Data Science

Course aim

To iintroduce students to data analytics providing some basic data-science tools. Statistical tools to individuate regularities, discover patterns and laws in complex datasets will be introduced to students together with instruments to analyse, characterize, validate, parameterize and model complex data. Practical issues in business data analysis and statistics will be covered with specific case studies also in collaboration with industrial partners.

Course content

Empirical investigation of complex data
Essential practical familiarization with complex and big data. Typical challenges with real business data. Basics on data acquisition, manipulation, cleaning, filtering, representation and plotting.

Univariate and multivariate statistics
Marginal probability, joint probability and conditional probability. Empirical estimation of probability distributions. Measures of dependency. Cause and effect. Granger causality, mutual information, transfer entropy. Spurious correlations and regularization. Forecasting and regressions. Calibration, validation hypothesis testing.

Modelling and filtering through networks
Basics on complex networks: definitions and properties. Construction of networks of interactions form correlation and causality measures. Information filtering though networks.

Applications and case-study
Application of the studied material and methods to practical cases and real data will be done within the course through case-studies developed in collaboration with industrial partners.

Textbook(s)

Newman, EJ 2010, Networks: an introduction, Oxford University Press

Casella, G and Berger, RL 2002, Statistical Inference, Thomson Learning

Dunlop, Dorothy D., and Ajit C. Tamhane 2000, Statistics and data analysis: from elementary to intermediate, Prentice Hall

Prerequisite(s)

Good knowledge of basic mathematics and statistics.

Corequisite(s)

Nil

Teaching method

Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.

Assessment

Continuous assessment

Fees

EFTSL*: 0.125
Commonwealth Supported program (Band 1)
To determine the fee for this course as part of a Commonwealth Supported program, go to:
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Fee-paying program for domestic and international students
International students and students undertaking this course as part of a postgraduate fee paying program must refer to the relevant program home page to determine the cost for undertaking this course.

Non-award enrolment
Non-award tuition fees are set by the university. To determine the cost of this course, go to:
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* Equivalent Full Time Study Load. Please note: all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation.