Which top Masters Courses should you consider for a great career in data-science?
A frequently cited study by McKinsey predicts that by 2018, the United States could face a shortage of 140,000 to 190,000 “people with deep analytic skills” as well as 1.5 million “managers and analysts with the know-how to use the analysis of big data to make effective decisions.”
The field is so hot right now that Roy Lowrance, the managing director of New York University’s new Center for Data Science program says “Anything that gets hot like this can only cool off.” Regardless of this, the current school year won’t be over for another five months and 50% to 75% of its students already have firm job offers!
To say the least, data science involves some art because it requires creative experimentation. This balance of creative experimentation and detailed analysis is not attainable by everyone. Thus the demand-supply gap, as forecasted by multiple MNC’s, for the Data Scientist talent will never be completely filled!
However, if you are comfortable with numbers and know how to code, even at the basic level, a career in Data Science is something you must explore. Here, we list down some of the best courses you can undertake to get the certification of being a Data Scientist:
This course, primarily, examines learning from data in order to gain useful predictions and insights. The people who take this course are expected to have prior programming experiences and a basic understanding of statistics. The main focus of this course is to teach students to deal with data (collect and prepare it), analyse the collected data and make useful predictions.
The 5 focus areas of this course are:
2) UC Berkeley: Master of Information and Data Science (MIDS)
The UC Berkeley School of Information offers the only professional Master of Information and Data Science (MIDS) delivered fully online. Through this program, you can achieve the Online Master’s Degree in Data Analytics [M. S.]. This can help you make sense of real-world phenomena and everyday activities by synthesizing and mining big data with the intention of uncovering patterns, relationships and trends.
This course introduces students to concepts of information systems and the role of information systems within an organization. Topics covered will include:
This program is a collaboration between Stanford’s Department of Statistics and Institute for Computational and Mathematical Engineering. The core curriculum is, as you might imagine, heavy on mathematics and computer programming. This Data Science course is carved to attract, both, engineering or science students as well as mathematically oriented students. These students are interested in better understanding of the mathematical and statistical underpinnings of data science. They are looking to gain expertise in data science and its applications.
With the MISM program, the students will be trained in business process analysis and optimization, and will be educated on data warehousing, data mining, predictive modelling, GIS mapping, analytical reporting, segmentation analysis, and data visualization. This program has an important component of experiential learning. The students are trained to acquire the skills for analytic technology practices with applied business methods.
Carnegie Mellon’s MISM focuses on three core areas:
By: Sudhanshu Ahuja, CEO, Ideatory
Originally published at http://smartdatacollective.com
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