Course Details

Important elements of the curriculum usually consist of:

Foundations of Data Science and Artificial Intelligence: Students learn about the basic ideas, methods, and algorithms in data science and artificial intelligence. This covers subjects like statistical modeling, data mining, machine learning, and programming languages like Python and R that are frequently used in data science and artificial intelligence.

Advanced subjects: Deep learning, natural language processing, computer vision, big data analytics, and predictive modeling are just a few of the advanced subjects in AI and data science that are covered in the program.  

Practical Experience: Projects, case studies, and practical exercises are used throughout the program to stress getting hands-on experience. Students hone their analytical and problem-solving abilities by working with real-world datasets and industry-standard tools and technology.

Ethical and Legal matters: Students also study the ethical implications of AI technologies, data privacy, security, and regulatory compliance, given the growing significance of ethical and legal matters in AI and data science.

Capstone Project: Many MSc programs in AI and data science culminate in a capstone project where students apply their knowledge and skills to tackle a significant real-world problem or research question.  

Upon completion of the program, graduates are well-equipped to pursue various career paths in industries such as finance, healthcare, technology, e-commerce, and government, where there is a growing demand for professionals with expertise in artificial intelligence and data science. They may work as data scientists, machine learning engineers, AI researchers, data analysts, or business intelligence analysts, among other roles.

Requirements:

CGPA-3.00
IELTS-6.5/6.0
OIETC-7/6
Gap-No Issue (proper explanation)
Scholarship-N/A