Faculty Interview Questions and Answers - A Free Guide for CS/CIS Academic Job Seekers

This is a free reference guide for academic job seekers in computer science and computer information systems. It collects more than 60 common faculty interview questions, with synthesized sample answers and strategic frameworks for responding.

It covers the kinds of questions candidates face across the process, from research and teaching statements to service, fit, and the on-campus visit, with guidance on how to structure strong answers.

The goal is a single, practical resource to prepare with. It is archived on Zenodo with a citable DOI.

DOI: https://doi.org/10.5281/zenodo.20585412

CyberQuest Summer Camp 2026 - A Free Five-Day High School Cybersecurity Curriculum

CyberQuest Summer Camp 2026 is a completely open-access curriculum for a five-day high school cybersecurity camp. It includes a 124-page PDF textbook, interactive HTML slide decks for all five days, Python notebooks, and integrations with free tools.

The topics span networking, threat modeling, cryptography, web security, ethical hacking, AI security, and a Capture the Flag exercise. The material is mapped to widely used frameworks including CompTIA Security+, CEH, and NIST.

Everything is free to use and adapt for teachers, camp organizers, and self-learners. It is archived on Zenodo with a citable DOI.

DOI: https://doi.org/10.5281/zenodo.20635564

LSTM-Demo: Bidirectional LSTM with TensorFlow on the Sonar Dataset

LSTM-Demo is a compact, runnable example that trains a bidirectional Long Short-Term Memory (LSTM) network with TensorFlow and Keras on the classic Sonar dataset.

The Sonar dataset is a well-known binary classification benchmark: each sample has 60 numeric features from sonar returns, and the task is to tell metal cylinders (mines) from rocks. It is small enough to train quickly while still showing a full pipeline.

A bidirectional LSTM reads the input sequence in both directions, which can help the model use context from the whole sequence. The demo is intended as a teaching example you can run, read, and modify. It is archived on Zenodo with a citable DOI.

DOI: https://doi.org/10.5281/zenodo.20672929

Generative AI with Amazon Bedrock - A Free Open Textbook

This is a free, open online textbook on generative AI, large language models, and building applications with Amazon Bedrock, adapted and expanded from the AWS Machine Learning University generative AI curriculum.

It opens with an AI Literacy Primer and then covers three full modules: Fundamentals of Generative AI, Responsible Generative AI, and Building Applications with Foundation Models. The applied module includes hands-on Amazon Bedrock lab notebooks.

The aim is a practical, self-contained path from core concepts to building and evaluating real foundation-model applications, with attention to responsible use. It is archived on Zenodo with a citable DOI.

DOI: https://doi.org/10.5281/zenodo.20652883

Links-Extractor: Extract Internal and External Links from a URL in Python

Links-Extractor is a small Python utility that takes a single URL and pulls out every hyperlink on the page, separating them into internal links (pointing to the same domain) and external links (pointing elsewhere).

Splitting links this way is useful for SEO audits, for finding broken or outbound links, for mapping the structure of a site, and as a starting point for a larger crawler. You give it a URL and get back two clean lists you can save or process further.

The project is open source and meant to be easy to read and adapt. It is archived on Zenodo with a citable DOI.

DOI: https://doi.org/10.5281/zenodo.20672987