Data Analytics

Course Overview

We anticipate you will have heard of Data Science (DS) and Artificial Intelligence (AI), but will probably not have direct, hands-on experience. Given that these topics and their applications are quite broad, the course will focus on the development of each and how they are being and can be applied in various industries.

We will cover the building blocks of Algorithms, including Correlations and Regressions and how to approach a business problem from a data analysis perspective. The participants will get hands on experience working with models and will gain an appreciation of the underlying principles and applications of DS and AI.

The end result will not be that the participants will become practical masters (programmers), but that they will gain some hands-on experience and will understand the rationale and thought process for using Data Science and AI at their desks and in their departments.

Learning Objectives

At the end of the course, the participants will be able to:

• Describe the Growth of Data and Data Analytics.
• Name the 5-Vs of Data and their importance.
• Perform single & multiple regressions and discuss the importance of correlations.
• Develop and use a regression to estimate a Descriptive and Predictive outcome.
• Explain the importance of Visualisation and create graphics that communicate key findings.
• Discuss various Data Analytics models, including Distributed Databases (DDB) and their management systems (DDBMS).
• Describe the development of Artificial Intelligence (AI) and Machine Learning (ML).
• Perform a basic Artificial Neural Network (ANN) analysis and model results.
• Describe the use of Layers in ANN applications and relate to Filters & Sorts in Excel.
• Examine various online services for Data Analytics.
• Perform a Final Case study in cross-functional teams to recommend Data solutions to real, existing business problems.