serviços digitais da FCT
Data Preparation
Ref. PREPDAD
Well-prepared data are the foundation of intelligent decisions, quality, rigour and automation to transform information into real value.
- Duration: 6 hours
- Effort: 6 hours
- Pace: Self paced
- Languages: English and portuguese
- 3,117 already enrolled!
What you will learn
- Understand the importance of data quality, identifying at least two practical consequences of poor-quality data in analytical projects.
- Identify at least two techniques for data cleaning and processing.
- Recognise at least two methods of data transformation and data engineering.
- Explore at least two tools or techniques used in data preparation.
Description
This course provides a detailed approach to data preparation, covering data quality, cleaning and processing, transformation and engineering, as well as preparation tools and techniques. Participants will explore topics such as the importance of data quality, methods for detecting and correcting issues, techniques for data transformation and engineering, and popular tools used to automate data preparation processes.
Assessment and certification
At the end of each module, in order to assess your progress, you will take a test with a mandatory knowledge check, which will account for 50% of the final grade.
At the end of the course, you will take a Final Assessment Test, which will account for 50% of the final grade.
Course plan
Part I - Data Quality, Cleaning and Processing
Module 1 - Data Quality
Module 2 – Detecting Quality Issues
Module 3 – Data Cleaning and Processing
Part II - Data Normalisation, Integration and Preparation
Module 4 - Data Normalisation and Standardisation
Module 5 - Data Integration and Consolidation
Part III - Data Transformation and Feature Engineering
Module 6 - Data Transformations
Module 7 – Feature Engineering
Module 8 – Data Preparation for Analytical Models
Part IV - Tools and Automation
Module 9 - Tools for Data Preparation
Module 10 - Automation and Good Practices
Module 1 - Data Quality
Module 2 – Detecting Quality Issues
Module 3 – Data Cleaning and Processing
Part II - Data Normalisation, Integration and Preparation
Module 4 - Data Normalisation and Standardisation
Module 5 - Data Integration and Consolidation
Part III - Data Transformation and Feature Engineering
Module 6 - Data Transformations
Module 7 – Feature Engineering
Module 8 – Data Preparation for Analytical Models
Part IV - Tools and Automation
Module 9 - Tools for Data Preparation
Module 10 - Automation and Good Practices
Organizations
License
License for the course content
Attribution-NonCommercial-NoDerivatives
You are free to:
- Share — copy and redistribute the material in any medium or format
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.