Postgraduate Certificate in Fundamentals of Data Science (Conversion) (Postgraduate Certificate in Fundamentals of Data Science (Conversion))

TU Dublin (TU257)
Key Programme Details
Award

Postgraduate Certificate in Fundamentals of Data Science

NFQ Level

Level 9 About NFQ

Delivery Method

Online, Blended

Mode

Part Time

ECTS Credits

30

Department

Computer Science

General Information
Contact

Sarah Jane Delany

Email

compsci-pg.city@tudublin.ie

Phone

contact by email

Address

School of Computer Science
TU Dublin
Kevin Street
Dublin 8

Role

Course Coordinator

Important Dates
Application Deadline

20/08/2020

Start Date

21/09/2020

End Date

31/05/2021

About this Course

The Postgraduate Certificate in Fundamentals in Data Science (Conversion) is a one-year part time programme which aims to provide non-computing graduates an opportunity to upskill in the developing area of data analysis and data science.

This is a postgraduate programme at level 9 in the National Framework of Qualifications. Applicants are required to have a strong numerate background. The programme covers the key skills needed for an entry level position in data analytics, including modules in programming, databases, data wrangling and data analysis. It is very practically focussed with students developing skills in the main tools, methods and techniques used in the domain.

It is a part time programme with evening delivery, over two evenings per week.

Objectives

The objectives of the programme are to:

• Impart an awareness of the principles and knowledge of data science to graduates with no academic background in computer science or other related discipline.
• Equip students with the base knowledge of technical skills, tools and techniques of data science.
• Expose students to leading-edge skills, tools methodologies and technologies needed for an entry-level position in data science within industry.

Entry Requirements

2.1 classification level 8 degree in a non-computing related degree or a 2.2 classification level 8 degree with at least 2 years of relevant industry experience.
All applicants require to have demonstrated strong numeracy and analytic skills which should be described in your supporting statement.

Long Description

The Postgraduate Certificate in Fundamentals in Data Science (Conversion) is a one-year part time programme which aims to provide non-computing graduates an opportunity to upskill in the developing area of data analysis and data science.
This is a postgraduate programme at level 9 in the National Framework of Qualifications. Applicants are required to have a strong numerate background. The programme covers the key skills needed for an entry level position in data analytics, including modules in programming, databases, data wrangling and data analysis. It is very practically focussed with students developing skills in the main tools, methods and techniques used in the domain.

It is a part time programme with evening delivery, over two evenings per week.

The programme includes the following modules:

Object Oriented Programming : This module focuses on developing the core programming skills needed to work with data. It covers the fundamental skills of object oriented programming in Python and at the end of the module the learner will be able to design and develop a software application in Python.

Information Systems: The focus of this module is to develop comprehensive core skills in working with databases. It covers the skills needed to design and implement databases and to access data in databases using SQL.

Data Wrangling: This module builds on the programming module to develop skills to build and manipulate the information sources associated with data analysis tasks. It will focus on data processing operations, retrieving and storing data for future analysis, data quality concerns, data cleaning methods and the integration of heterogeneous data from different sources through Python.

Data Analysis: This module addresses the application of data analysis techniques to real business problems. It covers the data analytics life cycle, data analytics techniques and tools for predictive modelling and data exploration, and how to evaluate these techniques, in addition to data management, security and ethical issues.

Career Opportunities

This course will give you, as a graduate from another discipline, skills and technical experience in working with both structured and unstructured data and performing data analysis at a basic level. It should supplement your existing knowledge, skills and know-how in your other discipline area to allow you to work with the data generated in these domains and work effectively on a data analysis team working with domain data.

Due to the focus on programming skills you will also be able to work in a data preparation role focusing which focuses on data extraction, cleaning and data wrangling.

Data science has been highlighted in a range of recent reports as an area of strategic importance both nationally and internationally. Data science is discipline-agnostic and can be applied across all industries and business processes where data is generated. Areas in which opportunities for data science and data analytics practitioners exist include retail, financial services, telecommunications, health, and government organisations.

With continuing education in data science you will be able to progress to a role more focused on using machine learning techniques to extract insight to help enhance business processes in a variety of industries. Specific roles include but are not limited to: Data Analytics Consultant, Data Scientist, Data Analyst, Data Architect, Database Administrator, Data Warehouse Analyst, Business Intelligence Developer, Business Intelligence Implementation Consultant, Business Analyst, Reporting Analyst.

Timetable Info

2 evenings a week

Delivery Notes

Blended learning - online lectures and practical labs

RPL Information

http://www.dit.ie/academicaffairsandregistrar/recognitionofpriorlearning/

Application Procedures

Apply online with transcripts of your level 8 degree, a full CV, a personal statement indicating why you are applying for this course and details of your numeracy and analytic skills/experience and a copy of your passport.