Harvard is undoubtedly one of the best universities owing to its excellent research institutes, world-renowned mentors, and state-of-the-art facilities. Moreover, it offers endless possibilities for students to explore their academic interests.
One such excellent academic offering is MS in Data Science at Harvard University!
The field of Data Science allows the students to study a blend of mathematics, algorithms, tools, and machine learning techniques.
MS in Data Science at Harvard University is a program offered by the Institute for Applied Computational Science. It is jointly offered by the university’s Statistics and Computer Science faculty.
The program offers students ample knowledge of machine learning, statistical modeling, data acquisition, optimization, and management and analysis of massive data sets.
Moreover, the course’s primary focus lies in collaborative problem solving, reproducible data analysis, visualization and communication, ethical issues, and security. A student must complete 12 courses within three on-campus semesters.
In other words, the duration of the course is 1.5 years. Students can extend the course by taking additional courses or a master’s thesis project in the fourth semester.
Modules
MS in Data Science at Harvard University has a 12-course module. They are bifurcated into three categories based on their type – core courses, research courses, and electives. Let’s take a detailed look at them:
1. Core Courses
Data Science 1: Introduction to Data Science
Critical Think in Data Science
Systems Development for Computational Science
Data Science 2: Advanced Topics in Data Science
Advanced Scientific Computing: Inference, Optimization, and Stochastic Methods for Data Analysis
2. Research Courses
Data Science Capstone Research Project Course
Independent Study in Applied Computation
3. Electives or Specializations
Visualization
Linear Models
Time Series & Prediction
Machine Learning
Topics in Machine Learning
Generalized Linear Models
Statistical Machine Learning
Artificial Intelligence
Advanced Machine Learning
Data Systems
Academic Cycle
The data science master’s is spread across 12 courses over three semesters. Every student’s study plan must include
Four technical courses:
Data Science 1: Introduction to Data Science
Data Science 2: Advanced Topics in Data Science
Advanced Scientific Computing: Stochastic Methods for Data Analysis, Inference, and Optimization
Systems Development for Computational Science
The necessary course of ‘Critical Thinking in Data Science’
Minimum one research experience either by taking a Capstone research project or a master’s thesis research
Minimum one elective course on Computer Science and one on Statistics
Up to one independent research course study
Up to one seminar course
At most two non-technical data science courses
The final requirement is a presentation of a data science project poster at the annual IACS Project Showcase
So, all in all, 12-course credits are required to fulfil MS in Data Science at Harvard University.
Eligibility
Academic
The Institute for Applied Computational Sciences hasn’t set stringent academic criteria. Instead, they take a holistic route to admission, considering every relevant application. No particular GPA is mentioned.
Besides, the institute seeks students that have showcased an interest in advanced computational work in the following ways:
Doing well in the courses of computer science, math, scientific computing, and statistics
Undertaking undergraduate research projects that have undertones of statistical or computational studies approach
There are no particular requirements for the master’s program application. Although, a sufficient background in Statistics, Math, and Computer Science is required.
Additionally, knowledge of linear algebra, calculus, statistical inference, and fluency in any programming language is a must.
English Language Proficiency
The minimum score for IELTS (minimum score of 6.5) or TOEFL (minimum score of 80) is required for students whose native language is not English. It’s not required if the student has a bachelor’s degree or equivalent from any university with English as its language of instruction.
Please keep in mind that a master’s degree from an institute with English as its language of instruction will not count. Moreover, the scores should be valid when sending the application.
Admissions for MS in Data Science at Harvard University
Now you know the basic admission requirements to get into MS in Data Science at Harvard University. The next question that arises is, how to get admission to the university? Let’s take a look!
Admission Cycle
The applications for the Fall cycle 2022 started in September of 2021 and concluded on December 1, 2021. Generally, the applications run from September to December of the current year if the student is keen to take admissions in the Fall of next year.
The admissions are not on a rolling basis. This course only has a single application with a deadline of December 1 every year.
Process
To apply for the MS in Data Science at Harvard University, you must submit your application through the GSAS Applicant Portal.
Go to the apply page, click on the apply button and fill out the application. Attach all the necessary and required supporting materials electronically. The application fee for the course stands at $105.
Documents Required for Admission
Here’s everything you would need to write a complete admission application for MS in Data Science at Harvard University.
A correctly filled application form
Statement of Purpose
Three Letters of Recommendation
All academic transcripts (even unofficial copies are allowed)
Resume or CV.
IELTS or TOEFL score
Application fee of $105
Supplemental data form
Cost of Attendance
Studying at Harvard is a dream that most young students harbour. This dream shouldn’t get curtailed due to a lack of clear financial information. Here’s all you need to know about the cost of attending Harvard to make specific prior arrangements.
Fee
The Harvard Data Science course fees are:
USD 59,968 for the first year
USD 29,984 for the second year (one term)
Living Costs
Here’s a breakdown of living costs at Harvard for a single student for 10 months
Items
Cost
Books and supplies
$900
Dormitory housing
$7,892-$12,392
Apartment housing with utilities
$17,730
Food
$6,700
Meal plan for dorm residents
$2,669
Miscellaneous
$6,910
Total
$42,801-$47,301
Last Class Profile
The acceptance rate for the master’s degree in the engineering department (within which Data Science falls) is 7.2%.
Placements after MS in Data Science at Harvard University
Around 51% of course graduates get hired in the technology sector. These include companies like Amazon, Apple, Meta, Google, Microsoft, Twitter, Waymo, Paige, Moveworks, and others.
Approximately 14% are hired in the finance sector. Some of the organizations that hire MS in Data Science at Havard University graduates are Bank of America, Bloomberg, JP Morgan, Nasdaq, Goldman Sachs, and others.
Study Abroad with upGrad Abroad
upGrad Abroad offers flexible study solutions to help aspirants achieve their foreign education dreams through collaborations with top international universities. You can pursue the most in-demand courses at one-fifth the cost.
Frequently Asked Questions
Which country is the best to pursue a master’s in Data Science?
The USA is one of the best, most famous educational destinations for pursuing a Data Science master’s. The country has top-ranking universities with well-renowned faculty members and excellent curricula for its students.
Is a master’s degree in Data Science a good option?
A Master’s in Data Science will help you achieve a well-paying job in a rapidly growing industry. According to the US Bureau of Labor Statistics, the job market for data scientists is expected to grow 22% by 2030.
What are the top US universities for masters in Data Science?
The top three universities to pursue masters in Data Science are Harvard University, Stanford University, and Yale University.
With over10 years of experience in the ed-tech sector, Sachin holds expertise in operations management, ensuring the smooth functioning of study abroad programs. He has deep understanding of the global university systems, acceptance rates, and selection process.
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