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MSc in Applied Data Analytics – Online

Date: 18th September 2017
Duration: 2 years part time
Grant Aided Cost: Email: susan.kelly@ictirelandskillnet.org
Location: ONLINE with IT Blanchardstown
Course Code: ICT316
Note:

The MSc in Applied Data Science and Analytics is a 2 Year part-time programme delivered entirely online by the Institute of Technology Blanchardstown.

Data Analytics is one of the fastest growing areas of IT, across a variety of organizations and industries, and remains mission critical for businesses as it turns information into an asset for deriving insight and making decisions. This reflects the need for companies to do business more smartly, enabled by business intelligence.

The course will focus on the knowledge and skills to select, apply and evaluate data science and big data analytics techniques to discover knowledge that can add value to a company. Students will gain both an in-depth theoretical understanding and practical hands-on experience, including implementing novel and emerging techniques. Participants will be kept abreast of current research and state of the art developments in data science related topics.

All lectures are delivered live online, two-evenings a week, using the Adobe Connect online classroom environment. Students are not required to attend campus for any aspect of the course.

Recordings of all lectures are made available immediately after the lecture. Students have access to lecture recordings for the duration of the course. This, coupled with other learning resources made available through Moodle (virtual learning environment) provides a truly flexible learning environment for all participants.

Modules are assessed through continuous assessment work only.

SEMESTER ONE

Core Modules

Business Intelligence

BI architecture, BI front-end, Data privacy and ethics; Business Intelligence and Data Mining methodologies, and the Business Intelligence life cycle.

Data Mining Algorithms

Standard Data Mining algorithms for descriptive modeling, classification, clustering, prediction, sequence analysis and association analysis.

 

SEMESTER TWO

Core Modules

Data Pre-Processing and Exploration

Data visualisation; Descriptive Statistics; Improving data quality; Transforming data in preparation for data mining;

Business Intelligence and Data Mining Applications

Project module: complete an analysis task to meet a business objective.

 

SEMSTER THREE

Additional Electives, students can select two electives:

Web Content Mining and Text Mining

Natural Language Processing techniques to extract data from unstructured text. Mining data from unstructured text.

Geospatial Data Mining and Knowledge Discovery

Data Mining techniques and algorithms for mining data from Geographic Information Systems.

Programming for Big Data

The algorithms and challenges for processing large datasets; students will need fundamental knowledge and skills in computer programming.

Statistics

The learner will cover the fundamental ideas of probability and descriptive statistics, moving on to hypothesis testing and the design of experiments

Multimedia Mining

Data Mining techniques and algorithms for mining digital media content

 

SEMESTER FOUR

Dissertation

Research Project which can be industry based

The MSc will be delivered by experienced lecturers in ITB and will also include guest lectures from individual subject experts in industry. ITB lecturers include:

  • Geraldine Gray (Course Coordinator)
  • Markus Hoffman
  • Laura Keyes
  • Simon McLoughlin

The minimum entry requirement is a 2nd Class Honours Grade 2 (GPA 2.5 or equivalent) in an NFQ level 8 degree in Computing, Science, Engineering, Business with IT or equivalent.

Applicants not meeting this entry requirement may be admitted to the programme on the basis of extensive practical and/or professional experience which can be assessed by the Institute’s APL/APEL process.

 

THE CLOSING DATE FOR APPLICATIONS IS 5PM MONDAY 11TH SEPTEMBER

Applications are now being accepted for a place on the September 2017 programme, simply forward your CV to susan.kelly@ictirelandskillnet.org

 

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