Big Data Capstone Project

Big Data Capstone Project

Course
en
English
24 h
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Source
  • From www.edx.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 6 Sequences
  • Advanced Level

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Course details

Syllabus

Dataset overview, data selection and ethics
Understand ethical issues and concerns around big data projects;Describe how ethical issues apply to the sample dataset;Describe up to three ethical approaches;Apply ethical analysis to scenarios.

Exam (timed, proctored)
The exam will cover content from the first four courses in the Big Data MicroMasters program, including the Ethics section of this capstone course, DataCapX. Itwill include questions on topics such as code structure and testing, variable types, graphs, big data algorithms, regression and ethics.

Project Task 1: Data cleaning and Regression
Understand the basic data cleaning and preprocessing steps required in the analysis of a real data set;Create computer code to read data and perform data cleaning and preprocessing;Judge the appropriateness of a fitted regression model to the data;Determine whether simplification of a regression model is appropriate;Apply a fitted regression model to obtain predictions for new observations.

Project Task 2: Classification
Build classifiers to predict the output of a desired factor;Analyse learned classifiers;Design a feature selection scheme;Design a scheme for evaluating the performance of classifiers.

Prerequisite

Candidates interested in pursuing this program are advised to complete

,,&before this course.

Instructors

Nick Falkner
Associate Professor, School of Computer Science
University of Adelaide

Gary Glonek
Associate Professor, School of Mathematical Sciences
University of Adelaide

Lingqiao Liu
Researcher, School of Computer Science
University of Adelaide

Gavin Meredith
Research Associate, School of Computer Science
University of Adelaide

Ian Knight
Lecturer, School of Computer Science
University of Adelaide

Editor

University of Adelaide

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