Master of Science in Data Science and Analytics

Program Overview

The Master of Science in Data Science and Analytics at Lincoln University College equips graduates with the knowledge and skills to work with large and complex datasets in various fields. The program covers core modules in data mining, data analytical programming, machine learning, big data storage and management, and data visualization. Graduates will be prepared for careers as data scientists, big data analysts, machine learning engineers, and other data-related roles.

Program Outline

Degree Overview:

Description:

The Master of Science in Data Science and Analytics equips graduates with the core analytics knowledge necessary to work with large and complex datasets in various fields. This program caters to both science and technical fields and social, political, and environmental challenges. It aims to develop students' business and communication skills while also providing them with training in crucial technical areas.

Objectives:

• To produce graduates who are:
• Knowledgeable and technically competent in Data Science and Analytics
• Effective team players with strong leadership qualities
• Creative and innovative problem solvers with strong ethical values
• Entrepreneurial and committed to lifelong learning
• To produce graduates who can:
• Successfully perform as a team player, demonstrate strong leadership qualities, and communicate effectively within an organization.
• Creatively and innovatively solve problems related to the field of IT using numerical and technical skills.
• Employ a sustainable approach to tackle Data Science and Analytics-related issues.
• Showcase entrepreneurial skills and lifelong learning commitment.
Graduates will gain the expertise to integrate specialized field requirements with Data Science and Analytics for improved data science processes within organizations.

Program Structure:

• Duration: 1 Year 6 Months
• Intakes: March, July, November

Individual Modules:

• Data Mining: This module will introduce students to the concepts and techniques of data mining, including data pre-processing, classification, clustering, and association rule mining.
• Machine Learning for Data Science: This module will cover the fundamental concepts of machine learning, including supervised learning, unsupervised learning, and reinforcement learning.
• Big Data Storage and Management: Students will learn how to store and manage large datasets using distributed systems and cloud computing.

Careers:

Career Paths:

• Data Scientist
• Big Data Analyst
• Machine Learning Engineer
• Mining Analyst
• Data Modeler
• Data Architect/Engineer
• Qualitative Analyst

Opportunities:

This program prepares graduates for graduate-level positions in the data-driven environment. With its focus on core knowledge, technical skills, and practical application, graduates will be well-equipped to pursue diverse career opportunities and contribute significantly to their chosen fields.