BSc in Data Science Crafting Future Decision-Makers

Bachelor of Science in

Data Science

  • On campus
  • 3 years
  • 180 ECTS

Britts Imperial Introduces On campus BSc Data Science Program: Awarded by Eucléa Business School, France in 3 years, Transforming from Skilled Professional to Global Industry Innovator.

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About

Globally Accredited

About
 Welcome to

Britts Imperial University College

Britts Imperial College, UAE is an Academic Centre & Education Partner of top-tier globally recognized British & European universities to offer Undergraduate, Postgraduate and Doctoral degree programs awarded by these universities to aspiring learners from across the globe.Steered by a team of Seasoned Educationalists as the Board of Governors, with decades of experience, Britts Imperial College boasts of a visionary leadership team from across the globe. Britts Imperial College is accredited by various prestigious UK exam bodies and welcomes students from more than 31 countries.

Eucléa Business School, in collaboration with Britts Imperial University College is a higher education institution that is a member of the Collège de Paris, specialised in business, technology and alternating management. With four campuses strategically located in Strasbourg, Metz, Mulhouse and Reims, Eucléa offers a complete range of training, ranging from Post-Bac to Bac+5 level.

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Why Choose Us

Bachelor of Science In
Data Science

The BSc in Data Science is a dynamic three-year program comprising 180 ECTS credits. It offers a well-rounded education in data science, encompassing key areas such as data analysis, machine learning, big data technologies, and statistical methods. The curriculum is designed to provide a solid foundation in the principles of data science, while also allowing for specialization in areas of interest. Students will engage with cutting-edge tools and technologies, gaining hands-on experience that is directly applicable in the industry.

Course Structure

BIGBAAI – BSc in Data Science (RNCP 35680)
Year BIG Code Course Code Course Name Credits
BSC101 OS Operating Systems 5 Credits
BSC102 DSPP Data Structures & Pyton Programming 5 Credits
BSC103 DDD Database Design and Development 5 Credits
BSC104 CSNS Computer Systems and Networks Security 5 Credits
BSC105 IDDA Introduction to Data and Data Analysis 7.5 Credits
BSC106 IDS Introduction to Data Science 7.5 Credits
BSC107 IAI Introduction to Artificial Intelligence 7.5 Credits
BSC108 CS Cyber Security 7.5 Credits
BSC109 DM Discrete Mathematics 5 Credits
BSC110 IES Innovation and Entrepreneurship for Startups 5 Credits
Total Credits (ECTS) 60 Credits
BLOC Competencies
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Program Objectives

  • Equipping students with a robust understanding of data science fundamentals, including statistical methods, machine learning, and data analysis.

  • Providing hands-on experience with industry-standard tools and technologies, ensuring students are well-versed in the practical aspects of data science.

  • Fostering the ability to analyze and interpret complex datasets, translating data insights into effective business strategies.

  • Cultivating critical thinking and problem-solving skills, essential for tackling real-world data challenges.

  • Encouraging ethical and responsible data handling practices, considering the implications of data in various societal contexts.

  • Preparing students for a seamless transition into the professional world, with skills that are highly sought after in the data science industry.

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Learning Outcomes

Machine Learning

Learners will understand the principles and applications of machine learning algorithms and will gain hands-on experience in implementing and evaluating machine learning models for various tasks.

Data Handling and Preprocessing

Graduates will learn effective techniques for collecting, cleaning, and preprocessing diverse datasets and gain proficiency in data wrangling and feature engineering to prepare data for analysis.

Programming Proficiency

Graduates will learn master programming languages commonly used in AI development, such as Python and Java and develop coding skills for data manipulation, analysis, and visualization.

Foundational Knowledge

Learners will acquire a strong foundation in statistical concepts, mathematics, and computer science relevant to data science.

Big Data Technologies

Graduates will familiarize oneself with big data technologies and platforms, such as Apache Hadoop and Spark and learn how to handle and analyze large-scale datasets efficiently.

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Frequently Asked Question

No prior programming or statistics experience is required, though it can be beneficial. The program starts with foundational courses.
The program is currently offered only on campus.
It includes hands-on projects, internships, and capstone projects to apply learning in real-world scenarios.
Some advanced modules may have prerequisites, but foundational courses are open to all students.
Graduates can advance to higher studies, including master's and doctoral programs.
The program equips students with skills suitable for tech entrepreneurship.
Skills gained are applicable for freelance or consultancy roles across various industries.
The degree is internationally recognized, allowing for global employment opportunities.
B.Sc Data Science focuses on statistical analysis and handling large datasets, suitable for those interested in data-driven insights, whereas B.Sc AI is more about developing and implementing AI algorithms.
Data Science covers a broader range of activities including data collection, processing, and analysis, while Data Analytics is more focused on extracting insights from existing data sets.