INTERESTS
Now that I have retired as a professor, I am spending most of time learning more about computers, computer science and related fields. The topics below, besides being study areas, are also my own classification for learning purposes.
COMPUTER SCIENCE FOUNDATIONS
In this category I include data structures, programming concepts (not linked to a particular language), algorithms, operating systems, etc.
PROGRAMMING
This category includes programming languages such as C, Python, Visual Basic for Applications and JavaScript. I even like older, less common programming languages such as Pascal and Cobol. Turbo Pascal remains my favorite!
ARTIFICIAL INTELLIGENCE
This category includes the concepts of artificial intelligence but also the tools. As such, it then includes: machine learning, natural language processing, neural networks, deep learning, etc. And tools like: ChatGPT, Gemini, Copilot, Claude, NotebookLM, etc.
DATA SCIENCE
This category includes: machine learning, data collection, data analysis, data visualization and databases (including SQL). I also include here libraries used for data science such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, etc.
IT, CLOUD COMPUTING & NETWORKS
This is a "composite" category that includes three areas that closely overlap with each other. Specific topics that I include in this category are: Linux CLI, Windows CLI, virtual machines, cloud services, network concepts and protocols, and security.
WEB DEVELOPMENT
This category encompasses everything related to web development from front-end to back-end. It includes web design, languages (HTML, CSS, PHP), frameworks & libraries (React, Angular, Django, Bootstrap, ExpressJS), run-time environments (NodeJS).