Data Science

This course enables students to model and interpret data. With a comprehensive combination of theory and practice, you will learn how to construct, analyse and present integrated data sets and deliver valuable insights for their organisations.

• Duration: 12 weeks plus final assessment
  
• Delivery Mode: Online
  

BENEFITS

The course introduces you to Data Science concepts, principles of statistical analysis, data interpretation and visualisation techniques, aspects of probability models, data cleaning and manipulation, pattern recognition and learning and statistical methods.

Students will use Python programming language to solve work-based big data problems, learn how to classify data sets into structured, semi- structured and unstructured data and apply their own code to work with this data. 

WHAT YOU WILL LEARN

• Introduction to Python Programming/ Machine Learning/Plot types
• Data scraping, parsing and down- sampling
• Data set fusion, filtering, slicing and dicing
• Schema validation and reconciliation
• Data manipulation, array programming, data frame
• Sources of data problems
• Co-occurrence grouping of data
• Statistical distribution fitting/ statistical significance of fitting
• Statistics
• Python Programming

On completion of this course, you will have created the following assets:

• A variety of Python programmes
• A selection of Data Science models for specific data sets

ASSIGNMENTS & ASSESSMENT

Assignments are centred on work-based business challenges.