course

Master of Science in Applied Statistics and Data Analytics - Kiriri Women's University of Science and Technology

The Master of Science in Applied Statistics and Data Analytics program is designed to provide students with a strong foundation in statistical theory and methods, as well as practical skills in data analysis and interpretation. The program emphasizes the application of statistical techniques to real-world problems in various fields, including business, healthcare, and social sciences. Graduates will be equipped to work as statisticians, data analysts, and research scientists in a wide range of industries Course overview: Statistical Theory Data Analysis Machine Learning Big Data

Kiriri Women's University of Science and Technology University Masters 2 years

Verified facts

Programme code: MSD
Programme: Master of Science in Applied Statistics and Data Analytics
Requirements: KWUST's official courses API lists this programme under School of Computer and Information Technology as Post-Graduate with duration shown as 2 years. Requirements: Applicants must have a bachelor's degree in statistics, mathematics, or a related field with a strong background in statistics and mathematics Confirm current admissions status, exact entry requirements, fees, intakes, campus availability, and application deadlines directly with KWUST before applying or paying.
Advice: Source context: The program emphasizes hands-on experience through projects, internships, and research Specializations: Financial Econometrics Biometry Social Statistics Data Science Electives: Electives include Time Series Analysis, Bayesian Statistics, and Data Visualization Use this as a source-backed KWUST course listing, then confirm current admissions status, requirements, fees, delivery details, and application deadlines directly with KWUST before applying or paying
Evidence note: KWUST official Courses page renders this record from the official /academics/courses JSON payload. School: School of Computer and Information Technology. Source course type: Post-Graduate. Source course ID: 25. Source updated at: 2026-06-17 09:36:39. Parsed row: 25.