project management ms in big data in usa helps you master the skills
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Best Universities in USA for Data Science & Analytics Courses
One thing is clear, data is the ruler of the new world. Today, your life is being encoded in bits and bytes. And it is not just your browsing history or your social media activities. Your shopping or travel habits, what games you play, what shows you watch, and pretty much anything that can have the possibility of data generation, does have data generation. It is not just constrained to your social habits.
Pretty much all industries, small to large scale transactions, economic to weather patterns have data associated with them. So it is safe to say that we are the needle in the data haystack. It’s everywhere.
Since the late 1990s, this data overdrive has been needing some technical finesse to handle. A large amount of data, or popularly known as Big Data, is so massive that mere database handling tools may fall short. Data is currency, as long as we can find value in them. Tapping this wealth has become a necessity and large tech companies like Amazon, Google, and more, have made this possible using cloud computing and software tools like Hadoop. The nature of big data analysis has shifted from an algorithm pulling in data for analysis to algorithms being pushed out to data instead, also called the MapReduce computing paradigm (Source). There are also other Mass Analytical Tools, with simpler interfaces, aimed at making it easier to analyze big data. Some of these you might have already heard mentioned in tech circles Machine Learning, Complex Event Processing, etc.
All of the above requires some serious computational skills and training in these analytical tools. So clearly, these changing times, driven by an overwhelming need of storing and using data, has given birth to a new class of profession, Data Science, and a new set of professionals who call themselves Data Scientists. These people have killer math skills, really good statistical powers and of course programming expertize to actually do something tangible. The field of data driven Science is an interdisciplinary one, drawing in people from all sorts of technical, computational and math backgrounds. The current entry level salaries are in the neighborhood of $90k a year, according to Payscale. It has now been termed the sexiest job of the 21st century”. A recent IBM study has even reported that there will be a rapid growth in Data Science jobs, with 2.7 million new Data Scientist and Analytics jobs opening every year, by 2020.
Most of the current Data Scientists don’t have a masters in data science or analytics. The most widely accepted means of getting trained is through self study using online study material on MOOCs like Coursera, Udemy, etc.
While MOOCs have the advantage of self pacing the courses at a significantly cheaper price tag, they often lack discipline and accountability. A feature which is quite well established in regular courses.
Most of the Big Data Analysis degree courses are relatively new and not enough time has passed to assess the usefulness of getting a full on degree in Data Science. In fact there are only a handful of Universities that even offer a full blown degree in Data anything. But whatever be the age of the degrees, it is clear that the trend is catching on, and with increasing demands for Data Scientists, the need for certified expertize has also increased.
In this article, we have tried to list out the handful of schools that offer a degree course in Data Analysis or Data Science. Quite a few university trainings are in the form of certifications. However there are some that offer an MS in Data Science/Analytics in either an on-site or an online format. The list is arranged to give a sense of the curriculums in some of the well known Universities. They are in no particular order.
Top Universities for MS in Data Analytics and Data Science
1. Stanford University
- Department: Statistics School of Humanities and Sciences
- Degree: MS in Statistics: Data Science
- Application Fee: $125
- Tuition: 45 Unit course with Tuitions as per Stanford Registrar
- Eligibility Requirements: GRE/TOEFL.Strong Mathematics, Probability, Statistics and Linear Algebra.
|Example of Courses||Mining Massive Data Sets|
|Introduction to Statistical Inference||Parallel and Distributed Data Management|
|Introduction to Regression Models and Analysis of Variance||Business Intelligence from Big Dat|
|Introduction to Statistical Modeling||Paradigms for Computing with Data|
|Modern Applied Statistics: Learning||Machine Learning|
|Modern Applied Statistics: Data Mining||Capstone Project|
2. Columbia University New York
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