Top 10 Analytics / Data Science Masters Program by Universities in the USA

Qualifying for learning Analytics/knowledge Science as a post-graduate course in the USA isn't straightforward. But it’s not impossible either. I recently got selected in 2016-2018 batch for MS in knowledge Science at university. So, I believed I'll share my learnings and analysis with our community.


1. MS in Data Science, Columbia University


Columbia University is found within the heart of recent York town. Being Associate in Nursing conference establishment, there are no questions about its reputation. The MS program is being passed by the information Science Institute at Columbia. The students have access to courses from all the highest programs at the institute. The general course duration is 16 months,i.e. 3 semesters of study and an internship semester.


Curriculum:

Courses value thirty credits are needed to be completed and most of the graduate level courses are three credits every.

It consists of half-dozen core courses covering the necessities of technology, probability, statistics, and machine learning.

There is a capstone project within the last semester.

Remaining three courses will be taken as electives from across the university.


Practical Training:

These are available the shape of Associate in Nursing position semester and capstone project.

Additionally, the Columbia knowledge Science Society organizes workshops and different events wherever you'll get ample opportunities to move and solve issues along with your peers.

The city of recent York contains a sturdy knowledge science community which can provide several opportunities to use knowledge science information.


Industrial Collaboration & Research Opportunities:


The data science institute runs seven analysis centers that run some smart analysis comes which might facilitate students get operating information of information science

Since the department consists of professors from varied departments as well as technology, statistics, business, civil, etc. there are ample research opportunities available.

Industry collaborations add terms of sponsored analysis comes moreover career development center that organizes career fairs, tech talks, etc.

Rankings:

Business: 10

Computer Science: 15

Statistics: 20

Mathematics: 9

Conclusion: The program provides a decent foundation in machine learning and programming alongside sensible expertise. Moreover, Columbia is hierarchic in high twenty altogether the domains associated with known science creating it a decent selection. One drawback of the program could be that the curriculum is a bit inclined towards programming and more technical in nature than a few other programs, which are more business oriented.


2. MS in Data Science, New York University:


NYU is found in the big apple town and is fairly acknowledged. The MS program is being passed by the middle for knowledge Science at NYU. The students have access to courses from a good vary of departments as well as statistics, AI, biostatistics, business, economics, psychological science etc. The course will be completed in three or four semesters, counting on the selection of scholars.


Curriculum:

12 courses value thirty-six credits are needed to be completed.

It consists of half-dozen core courses covering the necessities of statistics and machine learning and a capstone project within the last semester.

Remaining half-dozen courses will be taken as electives from a good pool of domains which might be found here. This course contains a distinctive structure providing five-hundredths of the courses as electives that aren't seen in courses.


Practical Training:

These are available the shape of Associate in Nursing position semester and a capstone project.

It has an identical location advantage of being in the big apple town as the university. As aforementioned higher than, NYC’s sturdy knowledge science community offers ample opportunities for applying knowledge science information.


Industrial Collaboration & Research Opportunities:

Since the program consists of electives from varied departments as well as technology, statistics, business, civil, etc. there are ample research opportunities available. You can get some plan concerning the analysis comes here.


The department conducts workshops, technical school talks, and different events unitedly with trade professionals. Details concerning those events will be found on the program web site.

Rankings:

Business: 20

Computer Science: 29

Statistics: 49

Mathematics: 9


Conclusion: This program can provide a robust foundation in machine learning and ample expertise during an explicit domain through the half-dozen electives courses. NYU may lack slightly in terms of the division rankings however the program structure and placement of NYC will certainly.


3. MS in process knowledge Science, Carnegie Mellon University


Carnegie Mellon University (CMU) is one in every one of the utmost universities for analysis in technology. Its metal department conjointly run few specialized masters programs.

These programs target one core domain, have higher tuition fee and offer no help. They treat them as money-spinner programs however students like the prime quality pedagogy. MSDS is one such program. It spans over sixteen months with three semesters of study Associate in Nursing a position semester.


Curriculum:

There are a pair of concentration to decide on from – Analytics or Systems.

Analytics can target machine learning side and Systems can target massive knowledge and process aspects.

Total eight unit-courses, a pair of seminar courses and one capstone project is needed to finish the course.

Out of the eight unit-courses, three are electives which might be taken from the Department of technology.


Practical Training:

These are available the shape of Associate in Nursing position semester, seminar courses and capstone project.

The location of Pittsburg may be a definite disadvantage however the name of CMU is simply too massive for it to possess an impression on the position or job search. Obviously, relocation could be a potential challenge.

Industrial Collaboration & Research Opportunities:

This is a work orientating program and therefore the research/industrial collaboration opportunities come back from sponsored capstone comes.


The institute conjointly helps to exploit internships and job opportunities.

Rankings:

Business: 18

Computer Science: 1

Statistics: 9

Mathematics: 34


Conclusion: this can be a metal orientating program and ideal for individuals with some cryptography expertise World Health Organization need to induce into machine learning. The drawback is that the business facet of the program is weak and you must not expect to obtain some domain expertise like finance/healthcare. It is higher fitted to code engineering roles instead of knowledge human roles.


4. MS in Machine Learning, Carnegie Mellon University


This is another program like #3 offered by the Machine Learning Department in the dept of CS at CMU. The core plan is that the same aside from some of the changes:

It is alone supported cc and is a lot of mathematical nature. Covers theoretical ML at a broader level.

There square measure solely a pair of elective courses and one final project. No seminar courses like above.

The tuition fee is slightly less.

This would additionally prepare you for computer code engineering or analysis roles. You should opt for this if you have got a theoretical bent of mind and would love to pursue a doctor's degree (Ph.D.) after masters.


5. MS in Analytics, Northwestern University


This knowledge domain masters program is passing McCormick (engineering), Kellogg (management) and Medill (journalism) schools at NWU along with industry professionals in the Chicago area. It’s a fifteen-month program with a ten-week billet.


Curriculum:

The info consists of fourteen courses, 18-month industry practicum, and 1 capstone project.

Only a pair of courses out of the fourteen square measure electives which too from a little pool. So, the curriculum is more or less fixed. One of the explanations for demanding info is the little batch size of simply thirty-five. This is a giant advantage in terms of interactions and learning throughout the program.

The courses touch upon crucial aspects of analytics together with statistics, programming, databases, optimization with a focus on industry applications.


Practical Training:

The course is significant on sensible coaching that begins with the associate 8-month business project running across the primary three quarters. This project is organized together with the associated business partner.

There is associate billet within the summer and a capstone project within the final quarter.

The location of Chicago could be a definite disadvantage in terms of the native opportunities, however, NWU strives exhausting to urge industrial connections to hide up this disadvantage.

Industrial Collaboration & Research Opportunities:

The work is wealthy in industrial exposure as an excessiveness of activities like workshops, tech talks are conducted.

Both practicum and capstone projects are industry sponsored.

The program has no inclination towards analysis and you ought to not go there expecting any.


The institute additionally helps in feat internships and job opportunities.

Rankings:

Business: 5

Computer Science: 34

Statistics: 49

Mathematics: 17


Conclusion: This program is meant for folks operating during a specific domain World Health Organization need to know analytics and its applications in several industries. It is not designed for techies World Health Organization need to include machine learning algorithms in their computer code. The program makes significant use of the business connections coming back from food manufacturer faculty of Management, that is one amongst the foremost acknowledged management establishment of the planet.


6. MS in Analytics, Georgia Institute of Technology


This knowledge domain program is run put together by the School of Engineering, Business, and Computing at GaTech. Its a one year program and covers the autumn, spring and summer semesters.


Curriculum:

The program is meant within the sort of three tracks – Analytics Tools, Business Analytics and machine information Analytics. The details can be found here.

Each track covers statistics, operational research, and computing courses. The number of courses of every sort dissent by track.

There is a good share of electives that depend upon the chosen track. In general, there square measure five core courses and five electives.


Practical Training:

The program is usually a work primarily based culminating into a pair of capstone comes within the summer semester or associate billet, if approved by the college.

The location of Georgia could be a definite disadvantage in terms of the native opportunities, but there are still some meetup groups and online hackathon events which you can attend.

Industrial Collaboration & Research Opportunities:

The capstone comes undertaken square measure together with the business.

Some guest lectures and school talks also are organized.

The program has no inclination towards research and you should not go there expecting any.


The institute also helps in acquiring internships and job opportunities.

Rankings:

Business: 34

Computer Science: 9

Industrial and Systems Engineering: 1

Mathematics: 29


Conclusion: This is a typical coursework based program. One downside can be the selection between a capstone and billet. Also, the short period of the program can place further tutorial burden and restricts the networking opportunities. The positives square measure in terms of GaTech’s brand and also the involvement of research courses during which GaTech is one amongst the simplest institutes.


7. MS in Analytics, North Carolina State University


This program is managed by the Institute of Advanced Analytics at NCSU and is that the 1st analytics program started means back in 2007.

Most of the opposite programs square measure 2-4 years recent and so lack recognition. But NCSU could be an extremely acknowledged program within the analytics business, albeit NCSU as an entire is taken into account a tier a pair of the establishment. This is a 10-month intensive program, with three semesters beginning within the summer and ending in spring. Moreover, GRE score isn't needed for an application, only TOEFL is required.


Curriculum:

The info exposes students to a large spectrum of topics which might be found here.

The program ends with an associate business sponsored capstone project.

The info focuses on arithmetic and statistics and covers several applied math techniques.


Practical Training:

The program could be a typical work primarily based on a pair of sensible courses. There is no option for an internship.

The location of North geographical area isn't rick in native opportunities in information science, but the course is intensive enough to keep students exhausted during the 10 months.

Industrial Collaboration & Research Opportunities

The capstone comes square measure together with the business.

Some guest lectures and tech talks are also organized.

The program has no inclination towards research and you should not go there expecting any.


The institute also helps in acquiring internships and job opportunities.

Rankings:

Business: 52

Computer Science: 48

Statistics: 15

Mathematics: 52


Conclusion: NCSU could be a well putative program with sensible future prospects. It prepares candidates well for information someone roles because it exposes them to a good spectrum of analytics techniques. Strong arithmetic and statistics fundamentals area unit needed to induce into this program and you must apply on condition that you're assured concerning constant.


8. MS in Analytics, Texas A&M University


The master's program at TAMU is obtainable by the department of statistics and it’s a part-time program for operating professionals. The program web site isn't abundant informative however TAMU as an establishment encompasses a good name within the trade. Being a district time program, it is spread over 5 semesters.


Curriculum:

The information consists of twelve courses, details of which can be found here.

The program ends with associate degree trade sponsored capstone project.

There are only 2 elective courses.

The information encompasses a concentrate on statistics with applications in finance and promoting.


Practical Training:

The program often works primarily based on a capstone project and a seminar with public speaking.

There is concentrate on SAS programming that prepares you well for the trade.

Industrial Collaboration & Research Opportunities

Being a district time program, there's no concentrate on analysis.

The program’s consultative body is created from trade professionals that the program runs hand-in-hand with the necessities within the trade.

TAMU organizes other events further just like the Analytics 2015 conference.


Rankings:

Business: 31

Computer Science: 40

Statistics: 15

Mathematics: 41

Overall, it's an honest program and designed specifically for operating professionals.


9. MS in Business Analytics, Michigan State University


This is a one year program that commences within the spring semester and continues in summer and fall with graduation in Dec. The course prepares students for information someone roles in industries like consulting, automotive, client product, retail, and monetary services.


Curriculum:

The curriculum consists of 12 courses, details of which can be found here.

There area unit solely no elective courses as all courses area unit pre-defined.

The summer semester has employment of solely two courses and additionally a capstone project of a 10-12 week place will be completed in this amount.


Practical Training:

The program often works primarily based on associate degree choice of capstone project or associate degree place.

Industrial Collaboration & Research Opportunities

It’s a typical work primarily based program with no attention to analysis.

The capstone comes area unit conducted together with an associate degree trade partner.

University organizes internship and job fairs as well.

Rankings:

Business: 35

Computer Science: 56

Statistics: 47

Mathematics: 46


Conclusion: this is often a decent program and if you wish the mounted information, it would estimate. Also, since Michigan State University isn't as putative as other universities mentioned here, it would be easier to induce in.


10. MS in Business Analytics, University of Cincinnati


This is another one year program commencing in fall, with an additional or less mounted information. It prepares the candidates for the business analyst and information someone positions.


Curriculum:

The curriculum consists of 12 courses, details of which can be found here.

The program ends with an industry-sponsored capstone project.

There are only 2 elective courses.


Practical Training:

The program often works primarily based on a capstone project.

The location of Cincinnati additionally doesn’t provide a spirited information science community to require advantage from.


Industrial Collaboration & Research OpportunIBM takes a slightly more conservative view, predicting demand for data scientists to grow by about 30 percent by 2020, but even still, those are compelling figures. As demand grows, talent supply for these roles continues to lag behind; LinkedIn alone lists more than 6,000 open data science positions, and that’s only in the U.S. Companies across the world are recognizing the need for talented data scientists on payroll, in virtually every industry known to humankind.


As we round the corner on 2018, let’s take a look at some of the trends and predictions expected to shape and drive this high-demand field over the next year.


1. The skills and responsibilities required of a qualified data scientist will become more clearly defined.

As the field has grown, a certain amount of fuzziness has occurred around the actual meaning and definition of “data scientist.” It could be argued that at this point, “data science” is a full-on buzzword.

In 2018, hiring managers and recruiters will begin to drill deeper into the specific skill sets and knowledge these professionals must have—the ability to build and test hypotheses, statistical and visualization understanding, machine learning knowledge, and model-building skills, to name some.


2. Specializing in machine learning will be an even more worthwhile path to pursue.

Data scientist was No. 2 on LinkedIn’s list of top emerging roles. Number 1? Machine learning engineers. There are nearly 10 times more machine learning engineers in jobs today as compared to five years ago, and the site lists nearly 2,000 open positions.

Ideal candidates in this field will combine their knowledge of software engineering with data science. Successful software engineers who expand their skillsets into data science through programs like DataTrained will be uniquely positioned to snag these high-demand, high-paying jobs.


3. Data scientists with design chops will have an even bigger role to play.

Companies now recognize the critical importance of using data to drive decision making, at every level of an organization.

As the need to understand and socialize data across organizations grows, data scientists with an understanding of how to display data in a visually pleasing and easy-to-understand way will be uniquely positioned to spread data’s (and their) impact across their organization.


4. Having an understanding of agile methodologies within data science will be even more important.

The agile approach swept the design world years ago, and it’s sweeping the data science world now. Taking a fast-moving approach to this discipline—by using small, cross-functional teams focused on specific, targeted goals—can help companies move more nimbly, and solve their problems with increased efficiency.


5. Specializing in a particular field will become more important.

Because demand is so darn high, even the most general data science practitioner will likely find success. Those who do best, though, and land in the most fulfilling and impactful roles, will be the scientists who specialize in specific areas within data science itself.

That can mean diving deep into a particular methodology or technology tool stack, or focusing intently on one niche industry, but either way, those practitioners who hone in will find themselves in even higher demand, and with the freedom to pick and choose their future role.


6. Everyone will be paying attention—and will have an opinion.


“Data science” is no longer a jargon-y term that gets thrown around the water cooler at startups and tech companies. When companies like Netflix use their trove of data to call out a hyper specific subset of users, causing an uproar across the internet and calls for rules around data mining, you know data science has made its way to the mainstream.

Beyond the playful, data science also has a massive role to play in emerging technologies like AI, AR, and in the security realm, which naturally makes it fair—albeit controversial—game for dinner party fodder. With so many open roles, and nonstop news stories about data’s importance, the spotlight is on—for better or worse!


No matter how you slice it, data science has a massive role to play in 2018, and so do pros in the field. If you’re interested in launching your data science career to get in on the data rush, there’s never been a better time!ities

The program has no focus on research.

List most different courses, trade collaborations area unit within the style of job fairs, technical school talks and sponsored capstone.

Rankings:

Business: 63

Computer Science: 112

Statistics: –

Mathematics: 115


Conclusion: this is often a rather less putative university with an honest program that ought to be relatively easier to induce through. But you must be comfy with the information before you think that concerning taking it up.

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