Baines Blogging

  I Graduated with a 2:1 in Computing from Sheffield Hallam University! I'm incredibly proud to share that I’ve officially graduated from Sheffield Hallam University with a 2:1 in BSc Computing! It’s been a challenging, rewarding, and ultimately fulfilling journey, and I’m grateful for all the experiences, both technical and personal, that have shaped me along the way. From learning core computing principles to diving deep into specialist areas, my time at university has equipped me with the tools and confidence to move forward in the tech world. One of the standout modules for me was Data Management. I found it fascinating to explore how data is structured, stored, and retrieved, and how good design can make or break the efficiency of a system. This module really laid the groundwork for many of my later projects, giving me the practical skills and theoretical understanding to handle data effectively and responsibly—something that proved crucial in my final year work. My Artific...

1. Begin with the 16 “rules” of Esperanto and its simple grammar Start by immersing yourself in the concise foundational rules of Esperanto: its phonetic spelling, predictable affixation, and regular verb system make it far easier to grasp than many natural languages. For a clear overview of why Esperanto is easier to learn than typical languages, see Why Learn Esperanto? (Lingolia) which outlines its regularity and simplified grammar. ( esperanto.lingolia.com ) 2. Use a structured online course to build vocabulary and grammar Enroll in a free, guided Esperanto course such as Transparent Language’s Esperanto module (which offers vocabulary lists, interactive exercises and listening tasks) to build a solid grammar and vocabulary foundation. ( Transparent Language ) 3. Complement your lessons with the community platform Lernu! Pair your formal lessons with practice on Lernu! , the free multilingual Esperanto learning site, which offers exercises, multimedia, dictionaries, and a co...

Unlocking the Power of Data Analysis: Tools and Techniques for Understanding User Feedback Data analysis is the backbone of decision-making across countless industries, providing insights that drive business strategy, marketing decisions, and customer experience improvements. With the explosion of user-generated content on platforms like YouTube, analyzing user comments has become a powerful tool to understand public sentiment, track brand reputation, and improve user engagement. Step 1: Data Collection – Pulling User Comments from YouTube Before any analysis can happen, we first need the data. In the case of YouTube, user comments are stored publicly on each video. To collect them, we use the YouTube Data API . This API allows us to programmatically retrieve comment data, such as the text of the comments, the date posted, and user metadata (like user ID or username). Here’s how it works: Set up the API : First, you’ll need to create a project on the Google Cloud Console, enab...

This is a summary of my GitHub Pages site!   https://cuthbert86.github.io/ It is my personal corner of the web where I’m showcasing a range of projects and experiments as I learn more about web design and development. Whether you’re a fellow tech enthusiast, a curious visitor, or someone interested in learning alongside me, I hope you’ll find something interesting and useful here. The site is a living portfolio, featuring examples of my work as I explore different technologies and programming concepts. You’ll see projects built with HTML and enhanced with popular web tools like Bootstrap, giving my pages a clean and responsive look. I’m always updating and improving the design as I pick up new techniques, and many of the pages reflect my journey in web development. One of the highlights is my exploration of Python and its many applications. I’ve included projects that demonstrate data analysis, working with CircuitPython and MicroPython, and even connecting devices using MQTT....