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FAQ

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MSAN Frequently Asked Questions

Program details

Q: What is the length of the MS in Analytics program?
A: This is a full-time, intensive, 12-month program. The program starts in early July and runs until the end of June in the following year. 

Q: Do you offer night classes or is there a part-time option to the program?
A: There are no night classes. There is no part-time option at this time.

Q: Do you offer online classes?
A: There is no online option at this time. At USF, you will interact frequently in person with both your instructors and the other students in your cohort.

Q: What is the expected class size?
A: The third cohort will be approximately 35 students in size. The fourth cohort will contain approximately 35-50 students. However, the number of students in a classroom will remain under 40.

Q: What does the class schedule look like?
A: The schedule of classes is typically Monday through Friday from 10 a.m. until 5 p.m., with 3-4 classes running simultaneously each module. (A “module” is approximately half a semester.) One day per week is devoted to practicum work. The practicum starts in mid-October.

Q: What is the purpose of the analytics bootcamp?
A: Because students come from a variety of academic backgrounds, students take three five-week courses starting in early July to bring everyone's background up to a similar level. All students take the Exploratory Data Analysis course and then take two of the following: computation for analytics, linear algebra, or probability/statistics. We encourage students to choose boot camp classes based on course content that they most need to review. The boot camp is a way for students to quickly decide whether they have the appropriate background and the proper motivation to succeed. Every year a few students do not continue with the program after the end of boot camp.

Q:  What is the total cost of the program? Is financial aid available? 
A: Please click here for information about tuition costs, living costs and financial aid.

Q: Does the program offer any scholarships?
A: The Master of Science in Analytics (MSAN) program awards a limited number of partial scholarships to our very best applicants. For the class of 2014-2015, the median fellowship (among those students given fellowships) was $3,000 (range $3,000 - $9,000). Approximately fifty percent of enrolled students were given some level of fellowship money. You do not need to fill out a separate application to be considered for a fellowship; all students are considered.

Q: Does the program offer teaching assistantships or research assistantships?
A: No. Teaching assistantships and research assistantships are typically reserved for doctoral students at research-oriented institutions. The time that might ordinarily be allocated, in a doctoral program, to supporting a faculty member's research or to helping a professor teach a course is allocated to practicum projects in our program. Most of our practicum positions are unpaid.

Q: This program is expensive! Why isn't more financial aid available?
A: We are proud to run a program that, with high probability, significantly increases the earnings power of our graduates over the long run. Some students from our first cohort have already paid off all of their loans from cash bonuses or other forms of deferred compensation received. We are confident that the return on investment associated with this particular professional program is superior to the return on investment from many other forms of professional training (law, medicine, etc.). There is a shortage of data scientists on the job market right now, and that shortage is projected to get far worse before it gets better.

Q: When is my tuition payment due?
A: You must either pay in full or sign up for a payment plan by the due date each semester. Your admission deposit is applied to your tuition payment plan. Tuition due dates are May 1 for Summer semester, August 1 for Fall semester, and January 2 for Spring semester. If you fail to pay by the due date, a hold is placed on your account and you are not able to register for classes until payment is received.

Practicums and job placement

Q: Which companies do MSAN students work with as part of their practicum?
A: One of the major advantages of the MSAN program at the University of San Francisco is that students work on real projects in real companies for approximately 10 months out of their 12-month experience. Many practicum companies are within walking distance from USF's downtown campus at 101 Howard Street. Students in the 2013-2014 cohort worked with Williams-Sonoma, The Weather Company, DataFox, Turbo Financial Group, Iteris, Autogrid, and Clorox, among others. See project opportunities for more details.

Q: What is the job placement rate for graduating students?
A: Students graduating from the University of San Francisco's Master of Science in Analytics (MSAN) program are embedded in the world's largest concentration of technology companies. Graduates find it easy to get challenging and well-paying jobs. For example, our computer science program, which supplies three MSAN faculty members, is recognized as having one of the highest returns on investment in the country, even above MIT. 

12 out of 12 students from the 2012-2013 cohort took positions within four months of graduation. Students received an average of 1.78 job offers (range: 1-3 offers). The median initial salary (not including deferred compensation) was $85,000.00 per year among those students who reported an initial salary. The maximum base salary offer was in excess of $100,000.00 per year. The job titles assumed by our graduates include: Data Scientist, Big Data Analyst, Consultant II Health Intelligence Reporting Manager Data Analysis, Senior Software Engineer -- Algorithms, Data & Quality Hacker, and Business Intelligence Data Analyst.

In approximately October 2014, we will release job placement data for the students in the second cohort of our program (i.e., academic year 2013-2014).


Program admission: requirements and timetables

Q: What are the key background requirements?
A: You can learn more on the application pagebut students must have high grades in prior coursework in probability and statistics, linear algebra, and computer programming (for example, Python, Java, C++, MATLAB, etc.). Applicants must hold a bachelor’s degree. Typically, though not always, our applicants majored in mathematics, engineering, economics, statistics, or computer science. Thirty-six percent of the 2014-2015 cohort was already in possession of a master's or doctoral degree in a technical field at the time of matriculation.

Q: I haven’t completed all of the program requirements. Can I complete the requirements during the program?
A: You must have completed all required prerequisites before the program begins. The program is very intense and there is no time to take extra courses.

Q: Does USF offer courses that will satisfy the prerequisites for the program?
A: Yes. Please consult the catalog for more information on mathematics and computer science. You can take these as a visiting student prior to applying for the analytics program.

Q: I'd like to take a course at the University of San Francisco to satisfy the linear algebra prerequisite. Which course should I take?
A: You should take MATH 230 (Elementary Linear Algebra). The Department of Mathematics typically offers this course course every year in the fall semester. MATH 202 (Linear Algebra and Probability) satisfies neither the linear algebra nor the inferential statistics prerequisite for the MSAN program.

Q: I'd like to take a course at the University of San Francisco to satisfy the inferential statistics prerequisite. Which course should I take?
A: You should take MATH 101 (Elementary statistics). The Department of Mathematics typically offers this course every semester. There are other courses at the university that satisfy the inferential statistics prerequisite, such as MATH 102 (Biostatistics), MATH 103 (Statistics for the Social Sciences), or ESS 200 (Statistics). We will also accept two-course sequences in probability theory and mathematics statistics for mathematics majors as satisfying the inferential statistics prerequisite. For example, at the University of San Francisco, this sequence is composed of MATH 370 (Probability with Applications) and MATH 371 (Statistics with Applications).

 

Q: I'd like to take a course at the University of San Francisco to satisfy the computer programming prerequisite. Which course should I take?
A: You should take CS 110 (Introduction to Computer Science I). The Department of Computer Science typically offers this course every semester. CS 110 features Python, a preferred programming language for the MSAN program. However, our more competitive applicants have also taken the equivalent of CS 112 (Introduction to Computer Science II), a second course in computer programming that typically features Java and requires students to build more sophisticated and larger programs.

Q: What kind of programming experience do I need to satisfy the requirements?
A: 
Programming experience is necessary to be successful in the MSAN program. Evidence can be in the form of a formal transcript or practical experience, but we definitely prefer students whose code has been evaluated by a college-level instructor as part of a traditional programming course. Note that HTML, web design, PHP, Microsoft Excel, VBA, etc. might be valuable, but they do not count towards programming experience. We prefer knowledge of programming languages like Python, Java, C#, C++, Matlab, or Mathematica.

Q: I'm only missing one of the prerequisites for your program, and I'm in the middle of taking a Coursera or other online course that will substitute for that prerequisite.
A: Given the uncertainties surrounding online coursework, and the failure of many online courses to provide a mechanism by which student code is checked for plagiarism and evaluated, students should show in-person coursework on transcripts from two- or four-year accredited academic institutions to have a competitive application.

Q: What GRE or GMAT scores are you looking for?
A: The students enrolled in the class of 2014-2015 had the following relevant scores:
Median Quant GRE percentile   93% (interquartile range 87%-99%)
Median Quant GMAT percentile   90% (interquartile range 76%-97%)
While the GRE exam is not a perfect measure of academic achievement or potential to be a successful data scientist, prospective students scoring strictly less than 160 on the quantitative portion are increasingly non-competitive for the Master of Science in Analytics program.

 

Q: What is the minimum GPA required?
A: We do not have a minimum GPA requirement but we examine transcripts carefully. For example, the median undergraduate cumulative grade point average exceeds 3.40.

Q: What is the typical acceptance rate?
A: For the 2014-2015 cohort, there were 261 applicants with fully complete applications of which 38 were sent formal acceptance letters (i.e., an acceptance rate of approximately 15%). We anticipate that the acceptance rate for the 2015-2016 cohort will again be between 10% and 20%.

Q: What are the programming languages used in the program?
A: 
We mostly use R, Python and SQL, although we also use SAS. To be competitive in a wide variety of jobs after graduation, our students are required to pass the SAS Base Programming Certification Examination.

Q: Is there an early admission deadline?
A: Yes. We review the existing pool of completed applications during the first week of December each year. A limited number of seats in each cohort will be reserved for students who apply early, successfully complete our interview process, are admitted, and place a deposit in a timely fashion.

Q: Are admission decisions made on a rolling basis?
A: Yes. Starting in January of each year, we process applications on an ongoing basis. Some applicants are summarily denied. Some applications are placed on hold until the main March application deadline. Other applicants are interviewed and admitted to the program before the main March application deadline. In general, we advise prospective students who are highly motivated to join our program to apply as early as possible in the admissions cycle.

International students

Q: Is the Analytics Program open to international students?
A: Yes, the program welcomes international applicants. Approximately 21% of the 2014-2015 cohort is composed of international students. These international students will hail from India, China, France, and Turkey.

Q: What is the minimum TOEFL score that you will accept? 
A: 
The program seeks applicants with TOEFL scores of 90 or higher. The 2014-2015 cohort has a median TOEFL score of 107 (range 96-115).

Q: I have completed an undergraduate degree at a college or university in a country where English is the official language. Do I still need to take the TOEFL?
A:
 The TOEFL is waived for applicants who have completed a bachelor's degree, a master's degree or two years or more of studies in a degree program in English at a higher education institution in the United States, Canada, United Kingdom, Ireland, Australia or New Zealand. The TOEFL is also waived for applicants from Norway and Iceland.

Q: Are there loans or scholarships available for international students?
A: The graduate admissions office provides a list of organizations that offer financial resources for international students. You can find more information on financial aid or loans available to international students at the One Stop office.

Q: Will I be able to request CPT or OPT? Is the Analytics program a STEM major?
A: International graduates typically apply for OPT (Optional Practical Training) after they graduate. MSAN qualifies as a STEM major. International students apply for CPT (Curricular Practical Training) during the academic year if their practicum assignment is paid. Some practicums are paid and some are unpaid—this matter is left to the discretion of each practicum company. Please direct all further questions regarding CPT, OPT, or STEM to the office of International Student and Scholar Services at isss@usfca.edu.

Q: What is life like in the United States?

Q: What is life like in the San Francisco?
A: Consider Jason Evanish’s blog post 25 Things I Wish I Knew Before Moving to San Francisco.