11  Courses

There are many courses available to you within both UMass Dartmouth and the wider UMass system (as well as other options too!).

Deciding on a course of study should be done as part of your planning with Gavin, and perhaps through discussions with your committee.

Remember, this is your program and you should get out of it what you want, including the academic training of interest to you.

That said, there are some courses that most students in the Fay lab take (in part due to program requirements), so here we lay out some suggestions and provide resources for courses offered at both SMAST and elsewhere on campus that lab members have found useful.

Course of study should be selected with the program requirements in mind - as always, refer to the Intercampus Marine Science Program Manual for details.

11.1 Suggested course schedule

Students generally take a full time credit load of 9 credits per semester while they are fulfiling the credit requirements for the degree. An exception is in the first year of study when students take 10 credits to meet the graduate seminar credit program requirement.

In the Fay lab, we tend to take most (ALL?) of the quantitative courses on offer.

Several SMAST courses are offered on an alternating basis every 2 years. Particularly for MS students, you may want to take advantage of courses when they are offered, even if this means taking them out of the natural ‘sequence’.

11.1.1 Year 1

Most students take many of their core program requirements (denoted below with [C] or [PC] for policy core courses) in the first year. An exception may be PhD students who save one of the Oceanography requirements for the 2nd year, depending on other courses.

Fall MAR 540: Introduction to Fisheries Science (Stokesbury)
MAR 544: Stock Assessment of Fishery Resources (even years) (Cadrin)
MAR 555: Introduction to Physical Oceanography (Cowles/Sundermeyer) [C]
MAR 700: Graduate Seminar (Fisheries Oceanography) [C]

Spring MAR 545: Biological Oceanography (Turner) [C]
MAR 536: Biological Statistics II (Fay) (even years)
MAR 530: Ecosystem-Based Fisheries Management (odd years) (Fay) [PC]
MAR 510: Chemical Oceanography [C]
MAR 700: Graduate Seminar (Fisheries Oceanography) [C]

Typically, most remaining coursework is completed in years 2-3, but this will vary by individual.

11.1.2 Other courses Gavin will strongly ‘suggest’ you take

MAR 580: Advanced Population Modeling (Fay) (odd years)

11.1.3 Other courses you might want to take

Fall MAR 525: US Ocean Policy (Pierce, fall even yrs) [PC]
MAR 522: Science Communication for Research Scientists (Fay, fall)
MAR 599: Bayesian Statistics and Hierarchical Modeling (Fay, fall even yrs)
MAR 527: Fisheries Management (Cadrin, fall odd yrs)
Spring BIO XXX: Biological Statistics I (Kozak, spring)
MAR 622: Stock Identification Methods (Cadrin, spring even)
Based on interest MAR 5XX: Marine Resource Economics (Griffin & DePiper) [PC]
MAR 580: Conservation in World Marine Capture Fisheries (He) [PC]
MAR 580: Fish Behavior & Conservation Engineering (He)
MAR 580: Field Methods in Fisheries Research (Cadrin/Bethoney)

Of course there are lots of other course offerings - these are the ones that lab members have taken more than once. For present semester offerings, see the SMAST website. Full list of current SMAST courses and for which courses meet IMS core course requirements can be found here.

11.1.4 Other UMassD courses

Check out course offerings in Data Science (DSC), Mathematics (MTH), Public Policy (POL), Biology (BIO), Mechanical Engeering (MNE), and Computer Science (CSI) in the Graduate Handbook and on COIN.
You may find this overview of the Data Science MS program and curriculum helpful in identifying other classes!

11.1.5 Courses outside of UMass Dartmouth

Some IMS courses are offered at UMass Amherst, Boston, and Lowell.
Instructions and forms for registering for intercampus courses can be found under the ‘Academics’ section of the SMAST Occupants page.

Jarrett Byrnes (UMass Boston) statistics & R courses
Biol 607: An Introduction to Computational Data Analysis for Biology Introduction to Data Science for Biology

You may also want to talk with Gavin about taking courses at another institution, say to take advantage of even more stock assessment and statistical computing courses (e.g. Andre Punt’s courses at University of Washington.