We be using Python 3 as the language for some of the programming assignments. It can be found at python.org. It is recommended to use the Spyder IDE, which can be downloaded at: spyder-ide.org
The Spyder IDE comes with the Scikit-learn Python library, which will also be used in the course. If Spyder is not used, you will need to install Scikit-learn from scikit-learn.org.
You will also need a spreadsheet software (e.g., MS-Excel), as well as other software tools that will be described during the course.
An introduction to data science and discovery from data: Data wrangling, feature engineering, feature selection, statistical inference, correlations, principal component analysis, classification, regression, novelty detection, clustering, cross-validation, bootstrapping, class profiling, multidimensional scaling, association rules, visualization, data science & society
The course is an introduction to use basic concepts of Data Science, the link between Data Science and Computer Science, application of Data Science, and practical knowledge on solving and approaching problems using data science paradigms. The concepts covered in the course are the following:
A substantial part of the learning will be done by working on a research project that aims at solving an unexplored research question using data. The data science concepts will be used in the context of solving a real-world problem, until the question is profiled and explained using data.
Unlike some other courses, the assignments (steps) of the research will sometimes be given before the concepts used in them are introduced in the course. Working on the research assignments will be done in parallel to discussions of these concepts in the course.
By the end of this course, each student will be able to
This course will be drastically different from the “traditional” on-line courses you are likely familiar with or took in the past. In this course, a substantial part of the learning will be done through hands-on research, working on an authentic research project in which we will make discoveries from data.
Assignments are to be completed without any collaboration with classmates or other outside help unless otherwise stated. Any unauthorized aid may result in a 0 for the assignment and/or report submitted to the Academic Honor Council.
Letter grades will be assigned following the standard scale:
All work is expected to be submitted on time. Late work can only be allowed with the explicit approval of the instructor.
As mentioned above, the course will be heavily based on research experience. Research will start when all students work on the same research project, and as we approach to the end of the semester, students will do their own research projects. Guidance on performing the project will be given during the course.
Assignments may be part of the research project. It is acceptable to communicate with the instructor and other students about the concepts in the assignments, and that communication should be in the discussion board. Information will often be posted on the discussion the Canvas board.
A major part of the course is a research project. Details about the research and specific instructions about the research will be given during the course. The deliveries will be the project is the code, the data, an article describing the project, and a final presentation.
Information about writing the final paper will be given in the course. The final paper will describe all parts of the research project. It will include a separate summary of the entire project (abstract), followed by an introduction, data section, result section, and conclusions. The length of the paper will be 2000-5000 words. Detailed information about writing the paper will be provided in the course.
Each student will prepare a final presentation of 10 minutes that describe her/his research project. The final presentation will be videotaped. Students will be required to upload their presentation to YouTube or any other service, and submit a link through Canvas so that all students can view the presentation. The presentation should provide the description of the research question that you aimed at solving, the data that you collected and used, the methods that you used for analyzing the data, the results of your analysis, and the conclusion of your results.
The details in this syllabus are not set in stone. Due to the flexible nature of this course, especially the research component of it, adjustments may need to be made as the semester progresses, though they will be kept to a minimum. If any changes occur, the changes will be posted on the K-State Canvas page for this course and emailed to all students, as well as the Canvas discussion board.
Kansas State University has an Honor and Integrity System based on personal integrity, which is presumed to be sufficient assurance that, in academic matters, one’s work is performed honestly and without unauthorized assistance. Undergraduate and graduate students, by registration, acknowledge the jurisdiction of the Honor and Integrity System. The policies and procedures of the Honor and Integrity System apply to all full and part-time students enrolled in undergraduate and graduate courses on-campus, off-campus, and via distance learning. A component vital to the Honor and Integrity System is the inclusion of the Honor Pledge which applies to all assignments, examinations, or other course work undertaken by students. The Honor Pledge is implied, whether or not it is stated: “On my honor, as a student, I have neither given nor received unauthorized aid on this academic work.” A grade of XF can result from a breach of academic honesty. The F indicates failure in the course; the X indicates the reason is an Honor Pledge violation.
For this course, a violation of the Honor Pledge will result in an automatic 0 for the assignment and the violation will be reported to the Honor System. A second violation will result in an XF in the course.
Students with disabilities who need classroom accommodations, access to technology, or information about emergency building/campus evacuation processes should contact the Student Access Center and/or their instructor. Services are available to students with a wide range of disabilities including, but not limited to, physical disabilities, medical conditions, learning disabilities, attention deficit disorder, depression, and anxiety. If you are a student enrolled in campus/online courses through the Manhattan or Olathe campuses, contact the Student Access Center at accesscenter@k-state.edu, 785-532-6441; for K-State Polytechnic campus, contact Academic and Student Services at polytechnicadvising@ksu.edu or call 785-826-2674.
All student activities in the University, including this course, are governed by the Student Judicial Conduct Code as outlined in the Student Governing Association By Laws, Article V, Section 3, number 2. Students who engage in behavior that disrupts the learning environment may be asked to leave the class.
Kansas State University is committed to providing a safe teaching and learning environment for student and faculty members. In order to enhance your safety in the unlikely case of a campus emergency make sure that you know where and how to quickly exit your classroom and how to follow any emergency directives. To view additional campus emergency information go to the University’s main page, www.k-state.edu, and click on the Emergency Information button, located at the bottom of the page.
K-State has many resources to help contribute to student success. These resources include accommodations for academics, paying for college, student life, health and safety, and others found at www.k-state.edu/onestop.
To protect the health and safety of the K-State community, students, faculty, staff and visitors must wear face coverings over their mouths and noses while on K-State campuses in all hallways, public spaces, classrooms and other common areas of campus buildings, and when in offices or other work spaces or outdoor settings when 6-feet social distancing cannot be maintained. In addition, all students, faculty, and staff are required to take the COVID-19 and Face Mask Safety training. Employees who need reasonable accommodations and assistance related to required face coverings may contact the ADA coordinator at charlott@k-state.edu, and students needing accommodations may contact the Student Access Center at accesscenter@k-state.edu. In classrooms, faculty have the right to deny a student entry into the room if the student is not wearing a face covering.
Kansas State University is a community of students, faculty, and staff who work together to discover new knowledge, create new ideas, and share the results of their scholarly inquiry with the wider public. Although new ideas or research results may be controversial or challenge established views, the health and growth of any society requires frank intellectual exchange. Academic freedom protects this type of free exchange and is thus essential to any university’s mission.
Moreover, academic freedom supports collaborative work in the pursuit of truth and the dissemination of knowledge in an environment of inquiry, respectful debate, and professionalism. Academic freedom is not limited to the classroom or to scientific and scholarly research, but extends to the life of the university as well as to larger social and political questions. It is the right and responsibility of the university community to engage with such issues.