The Program Prerequisites for a Master of Science in Business Analytics typically include the following: 1. Educational Background: A 4-year bachelor’s degree from an accredited institution. The degree can be in business, engineering, computer science, mathematics, economics, or a closely related field. While a background in business or quantitative fields is preferred, applicants from other disciplines may also be considered if they have the necessary skills in mathematics and data analysis. 2. Minimum GPA: A minimum GPA of 3.0 on a 4.0 scale (approximately 75%), though competitive programs may have higher GPA requirements. 3. Prerequisite Coursework: Some programs require applicants to have completed certain undergraduate courses before applying. These may include: Mathematics: Strong foundational knowledge in calculus and linear algebra. Statistics: Coursework in probability and statistical analysis is often required. Computer Science: Basic knowledge of programming (e.g., Python, R, SQL), data structures, and algorithms. Business Fundamentals: Some knowledge of business concepts, such as finance, marketing, and management, may be beneficial. Data Analysis: Experience or coursework in data analytics or working with data may be required or strongly encouraged. 4. Standardized Test Scores: GRE (Graduate Record Examination) scores may be required by some programs, although this requirement is becoming less common, especially for applicants with strong academic or professional backgrounds. Some programs may waive the GRE requirement based on professional experience or undergraduate academic performance. For non-native English speakers, TOEFL (Test of English as a Foreign Language) or IELTS (International English Language Testing System) scores may be required to demonstrate proficiency in English. 5. Work Experience (Optional but Preferred): While not always mandatory, some programs prefer or recommend work experience in business, data analysis, or a related field. This experience can be a significant advantage for applicants, especially those with experience in data-driven roles or internships in business analytics, consulting, or finance. 6. Letters of Recommendation: Applicants are generally required to submit 2-3 letters of recommendation. These letters should come from professors, employers, or professionals who can speak to the applicant's academic abilities, analytical skills, and potential for success in a graduate-level program. 7. Statement of Purpose: A personal statement or statement of purpose is usually required. This essay should outline the applicant’s motivation for pursuing a Master’s in Business Analytics, their career goals, and why they are interested in the specific program. It should also highlight any relevant work experience or academic background. 8. Resume or CV: Applicants need to submit an updated resume or CV detailing their academic achievements, professional experience, and any relevant skills or certifications (e.g., proficiency in data analysis tools, programming languages). 9. Technical Skills: Programming Skills: Familiarity with programming languages such as Python, R, or SQL is important, as they are commonly used in data analytics and business analytics tools. Some programs may require applicants to demonstrate proficiency in these languages through previous coursework or a technical interview. Data Analysis Tools: Experience with analytics tools like Excel, Tableau, Power BI, or other business intelligence tools is also beneficial. 10. Interview (Optional): Some programs may require an interview as part of the application process, especially for candidates with non-traditional backgrounds or those applying for highly competitive programs. 11. English Proficiency (for Non-Native English Speakers): Applicants whose first language is not English may need to provide evidence of English proficiency through TOEFL or IELTS scores. 12. Additional Documents: Some programs may request additional documents, such as writing samples, research papers, or portfolio projects related to data analysis or business analytics.