Program start date | Application deadline |
2024-09-01 | - |
Program Overview
The MSc Data Science and Analytics is a 12-month conversion master's program designed to equip students with the knowledge and skills to collect, process, analyze, and visualize data to extract useful information. The program combines modules on programming, statistics, databases, machine learning, data analysis, data ethics, and data visualization, culminating in a thesis project. Graduates are well-positioned for careers as data scientists, data analysts, machine learning engineers, and other data-related roles across various industries.
Program Outline
MSc Data Science and Analytics
- Nurture critical thinking, problem-solving, and communication abilities essential for success in data science and analytics.
- Provide a solid foundation in statistical and computational methods for data analysis.
Program Description:
The MSc Data Science and Analytics is a 12-month conversion master's program designed for individuals aiming to pursue a career in the field of data science. It offers a comprehensive curriculum combining modules on programming, statistics, databases, machine learning, data analysis, data ethics, and data visualization. The program concludes with a thesis project, allowing students to apply their acquired knowledge and skills to real-world data analysis challenges.
Outline:
Course Schedule:
The program commences in September and is delivered through a combination of lectures, tutorials, and practical sessions.
- Statistics for Data Science: Provides students with a solid understanding of statistical methods and techniques used in data analysis, including probability theory, hypothesis testing, regression analysis, and time-series analysis.
- Databases for Data Science: Explores the principles of database management systems and equips students with the ability to design, build, and query databases for efficient data storage and retrieval.
- Statistical Machine Learning: Introduces students to the theory and practice of machine learning algorithms, including supervised, unsupervised, and reinforcement learning, focusing on their application to real-world data problems.
- Data Analysis and Visualization: Teaches students how to effectively analyze and interpret data using various techniques and tools, including statistical software packages and data visualization libraries.
- Case Studies in Data Science: Exposes students to real-world applications of data science across diverse industries, showcasing the power and impact of data-driven decision-making.
- Thesis Project: Provides students with the opportunity to conduct a supervised research project on a data-related topic of their choice, culminating in a written thesis and oral presentation.
Assessment:
Assessment Methods:
- Continuous assessment: comprises regular assignments, quizzes, and mid-term exams, typically weighted around 50% of the final grade.
- End-of-semester exams: assess students' understanding of major topics covered in each module, typically contributing 50% to the final grade.
Assessment Criteria:
- Depth and breadth of content knowledge
- Ability to analyze, interpret, and communicate data effectively
- Application of statistical and machine learning techniques
- Problem-solving and critical thinking skills
- Quality and originality of research for the thesis project
Teaching:
Teaching Methods:
- Lectures: provide students with a foundational understanding of key concepts and theories.
- Tutorials: facilitate active learning and interaction with classmates through problem-solving exercises and group discussions.
- Practical Sessions: offer hands-on experience with real-world data using statistical software and programming languages.
- Independent Study: encourages self-directed learning and research through assigned readings and individual project work.
Faculty:
The program is delivered by a team of experienced and research-active faculty from the Departments of Mathematics & Statistics, Computer Science, and the National Centre for Geocomputation. These faculty members possess expertise in various areas of data science, including statistical modeling, machine learning, data visualization, and computational methods.
Teaching Philosophy:
The program adopts an active learning approach that emphasizes student engagement, critical thinking, and collaboration. Students are encouraged to actively participate in class discussions, ask questions, and work collaboratively on assignments and projects.
Careers:
Career Paths:
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Business Intelligence Analyst
- Quantitative Analyst
- Data Visualization Specialist
- Research Scientist
- Statistician
Potential Industries:
- Technology
- Finance
- Healthcare
- Government
- Retail
- Marketing
- Education
Opportunities for Graduates:
The demand for data scientists and analytics professionals is rapidly growing across various sectors. Graduates of the MSc Data Science and Analytics program are well-positioned to pursue successful careers in these fields, armed with the necessary knowledge, skills, and experience.
Other:
Admission Requirements:
Applicants must have a recognized primary degree equivalent to an Irish university primary degree level. The degree should be at level 8 in any subject with some mathematical content.
English language requirements:
Maynooth University
Overview:
Maynooth University is a public research university located in Maynooth, County Kildare, Ireland. It is known for its strong academic programs, vibrant campus life, and commitment to research.
Services Offered:
Maynooth University offers a wide range of services to its students, including:
Library:
A comprehensive library with extensive resources and study spaces.Maynooth Access Programme:
Support for students from underrepresented backgrounds.Gaeilge san Ollscoil:
Irish language services and resources.Campus Life:
A variety of student clubs, societies, and activities.International Office:
Support for international students and those wishing to study abroad.Graduate Research Academy:
Support for postgraduate research students.Research Development Office:
Support for research activities.MaynoothWorks:
A platform connecting researchers with industry partners.Student Life and Campus Experience:
Students at Maynooth University can expect a vibrant and engaging campus experience. The university offers a wide range of clubs, societies, and activities, including sports, music, drama, and volunteering opportunities. The campus is located in a picturesque setting, with easy access to Dublin and other major cities.
Key Reasons to Study There:
Strong Academic Programs:
Maynooth University offers a wide range of undergraduate and postgraduate programs across various disciplines.World-Class Research:
The university is renowned for its research activities, particularly in the natural sciences, social sciences, engineering, technology, arts, and humanities.Supportive Campus Environment:
Maynooth University provides a welcoming and supportive environment for students, with a strong focus on student well-being.International Focus:
The university has a strong international presence, with a diverse student body and a commitment to global engagement.Academic Programs:
Maynooth University offers a wide range of academic programs, including:
Undergraduate Studies:
Level 8 degrees in various disciplines.Postgraduate Studies:
Taught master's, diplomas, certificates, and research programs.Certificates and Short Courses:
A variety of short courses and certificates for professional development.Entry Requirements:
EU Home Students:
- Applicants must have a recognised primary degree which is considered equivalent to Irish university primary degree level.
- However, international students may also be required to demonstrate their proficiency in English through an English language test such as TOEFL or IELTS.
Language Proficiency Requirements:
- 88
- This requirement applies to both EU and International students who are not native English speakers.
Summary:
- To be eligible for this program, applicants must possess a level 8 degree with some mathematical content.
- International students may also require a minimum TOEFL score to demonstrate English proficiency. Please note: