| Domain Area | Course | Duration | Description |
Analytics and Modelling (Choose 1 out of 3 modules from this category to complete this domain area) | Analytics and Computational Modelling | 2 Days / 16 Hours | This course will equip participants with the ability to identify and utilise appropriate advanced statistical, machine learning, computational algorithms and data models to test hypotheses and derive patterns or solutions. |
| Data Analytics Using R | 2 Days / 16 Hours | This course will explore the strengths of the ‘R’ programming language, in numerical data preparation, analysis and modelling via case studies. Participants will be provided with a broad understanding of data analytic processes and the tools used. By the end of the course, participants will better appreciate analytical processes and use data tools to perform a broad spectrum of analytical operations. |
| Data Analysis Using Python | 2 Days / 16 Hours | This course aims to introduce participants to Python, a general purpose programming language commonly used in data science by companies to gain insights from harvested data for competitive advantage. Participants will learn ways to import, scrape, store and manipulate data as well as Python libraries and data science tools common used for data analysis. |
Business Needs Analysis | Business Needs Analysis - a Data-Driven Approach | 2 Days / 16 Hours | This course will enable participants to conduct a thorough, meaningful, and actionable business needs analysis using Data Analytics skills thus enabling successful Data and Analytics initiatives |
Data Engineering (Choose 1 out of 2 modules from this category to complete this domain area) | Data Engineering for effective Data Analytics | 2 Days / 16 Hours | This course will enable participants to learn about database concepts, architectural design patterns necessary for building data warehousing solutions. Additionally they also learn best practices and methodologies in data acquisition, integration, effective storage and transformation of data for analytical purposes and downstream applications |
| Introduction to Data Engineering | 2 Days / 16 Hours | No course date available yet |
Data Visualization (Choose 1 out of 3 modules from this category to complete this domain area) | Data Visualization with Qlik | 2 Days / 16 Hours | This course will enable participants to understand how data visualization can aid data analysis to gain insights more effectively. |
| Data Visualization with Tableau | 2 Days / 16 Hours | This course aims to equip participants with the skills to easily create useful and interactive visualizations and dashboards for presentation and recommendations to stakeholders. They will learn how to achieve this using Tableau software. |
| Visual Analytics using Power BI | 2 Days / 14 Hours | This course will enable participants to develop a dashboard that answers the problem question, use available functions and features to develop dashboard, learn to organize and plan items in a dashboard, provide insights, and make informed decisions. |
Data Strategy (Choose 1 out of 2 modules from this category to complete this domain area) | Strategies for effective Data and Information Management | 2 Days / 16 Hours | This course will provide an overview of core data management capabilities necessary to enable an environment in which the full potential of data can be realised. This course will enable participants to understand the drivers and benefits of good data management, and provide an overview of people, processes and technology |
| Fundamentals of Data Architecture, Governance and Strategy | 2 Days / 16 Hours | This course aims to introduce participants to key concepts, terminology and characteristics of Big Data and the promise it holds to deliver sophisticated business insights. Besides examining current approaches to enterprise data warehousing and business intelligence, the course also discuss the importance of data governance and strategy in view of the external influences enterprises are exposed to due to Big Data. Participants will also learn to appreciate how Big Data storage and analysis resources can be used in conjunction with corporate performance monitoring tools to broaden the analytic capabilities of the enterprise and deepen the insights delivered by Business Intelligence. |
