RFP: Course Development, Online Course in Cybersecurity for Artificial Intelligence and Machine Learning
The Master of Information and Cybersecurity program at the School of Information at UC Berkeley seeks proposals for an online graduate course in Cybersecurity for Artificial Intelligence (AI) and Machine Learning (ML).
About the Proposed Course
Proposals will outline a 14-week, master’s level online learning course experience that covers key aspects of the rapidly evolving intersection of cybersecurity, artificial intelligence (AI), and machine learning (ML). The course should focus on both secure AI/ML systems and use AI/ML techniques to enhance cybersecurity against evolving threats.
The instructor should assume that students are self-motivated, advanced master’s degree students who have completed one or more courses in natural language processing and/or machine learning. Furthermore, the instructor should assume students will be proficient, but not expert programmers in modern general-purpose programming languages (e.g., Python) and be familiar with ML frameworks and/or tools (e.g., scikit-learn, TensorFlow, or PyTorch). Topics covered in the proposed course should include but are not limited to, cybersecurity principles (e.g., CIA triad); AI & ML security (e.g., types of models, training processes); common ML algorithms from a security lens (e.g., decision trees, neural nets); use cases of where AI meets cybersecurity; adversarial machine learning (e.g., evasion attacks, poisoning attacks); secure model training & deployment (e.g., data validation, access control); AI system auditability and explainability; network traffic analysis; user and entity behavior analytics; using ML for malware detection and classification; AI intrusion detection systems; using AI for security automation, LLM threats; bias, fairness, & data integrity in AI systems; ethics of AI in security (false positives); data governance for ML pipelines; AI and human-in-the-loop security systems; designing usable and trustworthy AI security systems; social engineering attacks powered by AI (e.g., deepfakes, voice cloning); open-source security datasets (CICIDS); labs related to train a model for malware detection; secure and defend the model; NIST AI Risk Management Framework; AI and cybersecurity laws.
The successful proposal will be accepted for development and offered in the MICS online degree program. Since this is a fast-moving field, the course contents are expected to be continually revised.
Although typical MICS courses have 1.5 hours of pre-recorded asynchronous content, due to the fast-moving pace of this topic, for this course, we are open to innovative designs for content delivery so long as they meet the required contact hours (45 hours/semester).
About the MICS Program
The Master of Information and Cybersecurity (MICS) online program prepares students with the cybersecurity skills to assume leadership positions and drive innovation in the field.
Deliverables for Accepted Proposal
Instructors of accepted course proposals will be expected to produce well-designed, reusable presentation slides, structured topic outlines for discussion sections, and assignments that reinforce the course’s key objectives. Instructors will collaborate closely with an instructional designer and video producer to ensure the course meets established quality standards and fully aligns with defined learning objectives and outcomes. This partnership is integral to creating a high-impact, student-centered online learning experience.
Submission Requirements
Respondents to this RFP must submit a cover letter and draft syllabus using the webform below. Draft syllabus should contain at a minimum a course description, weekly topic breakdown for a 14-week course, brief descriptions of assignments, grading information, and a reading list.
Responses must be received no later than May 16, 2025 for fullest consideration and will be accepted until selection is complete.
Strong preference will be given to course developers interested in continuing their association with the School of Information by applying to teach the developed course as a lecturer. The separate lecturer application can be found here: https://aprecruit.berkeley.edu/JPF04649
Compensation
Compensation for course development will be offered via vendor payment from UC Berkeley. To be eligible to receive compensation, the successful proposer will need to register with the UC Berkeley Accounts Payable Vendoring Team and must meet all applicable university requirements. Our expert team will walk you through the process to ensure that your vendor profile is active before work proceeds. This is not a visa opportunity.
The University of California, Berkeley is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy, see: http://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct
Questions
Questions about this call for proposals can be directed to Dr. Christina Arias, Assistant Dean of Academic Programs.
