Atlantic Technological University
Atlantic Technological University

Master of Science Big Data Analytics and Artificial Intelligence

Atlantic Technological University, Ireland

Course Overview

The Master of Science in Computing in Big Data Analytics and Artificial Intelligence is a comprehensive program designed to equip students with the skills and knowledge necessary to excel in the rapidly evolving fields of big data analytics and artificial intelligence (AI). Offered as a one-year full-time or two-year part-time program, this course focuses on the processes involved in analyzing and interpreting large volumes of data to uncover hidden patterns, correlations, and valuable insights. In today's digital age, industries ranging from banking and financial services to retail and healthcare are increasingly relying on big data analytics and AI to gain competitive advantages and drive innovation. This program provides students with the qualifications and expertise needed to capitalize on the growing opportunities in these fields. Upon completion of the program, graduates are well-positioned to leverage their skills to deliver tangible benefits to businesses, including more effective marketing strategies, increased revenue, and informed decision-making. As companies across various sectors continue to harness the power of big data and AI, the demand for skilled professionals in these areas is on the rise. Successful graduates of this program can pursue diverse career opportunities in industries such as healthcare, banking, financial services, energy services, manufacturing, retail, transport, and communications. Roles may include data analysts, researchers, information managers, project managers, solutions specialists, and systems architects. Overall, the Master of Science in Computing in Big Data Analytics and Artificial Intelligence offers a pathway for students to enter dynamic and rewarding careers in fields where their skills and expertise are in high demand. With the increasing reliance on data-driven decision-making across industries, graduates of this program are well-equipped to make significant contributions and drive positive change in their respective fields.

Course Type
PG
Course Nature
Full Time
Course Duration
1 Year
Total Fee
€12000
Intake
Language Proficiency

Under graduation:60%

IELTS:6.5

Documents Required
  • 10TH
  • 12TH
  • DEGREE
  • DEGREE PROVISSIONAL CERTIFICATE
  • Degree Consolidated Marksheet
  • Degree Individual Marksheet
  • PASSPORT
  • LOR 1
  • LOR 2
  • CV
  • IELTS
  • SOP
  • EXPERIANCE CERTIFICATES
University
Atlantic Technological University
University Details

Syllabus

Semester 1

  1. Machine Learning Fundamentals (Mandatory)

    • Credits: 10
    • Contract Hours: 4
    • Details: This module introduces the fundamental concepts and techniques of machine learning. Students will learn about various supervised and unsupervised learning algorithms, model evaluation methods, and practical applications of machine learning in diverse domains.
  2. Mathematics for Analytics (Mandatory)

    • Credits: 10
    • Contract Hours: 4
    • Details: This module provides a comprehensive review of mathematical concepts relevant to analytics and data science. Topics covered include linear algebra, calculus, probability theory, and statistics, with a focus on their application in analyzing and interpreting data.
  3. Principles of Artificial Intelligence (Mandatory)

    • Credits: 10
    • Contract Hours: 4
    • Details: This module explores the foundational principles and techniques of artificial intelligence (AI). Students will learn about AI problem-solving paradigms, knowledge representation methods, and reasoning algorithms, as well as ethical considerations in AI development and deployment.

Semester 2

  1. Artificial Intelligence for Vision and Natural Language Processing (Mandatory)

    • Credits: 10
    • Contract Hours: 4
    • Details: This module focuses on advanced AI techniques for processing visual and natural language data. Students will learn about computer vision algorithms, natural language processing (NLP) techniques, and deep learning models for image recognition, language understanding, and text analysis.
  2. Big Data Analytics (Mandatory)

    • Credits: 10
    • Contract Hours: 4
    • Details: This module explores the principles and practices of big data analytics. Students will learn how to process, analyze, and derive insights from large and complex datasets using distributed computing frameworks, data mining techniques, and predictive analytics algorithms.
  3. Big Data Architecture (Mandatory)

    • Credits: 10
    • Contract Hours: 4
    • Details: This module covers the architectural components and design principles of big data systems. Students will learn about distributed storage systems, data processing frameworks, and scalable infrastructure solutions for managing and processing big data efficiently and effectively.

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