Data and Digital Analytics(Classroom and Synchronous eLearning)

About This Course

By the end of the course, learners will have a solid understanding of the key concepts, tools, and techniques used in data analytics and able to apply them to real-world problems.
Learners will be able to:

1) Apply statistical computing tools, methods and predictive data modelling techniques to identify underlying patterns and trends in data analytics to convey insights effectively.
2) Identify patterns across multiple data sets and methods to build data model to derive insights.
3) Identify the methods to use data mining to discover new business insights and mine data to find relevant insights for ongoing improvements.
4) Identify the appropriate exploratory visual analysis and predictive modelling techniques to manage interactive visualisations of data and data study outcomes using industry standard tools and techniques in accordance with organisational procedures.
5) Adopt statistical and experimental techniques for aggregation of data to build data models to test hypotheses and validate problem-solving strategies.
6) Identify the methods to interpret patterns in data and their relevance for business issues to make decision about which patterns are meaningful, and which to further analyse.
7) Develop prototype algorithms and proof of concept demonstrations using various methods and techniques to test the data algorithms.
8) Use machine learning techniques to gain new insights from data with the range of established and novel tools and techniques used in developing new business insights.
9) Evaluate the business data presented using complex software tools to determine impact of insights on organisation.
10) Explain the methods to identify and prioritise the problems to be solved in the organisational domains and key business processes.