MS in Data Science Programme

The MS in Data Science is an 18-month program offered by the Northwestern University School of Professional Studies in collaboration with Great Learning. This program equips you to build key analytical and leadership skills required for careers in today's data-driven world. This program equips the learners with a comprehensive understanding of the most in-demand tools and technologies of the current world.

WES accreditation is only required for courses from universities outside of the US to prove that they are equivalent to one by an accredited US university.

For example, WES may look at a course by an Indian engineering college that assigns points out of 100 and then converts it to an equivalent score for a similar course in the US out of a 4.0 GPA scale. 

As the MS in Data Science Programme is from Northwestern University, a US-accredited university, WES accreditation is not required.

There will be a mix of live sessions as well as pre-recorded video lectures. Live sessions will also get recorded, in case a student is unable to attend a session or wishes to review it they would be able to view the recording again.

The duration of a Data Science Master’s Degree from Northwestern University is 18 months, 6 terms of 3 months each.

While knowledge of a programming language is not a prerequisite, the course will extensively use Python and R programming languages for the demonstration of concepts as well as for project work. If applicants do not have any background in programming then it would be helpful if they started learning Python and R prior to the start of the course.

While in terms of curriculum design and academic & career outcomes, this online degree is the same as a classroom programme, the key difference comes in how the curriculum is delivered. Classroom-based learning relies on more in-person interactions where students attend lectures in a classroom, interact with faculty over office hours, have study sessions with TAs, etc. In an online programme all this interaction shifts so that it happens over the internet. This shift allows for greater convenience, flexibility, and adherence to social distancing measures, making online programs an attractive option. Thus an online programme offers more convenience, flexibility, and safety (by providing social distancing) compared to a classroom programme

This is a master level degree and will be rigorous in nature. While the time needed will vary depending on prior knowledge, students should plan to spend around 15 - 20 hours every week.

 All faculty will decide on the grading mechanism of their respective subjects. The evaluation criteria will be shared by them at the start of every course.

The programme follows a cohort-based approach and students would be required to complete the various courses in a prescribed order.

While we highly encourage attendance at the sessions, we understand that scheduling conflicts may arise, which is why we will be uploading session recordings on the LMS (Learning Management System). This will allow students the flexibility to access and view the sessions at their convenience, even if they are unable to attend them live.

The exact number of sessions will be determined by the respective faculty, although, each course will feature a minimum of three engaging live sessions.

The typical duration of a live session would be 2.5 hours.

Yes, candidates from any part of the world can take up the MS in Data Science programme. As this course is offered completely online, you can enrol yourself and learn Data Science from the highly reputed faculty of Northwestern University.

• Upon taking up the Masters in Data Science Programme offered by Northwestern University, you would learn the most in-demand tools and techniques of Data Science. Learners would gain a comprehensive understanding of all the concepts that are taught throughout the sessions.

• Participate in the live interactive sessions delivered by the top faculty of Northwestern University.

• You would work on several projects, and participate in quizzes and assignments that enhance your understanding. You would also work on a capstone project that incorporates all the tools and techniques learned throughout the course. 

• Taking up this course would also get you a Northwestern student email ID and provide membership to alumni clubs and exclusive Northwestern advantage.

• You would also become a bonafide Northwestern alum.

• You will also be provided with dedicated support to guide you throughout your learning journey.

• Great Learning provides dedicated career support to its learners upon the successful completion of the course.

• You would partake in several resume review sessions, 1:1 career guidance sessions, gain access to job boards and much more.

The curriculum of this programme encompasses all the fundamentals of Data Science. Throughout this course, you would learn about several concepts like Applied Statistics, Mathematics, Database Systems, Machine Learning, Data Governance, Python and more.
 

You will also complete coursework in Artificial Intelligence comprising Natural Language Processing, Artificial Intelligence, and  Deep Learning

MS in Data Science programme from Northwestern University stands out with its remarkable benefits. The exclusive Northwestern advantage clubbed with the amazing benefits this course has to offer, makes this the right choice for professionals.

Here are a few of the benefits of the programme:

• World-Class Faculty: Upon taking up the Masters in Data Science Programme by Great Learning, you would learn from the world-renowned faculty of Northwestern University. You will partake in the live interactive sessions with the faculty and enhance your understanding of concepts.

• Hands-on Learning: Learners gain hands-on exposure to the tools and concepts learnt throughout the classroom sessions by participating in quizzes, assignments and projects. A capstone project is also assigned to the candidates at the end of the course that encompasses all the tools and concepts mastered during the live teaching sessions.

• Comprehensive Curriculum:  The curriculum of this programme is designed by highly skilled Data Science academicians and experts. The curriculum incorporates all the requisite tools and concepts employed in Data Science and Artificial Intelligence. Learners master several in-demand tools such as Python, R, SQL, Pandas and more.

• MS Degree from Northwestern University:  Upon the successful completion of this course, learners obtain a certification from the prestigious Northwestern University that adds value to their resumes.

Besides the above mentioned, there are a lot more benefits that this course offers. Do check out the fee, syllabus and more.

• Flexibility: This programme encompasses online learning with live sessions. The live sessions of this programme are organised to cause minimal disruptions to your personal and professional lives. 

• Committed Student Support:  Learners are empowered with constant support from several industry experts that help them in every step of their learning journey.

• Career Assistance: Great Learning provides outstanding placement opportunities to their learners upon the successful completion of this course. Each learner is provided with comprehensive career services that assist them to land their desired job roles.

• Learn the most in-demand tools: Upon taking up this programme, learners gain an understanding of the most in-demand tools such as R, Python, TensorFlow and more.

Students should have completed a 4 year U.S. bachelor’s degree or equivalent.

(For students who did not complete their degree in the U.S.): If your transcript evaluation states that your degree is equivalent to a 4 year U.S. bachelor degree then you can apply for this programme.

(If the student completed their bachelor degree in the U.S.): If you have a 4 year bachelor’s degree then you can apply.

No.

If the medium of instruction for the student’s bachelor degree was English (as certified in the transcript evaluation report) then no. If your transcript is being evaluated by a NACES member agency , please ask them to clearly indicate this in their report. 
 

If the medium of instruction was not English then the student would need to give an English language proficiency test like IELTS or TOEFL.

While knowledge of mathematics and statistics will be useful, it is not a prerequisite. Being a master’s program, the individual subjects themselves will have significant quantitative components and potential students are advised to brush up on their mathematics if they have not had the opportunity to use it recently.

While the course is designed to be convenient for working professionals, any student who fulfills the eligibility criteria can do this degree programme.

There is no predefined list of questions that an applicant needs to answer. The SOP is meant more as a way for the admissions team to better understand an applicant and their background. Some of the points which an applicant can cover to achieve this are:

• What is your motivation to enroll in a master’s degree?
• How will this degree help you achieve your career goals?
• How are you well positioned to leverage this degree in order to grow your career?

Applying early will not confer any special advantage however, the faster you apply the earlier you stand to get a decision. Some steps in the application process will need time and the admissions team themselves thoroughly evaluate each application so we advise that students submit an application as early as possible to avoid missing the deadline or having to rush at the last minute.

We have multiple cohorts starting every year, please connect with your admissions counsellor to know more.

Applicants can get in touch with their Admissions Counselors for guidance on how to complete the transcript evaluation process. Applicants may also submit their transcripts directly to an evaluation agency accredited by the National Association of Credential Evaluation Services (NACES).

Please contact an admissions counsellor to review the process for submitting mark sheets for initial evaluation.

Applicants will be required to submit scanned copies of their mark sheets or their official transcripts, and a copy of their degree certificate.

The cost for each residency is approximately $500*, which is directly paid to Great Learning. This payment includes the following:

• Comfortable single-occupancy accommodation for 1-2 nights at the Great Lakes Institute of Management campuses in Chennai or Gurgaon

• Three meals per day, along with coffee, tea, and light refreshments

• A grand networking dinner gala featuring a variety of food and drinks

• Access to campus amenities such as the gym, tennis courts, and pool table, among others

• Remuneration for the experts and mentors for their valuable time

*Please note these costs do not account for personal travel expenses to the Great Lakes campuses.

• Networking Opportunities: Residencies offer the chance to solidify relationships with highly capable professionals that you have already been introduced to in an online environment through the course of the programme. The inviting atmosphere of the campuses makes it easy to connect with your fellow students during meals, refreshments, and various engaging activities. Given that all participants will spend at least one, and sometimes two, nights on campus, this residential environment promotes bonding among the cohort.

• High-Quality Educational Experience: Both Northwestern University and Great Learning are committed to providing a top-notch educational experience, which forms a crucial element of this MS in Data Science programme. Interaction with faculty through structured lectures and less formal social gatherings is encouraged. Each cohort's experience will differ, but participants can anticipate joining in on academic events like Kaggle competitions and comprehensive Capstone presentations and review sessions. Prestigious industry professionals will lead discussions on practical applications of data science across diverse industry topics, guaranteeing that participants acquire knowledge that is applicable in real-world scenarios and goes beyond theoretical classroom learning.

• Career Guidance: Robust career support for those who aspire to change their professional path, as well as those who wish to advance in their current roles, is offered. Within the residency, group sessions guide learners on how to fast-track their careers in data science. Personalized mentoring sessions with experienced industry professionals, allowing learners to delve deeper into their short and long-term career goals, are also a part of the offering.

Northwestern's Master's in Data Science Programme distinguishes itself as the only online programme that includes an in-person element - two residencies that take place in India during the 4th and 6th terms of the programme.

The practical Machine Learning module is divided into “a” and “b” parts. Practical Machine Learning (a) contributes .5 course credits to your degree progress and involves the actual in-course components of the curriculum.

The Practical Machine Learning (b) provides the remaining .5 credits towards your degree progress and comprises the compulsory residency component of the curriculum. For credit towards their degree, students must attend the residency in person at the Chennai or Gurgaon campuses.

Likewise, the Capstone module is divided into "a" and "b" parts, with .5 credits accumulated through class participation, and the last .5 credits are obtained by attending the second mandatory on-site residency.

The two-day residencies are distinct, in-person interactions that augment the online Masters in Data Science programme on Great Lakes Chennai or Gurgaon campuses.

Residencies provide an excellent platform to acquire knowledge, build connections, and interact with fellow students and professors in an environment reminiscent of a traditional campus. In these residencies, learners collaborate in person with their team members on mandatory coursework and showcase their projects. Attendees get an opportunity to understand varied strategies for addressing data science challenges by observing the work of others. You can also look forward to several career-enhancing activities throughout both residencies.

The tuition for this degree is $13,000. This can be paid in 6 equal instalments of $2,167 each (payable at the start of every term). Please note that apart from the tuition, students will also need to budget for the following expenses:

• A fee of $35 each for online proctored examinations (3 in total)

• The cost of travelling, boarding/lodging and other expenses for the residency sessions (approximately $500 per residency) will have to be borne by the students.

While there are no scholarships, enrolling students have the flexibility to pay the fees in installment. We also have tie up with financial institutions to provide education loans.

At this point, there is no discount or other financial aid available.

Becoming a Northwestern Alumni offers some excellent benefits: 

• Learners gain access to global alumni events.

• Learners gain access to free learning events, library resources and much more.

• Learners also gain access to Northwestern University's email address.

• Learners also get to join a community of award winners and thought leaders in several domains such as Science, Technology, Politics, Arts & Entertainment and more.

The application of the most in-demand technology of Data Science in formulating effective business strategy has generated huge demand for professionals that can make data-driven decisions to promote business growth.
 

Hence, Great Learning in collaboration with Northwestern University has designed a perfectly curated programme for professionals seeking to pursue an MS in Data Science to assist organisations in making critical data-driven decisions.
 

Below are the learning outcomes that learners can expect upon taking up this programme:
 

• Effective analytics as a central strategy of Data Science.

• Convert data into meaningful insights.

• Generate statistically sound and sturdy analytical solutions.

• Build leadership, define and execute plans to address business problems.

• Assess risks and limitations on the application of data.

• Evaluate data structure and data lifecycle.