DATA ANALYTICS CONTINUES WITH ME

In today’s highly dynamic business environment, companies in virtually every industry are looking to transform data into actionable business insights. Having the suitable data and analytical skills provides an unbeatable edge. This course provides an overview of intermediate concepts and tools one will need throughout the data science pipeline, so as to prepare participants for tackling data analytics challenges. It builds on the foundations gained in Data Analytics Begins with Me. Throughout the two-day course, participants will learn about the main concepts and tools in a data scientist’s toolbox. We will first revisit the basic analytical methods that have been covered in Data Analytics Begins with Me and learn about how to further improve them. We will then introduce intermediate machine learning models and algorithms, such as principal component analysis and textual analysis. The goal is to better understand trends and, ultimately, translate data into actionable knowledge. To demonstrate the application of these algorithms and reinforce the skills attained, there will be a focus on practical methods that leverage on the data analytics software, Orange. During the hands-on sessions, we will walk through the best practices in data analytics. Participants will also be introduced to basic Python scripting to extend the functionalities of the software. At the end of the course, participants will be able to: - Understand the best practices for data science workflows - Acquire a deeper understanding of the basic machine learning models to gain additional insights into your data - Learn about intermediate machine learning models and algorithms, including regression, classification, clustering, principal component analysis, and text analysis. - Apply these learning models through hands-on sessions - Analyze datasets that hold real-world implication