Bachelor of Science in Data Science (BS DSC)
- 4 Years / Onsite
- Semester: Sep, Jan, May
What is Data Science ?
Data Science is an interdisciplinary scientific field that unifies mathematics, statistics, computing, data mining, machine learning and their related methods (see Figure 1). It uses scientific methods, processes, algorithms and systems to discover and extract hidden knowledge and insights from structured and unstructured data. The objective of Data Science is to gather, interpret, and apply vital statistics and techniques that help uncover solutions to common problems in industry and society. To this end, a data scientist’s skills must include an advanced knowledge of calculus, algebra, statistics, computing and a palette of tools for deciphering and analyzing extracted data.
Most data used traditionally in relational databases or other storage is structured and moderate in size. Insights from such well-organized data can be uncovered using simple statistical or computing tools. However, today data drawn from a multitude of media sources including the Web, social media, telecommunications and the Internet of Things (IoT), is unstructured or semi-structured. There is a constant generation of this new type of raw and unstructured data that cannot be handled by traditional statistical or computing methods and tools. This is where Data Science comes into play to support the decision making process in automation and efficiency. In practice, the value of Data Science stems from its predictive and prescriptive nature that improves significantly revenues in e-commerce.
Program Overview
The Data Science program is designed in response to a growing need in industry for advanced academic qualifications and expertise in Data Science. It is a comprehensive and integrated curriculum including the general education and supporting STEM and BSS courses. The more detailed program sequence suggests that in the first and second years, students complete the necessary University core requirements and prerequisites courses. These prerequisites cover mathematics, statistics and computer science courses. The main objective of this program is to provide the necessary expertise in core data science skills including computational, data analytical and stewardship skills and knowledge and project design.
Learning outcomes
A student who graduates from this course will be able to:
- Show mastery of scientific fundamentals of data science;
- Use a sound knowledge of modern statistical methodology and computing;
- Apply data science techniques to address data management challenges;
- Develop abilities in the most used programming languages for data science;
- Demonstrate skills in statistical data analysis with professional software;
- Use machine learning algorithms to mine unstructured data;
- Interpret analytical models to make better business decisions;
- Organize and manage data sets for data science projects;
- Analyze critical computing challenges and identify analytical solutions;
- Communicate about and write solutions and methods of project activities
Career prospects
The Harvard Business Review, a notable management magazine published by Harvard University, suggested in its article “Data Scientist: The Sexiest Job of the 21st Century” that “the shortage of data scientists is becoming a serious constraint in some sectors.” In addition, IBM suggested that the global demand for data scientists will grow significantly in the next few years. This prediction was confirmed by the number of data science jobs offered from 2014 to 2018 according to CEB TalentNeuron, an online talent market intelligence portal. In African industries and governments, there is a growing interest in applying data science methods and innovative analytics techniques to local problems in the fields of sustainable development, healthcare, agriculture, education, wildlife conservation, telecommunications and manufacturing. Therefore, there are opportunities for data scientists like graduates from the IUGB Data Science program who can find appropriate solutions for these problems.