Level 7 in Information Technology

Key Information:

Programme Summary:

The Level 7 Diploma in Information Technology is designed for professionals seeking advanced expertise in IT, computing, and digital transformation. The programme develops high-level problem-solving skills, project management abilities, and a deep understanding of the societal impact of IT. Learners will gain proficiency in data analytics, network management, database systems, and information security, preparing them for leadership roles in the IT industry or further academic progression to a Master’s degree.

Level 3 Diploma in Data Science

Progression routes

Level 4 Diploma in IT-related rectors
Level 4 Diploma in DS
Level 5 Extended Diploma in DS
Year 1 of Bachelor's Degree
Directly into employment in an associated profession

Qualification Overview

The aim of the Level 3 Diploma in Data Science is to provide learners with an introduction and understanding of the field of data science.
The Level 3 Diploma provides a contemporary and holistic overview of data science, artificial intelligence, and machine learning, from the birth of artificial intelligence and machine learning in the late 1950s, to the dawn of the “big data” era in the early 2000s, to the current applications of AI and machine learning and the various challenges associated with them. In addition to the standard machine learning models of linear and logistic regression, decision trees and k-means clustering, the diploma introduces learners to two new exciting and emerging areas of data science: synthetic data and graph data science.
The Diploma also introduces learners to the data analytical landscape and associated analytical tools, teaching introductory Python so that Learners can analyse, explore, and visualise data, as well as implement a number of basic data science models.
Successful completion of the Level 3 Diploma in Data Science provides learners with the opportunity to progress to further study or employment.

Mandatory Units

- The Field of Data Science
- Python for Data Science
- Creating and Interpreting Visualisations in Data Science
- Data and Descriptive Statistics in Data Science
- Fundamentals of Data Analytics
- Data Analytics with Python
- Machine Learning Methods and Models in Data Science
- The Machine Learning Process
- Linear Regression in Data Science
- Logistic Regression in Data Science
- K-means Clustering in Data Science
- Decision Trees in Data Science
- Synthetic Data for Privacy and Security in Data Science
- Graphs and Graph Data Science

Credits:

60

Duration:

06 Months