CPD Diploma in Data Analysis for Professionals

Program Overview

Data Analysis for Professionals

Overview

The Continuous Professional Development (CPD) Diploma in Data Analysis for Professionals caters to individuals from diverse backgrounds, including business, accounting, finance, science, and engineering. This program develops core skills in statistical data analysis, including interpreting data sets and representing data and results.

Program Details

TU Code

TU5294

NFQ Level

Level 8

Award Type

Special Purpose

Award

CPD Diploma

Duration

1 Year

Course Type

CPD, Undergraduate

Mode of Study

Part Time

Method of Delivery

Online

Commencement Date

September 2025

Location

Grangegorman

Fees

€2,950 Total Fee

Program Description

The program equips students with statistical and mathematical knowledge to extract critical information from large data sets. It enhances problem-solving and decision-making skills by building and strengthening analytical capabilities. A blend of theory and practice with a strong emphasis on modern software packages, such as R, underpins the program.

Minimum Entry Requirements

Students should normally possess either a qualification in science, engineering, or computing at level 7 on the National Framework of Qualifications or a qualification in business, accounting, or a financial discipline at level 8 on the National Framework of Qualifications.

Career Opportunities

Graduates are highly practical and grounded in the specific needs of organizations with respect to data analysis and problem formulation and solution. The program produces innovative and creative graduates who are independent and adaptive thinkers in the face of complex and dynamic problems.

Module Listing

Year One

Semester 1

• Business Case Study Project [Mandatory]
• Data Set Management [Mandatory]
• Probability & Statistical Inference [Mandatory]

Semester 2

• Business Case Study Project [Mandatory]
• Quantitative Decision Making [Mandatory]

Schedule

Each module is delivered over one semester. Online lectures and tutorials are held:

• Monday (Online) 18:30 - 21:30
• Wednesday (Online) 18:30 - 21:30