any beginner who wants to learn data preprocessing from the basics can enroll in this free Data Preprocessing course.
What are the steps to enroll in this course?
- Search for the "Data Preprocessing" free course in the search bar present at the top corner of Great Learning Academy.
- Register for the course through the Enroll Now button and start learning.
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