Certificate in Data Science
The Certificate in Data Science at Iconic University is a comprehensive one-semester programme designed to equip students with the necessary skills and knowledge to excel in the field of data science. This programme is suitable for individuals who are interested in working with big data and applying advanced analytical techniques to solve complex problems in various industries. Students will learn a combination of theoretical concepts and practical skills that are essential for a successful career in data science.
- To introduce students to the fundamentals of data science, including statistics, programming, and data visualization.
- To equip students with the ability to collect, clean, and manipulate large datasets for analysis.
- To provide a comprehensive understanding of machine learning algorithms and their applications in real-world scenarios.
- To develop critical thinking and problem-solving skills through hands-on projects and case studies.
- To prepare students for the workforce by teaching them how to effectively communicate insights and findings derived from data analysis.
21st Century Skills
Among the 21st Century skills for the programme are:
- creativity;
- information literacy;
- flexibility;
- social skills;
- problem solving;
- innovation skills; and
- critical thinking.
For candidate to be admitted into this programme, he/she must have a submitted a recognized national identity or international passport.
Iconic University charges modest fees that give learners the chance to pay per semester only. Nigerian candidates seeking admission will pay an application fee of N5,000 and $10 would be paid by international applicants.
Semester Fees:
Semester Fees are charged based on the human development index (HDI) of country of residence.
Nigerians |
|
Very High Development Countries | $500 |
High Development Countries | $400 |
Medium Development Countries | $300 |
Low Development Countries | $200
|
Other countries | $200
|
Click here to see list of countries based on HDI
Note: This schedule is only applicable to Spring Semester 2024/’25 academic session.