5 Things to Remember Before Applying for Data Science Course in US
Data science is the study of collecting, processing and extracting value from big and diverse data sets. It enables the scientists to create data-driven solutions to boost profits, reduce costs and make solutions to various problems.
The Areas of Usage
The following industries employdata scientists regularly:
- Pharmaceuticals
- Computer Software
- IT and Services
- Biotechnology
Do you plan to do your Data Science certifications in US Universities? Then you must keep in mind some basic points:
1. Knowledge Requirement:Admission to the MS course in Data Science requires but specific mathematical competencies. Your previous course of study should include Calculus I, Linear Algebra, Basic Computer Science (CS-101 programming course), One of Calculus II, Probability, Statistics, or an advanced physics, engineering, or econometrics course.
2. Preference Given:The students with prior exposure to machine learning, computational statistics, data mining, large-scale scientific computing, and operations research get preference during the application process. This knowledge helps the students in the primary courses too.
3. Examinations: Good GRE (Graduate record examination) or GMAT (Graduate management admission test) scores are mandatory for application. The applicants whose native language is not English and who have not received a university degree in an English-speaking country must produce TOEFL (Test of English as a foreign language) score.
4.Documents: You need to submit official college transcripts and letters of recommendation from the professors.
5. Choice of University: The market research says that by 2018, there would be a requirement of 140,000 to 190,000 data scientists in US. So Data Science is a subject in demand. Before you apply to a university you should verify the background of the program and the faculty. A partnership with business and research institutions should be there. You should be sure about the job placement figures. A good course of Data Science should offer rigorous theoretical and practical training. In addition to technical courses, communications, project management, and professional ethics courses should be there.
