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Harvard Extension Online Master of Liberal Arts (ALM) in Extension Studies, field: Data Science

Why Harvard Extension? 

The Harvard Extension Online Master of Liberal Arts (ALM) in Extension Studies, field: Data Science degree program is designed for working adults wanting an in-depth education in data science that requires students to complete an impressive 48 credits. In keeping with Harvard Extension’s historic mission to increase access to the resources of Harvard University, the Extension offers an “Earn your way in” model for admission, where students simply enroll in courses without an application process.

Upon completion of 2 courses in the degree program, students then must take either a test in reading and writing or a Harvard Extension course in business rhetoric, and demonstrate knowledge of Python, R, and Calculus. If these requirements are met, students are considered for admission to the program. Therefore aspiring data scientists who are not confident that the work of data science is right for them might want to consider enrolling in a course through Harvard Extension before deciding to commit to the degree. 

Program Snapshot

University NameHarvard Extension
LocationCambridge
StateMassachusetts
Niche.com GradeA+
Name of DegreeMaster of Liberal Arts (ALM) in Extension Studies, field: Data Science. 
School or Department Administering ProgramExtension Studies
Credits48
Cost per credit$925
Tuition for Entire Program$44,400
Test RequirementsNone
Minimum GPANone indicated
Prerequisite Courses and Skills
  • Take the first two courses in program and test of reading and writing or course in business rhetoric, then apply to the program 
  • Knowledge of Python, R, and Calculus
Campus Visit Required?Yes
Typical Time to CompleteTwo years
When Can Students Start the Program?Fall, Spring, Summer
Program ConcentrationsNone
Synchronous classesYes
Required Courses
  • Advanced Python for Data Science
  • Data Modeling or Introduction to Statistical Modeling 
  • Precapstone (on-campus)
  • Capstone

4 of:

  • Advanced Scientific Computing: Stochastic Methods for Data Analysis, Inference and Optimization
  • Elements of Data Science and Statistical Learning with R  Advanced Machine Learning, Data Mining, and Artificial Intelligence
  • Principles of Big Data Processing
  • Computing for Big Data
  • Introduction to Natural Language
  • Introduction to Data Science
  • Advanced Topics in Data Science
  • Advanced Practical Data Science
Does the Program Include a Capstone?Yes
Does the program include a practicum or internship?No
Other Features that Make the Program Unique
  • “Earn your way in”admission model
  • alternate program requirements/pathway for students who have earned the MITtx Micromasters Program in Statistics and Data Science via Edx
  • on-campus 3-week precapstone during January session
  • possibility of working with Harvard or MIT faculty on research project
Program Objectives 
  1. Develop an in-depth understanding of data science methods in predictive modeling, data mining, machine learning, artificial intelligence, data visualization, and big data
  2. Build the skills to explore, analyze, manage, and visualize large data sets using the latest technologies
  3. Apply data science and analytical methods to address data-rich problems from a variety of fields, think critically about data, and drive decision making
  4. Develop the skills for quantitative thought leadership, including the ethical and legal dimensions of data analytics, as well as effective communication and collaboration
Program DescriptionThis 48-credit program provides students with an in-depth understanding of data science methods in predictive modeling, data mining, machine learning, artificial intelligence, data visualization, and big data. The emphasis is on critical thinking, problem-solving, and developing the ethical and legal background to become thought leaders in the field.  A three-week residential capstone project is required during the final semester. No concentrations are offered, and the program can be completed within two years. 

What will I Learn?

The emphasis throughout the Harvard Extension program is on developing thought leaders in the data science profession, equipped with both the technical skills and the higher-level knowledge they need to attack problems in a range of organizations. Legal and ethical frameworks for decision-making are highlighted throughout the program. All students must complete the required courses in Python programming and data modeling. An extensive range of choices is a hallmark of the curriculum. Students must choose three courses from a suite of 8 core courses covering topics in analytics, machine learning, data mining, artificial intelligence, natural language processing, and others. The remainder of the credits is electives. A unique feature of the Harvard Extension program is the three-week precapstone session, which all students must attend at Harvard in the January of their final semester. This session prepares students for completion of the semester-long capstone research project in which they apply their skills to a real-world problem. Some students may work with Harvard or MIT faculty on an ongoing research project. 

Harvard Extension also offers an alternative curriculum pathway to earn this degree for students who may have already taken some data science courses through the EdX platform. If students complete the requirements of the MITx Micromasters Program in Statistics and Data Science via EdX, they can apply EdX coursework to their Harvard Extension degree if they also take additional Harvard Extension courses and the precapstone and capstone. 

How much will the program cost?

Students finish their degree within two years and pay $925 per credit for a total of 48 credits, or just under $44,500 for the entire degree.

How does the program fit into my life?

In comparison with other data science master’s programs, the Harvard Extension data science program is less flexible. Still, it offers more opportunities for in-person and “real-time” interaction with fellow students, instructors, and research partners. Some courses have scheduled meeting times (known as “synchronous” instruction), and some are synchronous, meaning that instructors create learning materials such as lectures, activities, quizzes, assignments, and group discussions in weekly modules. Students are responsible for completing the module on their schedule within the given week.  Students enter the program in Fall, Spring, or Summer semesters, and most complete the program within two years. Because of the project-based nature of the program, students can expect to need to schedule time to work with classmates or meet with instructors, in addition to setting aside time and funds to complete the precapstone residency.

Summary

This program is a higher-cost option, and students also need to be able to commit to traveling to Cambridge for three weeks during their final semester. The program also has a much higher credit requirement than many similar programs. A major advantage is the option to register in courses without a formal application process. Students may also be attracted to the opportunity to work with Harvard and MIT faculty, and to visit the Harvard campus.