M.Sc

Minimum 50% required in graduation for getting admission in M.Sc courses in GGSIPU. For more details you can visit : https://www.shiksha.com/university/ggsipu-guru-gobind-singh-indraprastha-university-delhi-24725/courses/msc-bc

Hello
No ! M.Sc. In Environmental Science students is not eligible for Pharmaceutical job, but, candidate can work in Environmental Department of Pharmaceutical industries !

Candidate must be passed Bachelor's Degree from any recognized University or it's equivalent examination with any of the following subjects like Environmental Sciences, Chemistry, Botany, Zoology, Microbiology, Geology, Geography, Life Sciences, Fisheries Science, B.E. (Civil Engineering), Environmental Engineering.

The MSc program is of 2 years and the total fees will cost you around 2 lakhs including registration fees and tuition fess.
Don't forget to call and confirm at 080-43226500 in case of any doubts.

M.Sc Food and nutrition mainly covers subjects like Statistics & Computer Applications, Advanced Nutritional Biochemistry and Instrumentation I, Principles of Food Science, Advanced Human Nutrition I, Practical: (Advanced Nutritional Biochemistry, Principles of Food Science, Advanced Human Nutrition I). For detailed syllabus, please check the official website of the college where you wish to apply.

You can refer to this link for admission details http://msubaroda.ac.in/modules/manual/Admission_Manual_2018-19.pdf.

You have to prepare for the following subjects:
Biology and Life Sciences.
Applied Biology.
Applied Life Sciences.
Applied Zoology.
Behavioural Biology.Biochemistry.Bioengineering.

The curriculum for the MS in Data Science (MSDS) degree is 36 credits. One of the key features of the MS in Data Science curriculum is a capstone project that makes the theoretical knowledge you gain in the program operational in realistic settings. I have been looking through data science curricula and already feel overwhelmed by the amount of subjects a proper data science curriculum contains. Just to name a few: natural language processing, machine learning, R, Python, SQL, NoSQL, probability, statistics, numerical methods, algorithms, and the list goes on.