BACHELORS IN DATA SCIENCE AND BUSINESS ANALYTICS (2+2)
Bachelor
The aim of the program is to provide students with technical skills and practical insight to Data Science. The DS program combines theory and practice, based on three main disciplines, Computer Science, Statistics and Mathematics, and real-world application domains. It has been designed to enable graduates of the program to meet the demands of the data-driven economy of the future.
The program aims at providing students with:
- Technical and analytical skills required for acquiring, managing, analyzing and extracting insight from data.
- A strong mathematical and statistics foundation that will enable them to appropriately formulate models and apply optimization techniques for data analyses challenges.
- Machine learning skills to design and implement scalable, reliable and maintainable solutions for data-oriented problems.
- Ability to assess the level of privacy and security of a technical solution to a data science problem.
- Opportunity to pursue further higher education and research that require expertise in data science and analytical reasoning.
- A strong sense of social commitment, global vision and independent self-learning ability.
Program Structure
A student can apply for 4 years full time on campus programme in University of Nicosia.
OR
A student can choose to take two years at Patkar- Varde College, University of Mumbai and complete the remaining 2 years at University of Nicosia Campus.
Program Fees
- The Normal Tuition fees for the bachelor programme: €9.420 (per year / 60ECTS)
- If a Bachelor student completes 120 ECTS (first 2 years in India) then he will pay for the remaining 120 ECTS (50%) of the programme
Eligibility Criteria
- A recognised High School Leaving Certificate with a grade of 7.5 out of 10 or 15 out of 20 or a rank in the top 50%, or equivalent qualifications.
- English Language Proficiency: Students may be required to take NEPTON, UNIC’s English Placement Test at no charge, before registering for classes
- Students with the following English qualifications can register directly for their academic programme of study:
- TOEFL – 500 and above
- Computer-based TOEFL – 173 and above
- Internet-based TOEFL – 61 and above
- IELTS – 5.5 and above
Course Outline
Semester 1
- Introduction to Data Science
- Programming Principles I
- Discrete Mathematics
- Calculus I
- English Composition
Semester 2
- Programming Principles II
- Software Development Tools for Data Science
- Calculus II
- Probability and Statistics I
- Principles of Sociology
Semester 3
- Data Structures
- Data Programming
- Probability and Statistics II
- Bayesian Statistics
- Elements of Biology
Semester 4
- Algorithms
- Database Management Systems
- Linear Algebra I
- Machine Learning and Data Mining I
- Project in Data Science
Semester 5
- Machine Learning and Data Mining II
- Optimization Techniques
- Data Visualization
- Data Privacy and Ethics
- Visual Programming
Semester 6
- Big Data
- Web and Social Data Mining
- Linear Models I
- Technical Writing and Research
- Knowledge Management
Semester 7
- Artificial Intelligence
- Neural Networks and Deep Learning
- Data Science Final Year Project I
- Blockchain Programming
- Marketing
Semester 8
- Data Science Final Year Project II
- Industry Placement in Data Science
- Times Series Modelling and Forecasting
- Cloud Computing
- Linear Algebra II
