Reference no: EM132865020 , Length: word count:2600
CS5811 Distributed Data Analysis - Brunel University
Assessment - Distributed Data Analysis
LO1: Design and implement a data analytics solution for generating value and insight from the processing of heterogeneous data using statistical learning and distributed computing technologies.
LO2: Critically evaluate and reflect on the appropriate use of methods and technologies for distributed data analysis, their ability to deliver accurate predictions and the value and limitations of prediction.
a) Identifying a data analytics problem and formulating a relevant research question and plan [LO2]
b) Preparing, integrating and exploring multiple data sets suitable to answer the research question [LO1]
c) Implementing and executing a complete and coherent data analysis [LO1]
d) Critically reflecting on the results of the data analysis (accuracy, limitations and interpretation) [LO2]
A clearly written scientific report including all required sections and demonstrating:
a) correct definition of the problem and formulation of the research question
b) basic data preparation and dataset integration
c) correct application of one machine learning method and one HPC technique
d) Authorship Contribution statement and reflection on the accuracy of the results
All the requirements for a D-grade plus evidence of:
a) consistent structure of the whole data analysis driven by the research question
b) use of graphical analysis to gain insight on the data sets at exploratory level
c) effective use of performance evaluation for methods comparison
d) attempt to provide an interpretation of the results and discussing limitations
All the requirements for a C-grade plus evidence of:
a) clearly presented justification for most of the data analysis steps
b) use of at least one unsupervised learning method for exploratory data analysis
c) effective use of HPC techniques in combination with a data analysis method
d) understanding of the results in the context of the research question
All the requirements for a B-grade plus evidence of:
a) well formulated storytelling about the data across the report and inclusion of DMP
b) use of exploratory data analysis to inform data preparation and/or analysis
c) relevant use of R packages and/or Python libraries
d) new knowledge discovery directly obtained from the data analysis
Attachment:- Distributed Data Analysis.rar