Kenyatta University
Statistics & programming
My studies bring together statistical reasoning and programming: understanding what data can tell us, then expressing that reasoning through code. I am interested in the connection between mathematical ideas, analytical judgement and practical implementation.
I approach learning by breaking a problem into smaller questions, examining assumptions and comparing results. Python, JavaScript and C give me different ways to explore those questions, from analysing information to understanding how software behaves.
- Statistical reasoning, data interpretation and analytical thinking
- Programming foundations and systematic problem-solving
- Connecting academic concepts with practical experiments
From ideas to working software
ROTICH TECHNOLOGIES
ROTICH TECHNOLOGIES is my personal initiative for bringing together software, data and thoughtful interface design. The portfolio includes Data Studio, Regression Explorer and Sampling Simulator—interactive tools that let visitors explore ideas using data and clearly stated assumptions.
My focus extends beyond how a page looks. I care about how information moves through an application, how user input is validated and how errors are communicated. Each iteration is an opportunity to improve usability, test behaviour and make the implementation easier to understand.
- Interactive data tools and browser-based demonstrations
- Clear interfaces, accessible interactions and responsive layouts
- Application validation, testing and iterative refinement
Current learning directions
Intelligent, secure & connected systems
I am exploring how machine learning and language models can support useful applications, while developing a deeper understanding of the security and backend systems around them. I am particularly interested in connecting intelligent features to clear user needs rather than adding technology for its own sake.
IoT and embedded programming are further learning directions: how devices collect information, communicate with software and protect the data they handle. These interests guide future experiments; they are not claims of completed projects or commercial experience.
- Applied AI, model evaluation and responsible integration
- Authentication, API security and defensive engineering
- IoT architecture, device communication and embedded fundamentals
