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Data Wrangling and Preprocessing

Data Wrangling and Preprocessing

$200.00
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Course access is prepared after purchase and delivered via email
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Self-paced • Lifetime updates
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Includes a practical, ready-to-use toolkit with implementation templates, worksheets, checklists, and decision-support materials so you can apply what you learn immediately - no additional setup required.
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What does the Data Wrangling and Preprocessing course cover?

Data Wrangling and Preprocessing is covered here in 9 modules: Introduction to Data Wrangling and Preprocessing: Defining data wrangling and preprocessing, Data Import and Export: Understanding data encoding and formatting, Data Cleaning and Preprocessing: Data normalization and scaling and 6 more. The outline lists 35 specific topics, opening with defining data wrangling and preprocessing and closing with receiving a certificate upon completion.

How do you approach Data Wrangling and Preprocessing step by step?

The work is sequenced in 9 stages. It starts with Introduction to Data Wrangling and Preprocessing: Defining data wrangling and preprocessing, moves through Data Import and Export: Understanding data encoding and formatting and Data Cleaning and Preprocessing: Data normalization and scaling, and ends at Final Project and Assessment: Receiving a certificate upon completion.

What is in Module 1 of the Data Wrangling and Preprocessing course?

Module 1 is Introduction to Data Wrangling and Preprocessing: Defining data wrangling and preprocessing. It works through defining data wrangling and preprocessing, understanding the importance of data wrangling and preprocessing, overview of the data wrangling and preprocessing process and 1 more. It sets the vocabulary the remaining 8 modules build on.

How is the Data Wrangling and Preprocessing course delivered?

The Data Wrangling and Preprocessing course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the Data Wrangling and Preprocessing course cost?

The Data Wrangling and Preprocessing course is $199 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

Closely related courses: Data Wrangling Toolkit, Data Preprocessing in Data mining, Data Wrangling in Metadata Repositories, Data Preprocessing in OKAPI Methodology.

More answers: what you get with every course, refund policy, all help answers.

Data Wrangling and Preprocessing Course Curriculum

Welcome to our comprehensive Data Wrangling and Preprocessing course, designed to equip you with the skills and knowledge needed to efficiently handle and preprocess data for analysis and visualization. Upon completion of this course, participants will receive a certificate, demonstrating their expertise in data wrangling and preprocessing.



Course Overview

This interactive and engaging course provides a personalized learning experience, with expert instructors guiding you through real-world applications and hands-on projects. Our high-quality content is up-to-date, practical, and comprehensive, ensuring that you gain actionable insights and skills that can be applied immediately.



Course Features

  • Interactive and Engaging: Learn through interactive lessons, quizzes, and hands-on projects.
  • Comprehensive: Covering all aspects of data wrangling and preprocessing.
  • Personalized: Tailored learning experience with expert instructors.
  • Up-to-date: Stay current with the latest tools, techniques, and methodologies.
  • Practical: Focus on real-world applications and hands-on projects.
  • High-quality Content: Expertly crafted lessons and materials.
  • Expert Instructors: Guiding you every step of the way.
  • Certification: Receive a certificate upon completion.
  • Flexible Learning: Learn at your own pace, anytime, anywhere.
  • User-friendly: Easy-to-use interface and navigation.
  • Mobile-accessible: Learn on-the-go, on any device.
  • Community-driven: Connect with peers and instructors through our community forum.
  • Actionable Insights: Gain practical skills and knowledge that can be applied immediately.
  • Hands-on Projects: Apply your skills to real-world projects and scenarios.
  • Bite-sized Lessons: Learn in manageable, bite-sized chunks.
  • Lifetime Access: Enjoy lifetime access to course materials and updates.
  • Gamification: Engage with our interactive gamification elements to stay motivated.
  • Progress Tracking: Track your progress and stay on top of your learning.


Course Outline

Module 1. Introduction to Data Wrangling and Preprocessing: Defining data wrangling and preprocessing

  • Defining data wrangling and preprocessing
  • Understanding the importance of data wrangling and preprocessing
  • Overview of the data wrangling and preprocessing process
  • Introduction to key tools and technologies

Module 2. Data Import and Export: Understanding data encoding and formatting

  • Importing data from various sources (e.g., CSV, Excel, JSON)
  • Exporting data to various formats (e.g., CSV, Excel, JSON)
  • Understanding data encoding and formatting
  • Handling missing values and data quality issues

Module 3. Data Cleaning and Preprocessing: Data normalization and scaling

  • Handling missing values and data quality issues
  • Data normalization and scaling
  • Data transformation and feature engineering
  • Handling outliers and anomalies

Module 4. Data Transformation and Feature Engineering: Creating new features through data transformation

  • Introduction to data transformation and feature engineering
  • Handling categorical variables and encoding schemes
  • Creating new features through data transformation
  • Using techniques such as PCA and t-SNE for dimensionality reduction

Module 5: Handling Missing Values and Data Quality Issues

  • Understanding the impact of missing values on analysis and modeling
  • Strategies for handling missing values (e.g., mean, median, imputation)
  • Techniques for detecting and handling data quality issues (e.g., outliers, duplicates)
  • Using data validation and data cleansing techniques

Module 6. Data Visualization and Exploration: Understanding data distributions and relationships

  • Introduction to data visualization and exploration
  • Using visualization tools (e.g., Matplotlib, Seaborn, Plotly)
  • Understanding data distributions and relationships
  • Using visualization to identify patterns and trends

Module 7. Advanced Data Wrangling and Preprocessing Techniques: Handling large datasets and big data

  • Using regular expressions for data cleaning and preprocessing
  • Using techniques such as data masking and data anonymization
  • Handling large datasets and big data
  • Using distributed computing and parallel processing techniques

Module 8: Case Studies and Real-World Applications

  • Real-world examples of data wrangling and preprocessing in action
  • Case studies of successful data wrangling and preprocessing projects
  • Applying data wrangling and preprocessing to different domains (e.g., finance, healthcare, marketing)
  • Best practices and lessons learned from real-world applications

Module 9. Final Project and Assessment: Receiving a certificate upon completion

  • Applying data wrangling and preprocessing skills to a real-world project
  • Final assessment and evaluation of skills and knowledge
  • Receiving a certificate upon completion
Join our Data Wrangling and Preprocessing course today and gain the skills and knowledge needed to efficiently handle and preprocess data for analysis and visualization. Upon completion, you'll receive a certificate, demonstrating your expertise in data wrangling and preprocessing.

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