Masters

A Masters data science degree program or a PhD might be a way to go, in developing and waving a technical data science skill set to potential employers but is not a prerequisite to get started with a career in data science. Lack of a highly quantitative degree does not debar one from learning data science. It is possible to learn data science even without a Masters degree. For high-functioning individuals, who really have the knowledge and expertise with the required tech skills, having a Masters or a PhD does not matter in the data science space. Real data science experience always outweighs the time spent in acquiring a Masters degree or a PhD because getting a PhD can prove to be a very long grind.
A Masters or a PhD matters when you are applying for a job but not having a PhD is not going to stop you from becoming a data scientist. If you are applying for a data science job at Google, then a Masters or a PhD might be a requirement but other companies will have biases in other directions for hiring a data scientist. PhDs matter only if you are applying for a higher level data science position. When beginning to learn data science, PhD or a Masters Degree is not a necessity.

Master Courses:
The master courses in this field are of two years:
Master of Science in Microbiology
Master of Science in Applied Microbiology
Master of Science in Medical Microbiology
Master of Science in Microbial Genetics and Bioinformatics
Specializations in Microbiology
Agricultural Microbiology
Industrial Microbiology
Evolutionary Microbiology
Nano Microbiology
Cellular Microbiology
Soil Microbiology
Veterinary Microbiology
Generation Microbiology
Microbial
Water Microbiology
Pharmaceutical Microbiology
Microbial Genetics
Environmental Microbiology
For admission to PG courses, it is necessary to hold a bachelors degree (B.Sc.) in the related field. Some universities organize their own entrance exams for screening candidates for admissions.