Welcome to an NCSU Data Science Academy Course! In July 2021, the university-wide and interdisciplinary Data Science Academy (DSA) was launched to meet the growing needs of data science research, education and expertise in North Carolina and beyond. At NC State, Data Science is for Everyone. Data Science Academy Courses are designed to make sure that each student can pursue appropriate level challenges through opportunities to make choices and pursue projects of interest. DSA courses will highlight the work of a diverse group of data scientists, bring attention to ethical issues, teach design for accessibility, and explore current issues in data science research and practice. The DSA will develop courses that attract and serve students from all ten NCSU colleges and beyond. Whether you have never thought about data science before or bring experience and expertise, we welcome you. Our goal is that after each DSA class you want to learn more!
To make sure that we are providing an appropriate collection of courses with a variety of challenge levels within each course, we will be collecting data to help us build a practice of continuous improvement. The purpose of the data is to evaluate the DSA and how well we are serving our students. We hope to be able to share what we learn with other universities and researchers - we will ask your permission at the beginning of the course to be able to share your de-identified data when we communicate about the work of the DSA.
In 2021 alone, a cyber attack occurred once every 39 seconds on average. Data Science for Cybersecurity will introduce students to the use of data to discover, explore, and address relevant cybersecurity use cases. Students will become familiar with fundamental approaches to tackle common cybersecurity problems using Python in this introductory-level course.
Instructor: Jessy Ayala
Email: jayala2 [at] ncsu [dot] edu
Meeting Time: See Moodle
Format: Online
Zoom Link: See Moodle
By the end of this course, students will be able to:
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Explain common use cases of data science applied to cybersecurity
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Describe approaches to address common cybersecurity problems including spam classification and anomaly detection
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Recognize and describe limitations of using algorithms to tackle cybersecurity problems
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Use Python to load and analyze cybersecurity data from CSV format
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Create datasets that can be used in a cybersecurity context
Some familiarity with Python is recommended.
Week 1: Course overview and introduction
Week 2: Python basics intro
Week 3: Ciphers
Week 4: Dataframes
Week 5: Data visualization
Week 6: Spam or ham
Week 7: URL classification
Week 8: Project proposals check-in (Checkpoint 1)
Week 9: Anomaly detection
Week 10: Fall/Spring break (no class)
Week 11: Intrusion detection
Week 12: Addressing security in open-source repositories
Week 13: Project progress check-in (Checkpoint 2)
Week 14: Work on project
Week 15: Project presentations
Week 16: Project deliverables due
~50% Course Project (built-upon throughout the semester)
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Checkpoints: 10%
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Presentation: 15%
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Deliverable(s): 25%
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See project guidelines for more details and actual point breakdown
~24% Additional Exercises (weekly)
- 8 take-home and credit-based assignments, worth 3% each and due before the following lecture
~18% Discussion Board (bi-weekly ish)
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6 discussion board assignments, worth 3% each and due before the following lecture
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Active responses to multiple posts may bump grade up at the end depending on where you stand
~10% Peer Review (two instances)
- Peer review on others' project submissions, worth 5% each requiring 2 feedback responses
The course will follow all NCSU academic integrity regulations. All students are expected to maintain traditional standards of academic integrity by giving proper credit for all work. All suspected cases of academic dishonesty will be aggressively pursued. A student shall be guilty of a violation of academic integrity if he or she represents the work of others as his or her own or aid another’s misrepresentation.
We encourage you to read the ACM Code of Ethics, particularly Sections 1.3, 1.5, 1.6, 2.2 and 2.4: https://www.acm.org/code-of-ethics
All persons, regardless of age, race, religion, gender, physical disability or sexual orientation shall have equal opportunity without harassment in this course. Any harassment should be reported immediately to the instructor.
Students are responsible for reviewing the NC State University PRR’s which pertains to their course rights and responsibilities:
https://policies.ncsu.edu/policy/pol-04-25-05
Additional references at: https://oied.ncsu.edu/equity/policies/
Students are expected to conduct themselves in a respectful and professional manner at all times. Grades will be adjusted if students do not handle themselves in a respectful and professional manner with all members of the teaching staff and with others in the class - both in person and electronically (email, message board posts). See more details at: https://policies.ncsu.edu/policy/pol-11-35-01
The course will follow all NCSU regulations relevant to students with disabilities. Any students requiring additional assistance due to disabilities (e.g., learning disabilities), should contact the instructor during the first week of the semester. Students requiring extra time for examinations and quizzes are asked to make arrangements at least three days in advance. You may contact the NCSU Disability Services for Students Office regarding campus services at the Student Health Center for more information and assistance: http://www.ncsu.edu/dso/students