Clarify final course objective

Author: Vivek Gopalakrishnan

_pages/syllabus.md

@@ -11,7 +11,7 @@ author_profile: true
 If you feel your goals/desires don't fall under either category, please talk to us so we can see if something else would be feasible. 
 
 ### Course Summary
-Neuro Data Design (NDD) is a year-long project-based course where students work in teams of four to six. We offer two different levels: 4xx and 6xx. The 4xx is designed for undergraduates with background in engineering and data science and the 6xx is designed for more advanced undergraduates and graduate students. Teams are encouraged to include students at both levels, as each level brings a unique and valuable perspective. The goal of the course is to create an inspirational environment in which each of the students works on a team to build a data science product "soup to nuts", starting with ideation and ending with publication. Along the way, students learn skills that will serve them well in industry, academia, or government. To facilitate these goals, the course is divided into **Sprints**.
+Neuro Data Design (NDD) is a year-long project-based course where students work in teams of four to six. We offer two different levels: 4xx and 6xx. The 4xx is designed for undergraduates with background in engineering and data science and the 6xx is designed for more advanced undergraduates and graduate students. Teams are encouraged to include students at both levels, as each level brings a unique and valuable perspective. The goal of the course is to create an inspirational environment in which each of the students works on a team to build a data science product "soup to nuts", starting with ideation and ending with publication. **Specifically, we aim for every student in NDD to complete a research artifact (code package, data analysis, manuscript, publication) that they are responsible for by the end of the year.** Along the way, students learn skills that will serve them well in industry, academia, or government. To facilitate these goals, the course is divided into **Sprints**.
 
 ### Goals by Sprint
 The course is focused on contributing easy-to-use, well tested, well documented code to open source software repositories ([repos](https://en.wikipedia.org/wiki/Software_repository)). The instructors will provide a list of repos to contribute to and a list of issues that need tackling. We will [fork](https://help.github.com/en/github/getting-started-with-github/fork-a-repo) the public version of these repos, and students will make [pull requests](https://help.github.com/en/github/collaborating-with-issues-and-pull-requests/about-pull-requests) (PRs) into those forks. After iterating with the instructors, students will submit their PRs to the public repos, and iterate with the developers to get their PRs merged.