Advanced Certificate in Data Analytics in Digital Economy Module 2: Data Collection and Preprocessing Techniques (Synchronous E-Learning)
About This Course
Module 2 provides an in-depth understanding of the fundamental concepts and techniques for collecting and preprocessing data in the context of data analytics within the digital economy. The module covers various methods for acquiring, cleaning, and transforming raw data into a format suitable for analysis. Participants will learn about different types of data sources, such as structured and unstructured data, as well as strategies for handling missing or inconsistent data. participants will explore advanced preprocessing techniques including normalisation, feature scaling, dimensionality reduction, and outlier detection. Through hands-on exercises and case studies, participants will gain practical experience in applying these techniques to real-world datasets.
What You'll Learn
• Understand the importance of data collection and preprocessing in the context of data analytics within the digital economy
• Demonstrate proficiency in selecting appropriate data collection methods and tools for types of data sources, including structured and unstructured data
• Apply various techniques for cleaning, transforming, and integrating raw datasets to ensure accuracy, consistency, and completeness for analysis
• Evaluate the impact of different preprocessing techniques on downstream analytical processes such as machine learning models or statistical analysis
• Develop practical skills in using popular software tools and programming languages to implement effective data collection and preprocessing workflows for real-world business scenarios within the digital economy context
Entry Requirements
Nil