Data science is an interdisciplinary field that uses statistical modelling to uncover patterns in data that lead to key insights about businesses and their operations, and can test how changes to particular variables will influence markets, performance and other factors.
Data scientists write programs to model organisational and experimental data, and so must also master real-world business and organisational-based scenarios to be able to evaluate the performance of their models.
On completing this course you will have a good idea of what data scientists do, and understand how your organisation can take advantage of data analysis and machine learning.
Who is it for?
Executives who need to get up to speed quickly with key points of importance in data science; entrepreneurs who want to use fact-driven analysis to optimise their resource-use and make better decisions.
Certificates are awarded on the following basis:
- Certificate of completion: Cumulative average of 80% in online tests
- Certificate of participation: Cumulative average of 50%-79% for online tests
- Certificate of attendance: Cumulative average of less than 50% for online tests
You will emerge from this course knowing:
- How data science affects society;
- The value of data – and who owns it;
- What the IT sector around the world is doing to protect data;
- What an efficient data scientist does;
- The life cycle of a data science project;
- Sources of data and collection methods;
- Mathematical terms frequently used in data science;
- How data is classified and analysed;
- Machine learning techniques;
- How to manage your data science team;
And knowing the importance of:
- Data ethics;
- Data security; and
- Data privacy.
You will cover
Key terms and mathematics in data science; establishing a data science team and managing it; structuring a data science project from data gathering, analysis and visualisation to feature engineering; bias and variance trade off; A/B testing; model deployment and retraining; data ethics, privacy and ownership.
- Basic understanding of algebra and geometry;
- Basic knowledge of statistical and mathematical terms; and
- A grasp of the role data plays in business.
- Project manager; product manager; presales and sales executive; directors; software architect; business analyst.