Hi I am a computer science undergraduate planning to do a master's degree in computational science(scientific computing) winter 2018. Since I have a bachelor's degree in computer science, I want to prepare before I apply for a degree. As of now I am following basic mathematics from A level syllabus, and once I complete basics of mathematics, I have planned to study, Linear algebra, Statistics and numerical methods (for data science and machine learning). For computer science, I am learning data science with python right now, and planned to do an online course in Machine learning with R. Also I have planned to do an internship in it next year beginning. For physics I am studying Halliday&resnick and campbel's for biology.( I want to get into geophysics or genomics sequencing program). How can I improve my skills of getting selected in the masters program? Is my plan good enough or do I have to do anymore than that?? To establish my knowledge in genomics or geophysics, Should I write any examinations?(like GRE), what would improve my chances internship or exams? I have contacted universities which very little helpful to get a correct answer. My efforts are totally disorganized because I don't know whether I am following the correct method. So please suggest a systematic method.