Course Description
The field of Data Science encompasses methods, processes, and systems that enable the extraction of useful knowledge from data. Foundations of Data Science introduces core data science concepts including computational and inferential thinking, along with core data science skills including computer programming and statistical methods. The course presents these topics in the context of hands-on analysis of real-world data sets, including economic data, document collections, geographical data, and social networks. The course also explores social issues surrounding data analysis such as privacy and design.
Materials and Resources
Our primary text is the online book called Computational and Inferential Thinking: The Foundations of Data Science. This text was written by Ani Adhikari and John DeNero of University of California, Barkeley. The computing platform for the course is hosted at http://datahub2.cs.umass.edu/. Students will need access to a laptop with a modern web browser to complete the lab exercises, or will need to register for a lab section held in a computer lab facility. Computer access is also required to complete homework assignments. Note that DataHub, which we will use for labs and homework assignments, may log you out of the system after 20 minutes of inactivity.
Grades
The coursework will consist of weekly homework assignments, weekly labs, a midterm exam and a final exam. The lowest two homework grades and the lowest two lab grades will be dropped from your homework and lab totals. The grading scheme is shown below:
| Activity | Grade |
|---|---|
| Homework | 35% |
| Labs | 20% |
| Midterm Exam | 20% |
| Final Exam | 25% |
Late Submission Policy
Homework assignments and labs must be submitted by the date and time they are due. Work submitted late will not count for credit.
Regrading Policy
Errors in grading of assignments, labs and exams can occur despite the best efforts of the course staff. If you believe you’ve found a grading error, please submit a re-grade request. Re-grade requests must be submitted no later than one week after a graded item is returned. Note that when a re-grade request is received, the complete assignment, lab, or exam will be re-graded from scratch. This may result in your original grade increasing, decreasing or staying the same as appropriate.
Homework Collaboration Policy
You are encouraged to discuss homework problems with other students; however, to avoid issues with the course’s academic honesty policy, you should not take any materials out of such discussions (writing, whiteboard photos, code, etc.). You should never share your completed or in-progress code or write-up with another student in any form, or request to see another student’s code or write-up. Your code and written solutions must be your own work.
For labs you can work coopertatively in class and you can share code with the people you are working with.
Course Academic Honesty Statement
Copying any homework solution materials from external sources (books, web pages, etc.) or from other students is considered cheating. Sharing your code or solutions with other students is also considered cheating. All instances of suspected cheating will be dealt with through official UMass Amherst Academic Honesty Procedures. Students are expected to be familiar with the relevant policies and procedures: http://www.umass.edu/honesty/
UMass Academic Honesty Statement
Since the integrity of the academic enterprise of any institution of higher education requires honesty in scholarship and research, academic honesty is required of all students at the University of Massachusetts Amherst. Academic dishonesty is prohibited in all programs of the University. Academic dishonesty includes but is not limited to: cheating, fabrication, plagiarism, and facilitating dishonesty. Appropriate sanctions may be imposed on any student who has committed an act of academic dishonesty. Instructors should take reasonable steps to address academic misconduct. Any person who has reason to believe that a student has committed academic dishonesty should bring such information to the attention of the appropriate course instructor as soon as possible. Instances of academic dishonesty not related to a specific course should be brought to the attention of the appropriate department Head or Chair. Since students are expected to be familiar with this policy and the commonly accepted standards of academic integrity, ignorance of such standards is not normally sufficient evidence of lack of intent: http://www.umass.edu/dean_students/codeofconduct/acadhonesty/
Accommodation Statement
The University of Massachusetts Amherst is committed to providing an equal educational opportunity for all students. If you have a documented physical, psychological, or learning disability on file with Disability Services (DS), you may be eligible for reasonable academic accommodations to help you succeed in this course. If you have a documented disability that requires an accommodation, please notify the instructors within the first two weeks of the semester so that we may make appropriate arrangements.
Course Particiation
Students are expected to attend each class and lab session.