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Higher Diploma in Science in Data Science & Analytics

HDip in Sc
Programme Code: CR_SDAAN_8
Mode of Delivery:Full Time, Part Time, ACCS
No. of Semesters:2
NFQ Level:8
Embedded Award:No
Programme Credits:60
programmeReviewDate:March 2022

Programme Outcomes

Upon successful completion of this programme the graduate will be able to demonstrate... :

PO1 Knowledge - Breadth
  (a) Demonstrate detailed knowledge and understanding of areas of Mathematics, Statistics, Computer Science and Business Intelligence relevant to the Data Analyst.
PO2 Knowledge - Kind
  (a) Demonstrate understanding of the terminology, defining concepts and theories underlying the Data Science and Analytics field; demonstrate knowledge of the advanced methods and technologies for acquiring, interpreting and analysing big data, with a critical understanding of the appropriate contexts for their use; relate current issues in Data Science to society; understand current knowledge of the Data Science field, including current limits of theoretical and applied knowledge.
PO3 Skill - Range
  (a) Demonstrate mastery of relevant skills and tools in Statistics, Mathematics, Computer Science and Business Intelligence; use these to solve complex problems involving big data sets; interpret and apply appropriate and referenced literature and other information sources; work independently within defined time and resource boundaries; communicate scientific information in a variety of forms to specialist and non-specialist audiences.
PO4 Skill - Selectivity
  (a) Formulate and test hypotheses; design experiments; appreciate current limits of knowledge in the Data Science field and respond appropriately; think independently and make effective decisions; contribute fully to the day-to-day operations of the Data Science work setting.
PO5 Competence - Context
  (a) Apply data analysis skills and technologies in a range of contexts in order to critically interpret existing knowledge and apply in new situations; make and report appropriate decisions in a responsible and ethical manner.
PO6 Competence - Role
  (a) Act effectively under guidance in a peer relationship with qualified practitioners; participate constructively in a complex interdisciplinary team environment; plan for effective project implementation; reflect on own practices.
PO7 Competence - Learning to Learn
  (a) Learn to act in variable and unfamiliar learning contexts; identify learning needs and undertake continuous learning in the Data Science field; assimilate and apply new learning.
PO8 Competence - Insight
  (a) Demonstrate an understanding of the wider social, political, business and economic contexts of Data Science, including an appreciation of the philosophical and ethical issues involved.

Semester Schedules

Stage 1 / Semester 1

Module Code Module Title
DATA8001 Data Science and Analytics
STAT8006 Applied Stats & Probability
MATH8009 Maths Methods and Modelling
COMP8042 Analytical and Scientific Prog
DATA8002 Data Management Systems
DATA8003 Unstructured Data & Visualis'n

Stage 1 / Semester 2

Module Code Module Title
STAT8007 Statistical Meth for Big Data
DATA8005 Distributed Data Management
DATA8006 Data Science Analytics Project
Group Elective 1
Module Code Module Title
DATA8007 Data Visualisation & Analytics
DATA8004 DataMining &KnowledgeDiscovery
Module Code Module Title
COMP8043 Machine Learning
STAT8008 Time Series & M-V Analysis

Cork Institute of Technology
Rossa Avenue, Bishopstown, Cork

Tel: 021-4326100     Fax: 021-4545343
Email: help@cit.edu.ie