Professional Data Analyst with 5+ Years of Python Experience at University-Level. Cambridge PhD. Online teaching with FREE first lesson.

Find out more about Shameer

• 1) Can you tell us about your first experience using a computer?

  My first real experience with a computer was at school, where I initially saw it as a tool for assignments and presentations. What changed everything was realising that a computer will do exactly what you tell it to do. No more, no less. Once I started writing small programs, it clicked that technology is not “mystical”; it’s logic made practical. What stuck with me most was the feeling of control: the computer wasn’t “magic”, it was a tool that responded to logic. That early experience made me curious about how things worked behind the screen, and that curiosity has never really left. That early curiosity grew into studying Physics at UCL and then using programming daily across data science, analytics, and software projects.

• 2) What is the technological evolution that has marked you most and what will be, in your eyes, a turning point in this field?

  The biggest evolution for me has been the shift from isolated programming to building systems that are connected, data-driven, and continuously improved; through cloud tools, modern data pipelines, and rapid iteration. I’ve seen how much more powerful work becomes when data is clean, accessible, and used well across an organisation. Looking ahead, I believe the turning point will be trustworthy AI in everyday workflows: not just “AI that can generate output”, but AI that can be audited, evaluated, and used safely in real environments. The winners in IT won’t be the people who chase hype; it’ll be those who combine modern tooling with strong fundamentals and good judgement.

• 3) Explain your expertise, your interest in it and, more broadly, its importance in the computer world.

  My expertise is in practical programming and data work: Python, SQL, and building pipelines and dashboards, alongside experience with C++ and machine learning from my academic and project background. I’ve built analysis pipelines to improve efficiency, worked with data warehouses and dashboards, and developed real-world systems that people rely on. What I enjoy most is turning complexity into clarity. Whether that’s cleaning messy data, designing a workflow that makes sense, or teaching someone step-by-step. IT matters because it underpins almost everything: communication, business operations, public services, and innovation. The people who understand it can build tools, solve problems faster, and create opportunities for others.

• 4) Do so-called “visionaries”, such as Bill Gates, Steve Jobs and Mark Zuckerberg inspire you or do you have other role models?

  I respect what they built, but I’m more inspired by people who combine technical skill with consistency and responsibility; engineers, researchers, and teachers who focus on craft and long-term impact. I also take a lot from mentors and colleagues who are calm, methodical, and clear under pressure. In IT, competence and clarity beat charisma every time.

• 5) Provide a valuable anecdote related to your subject or your days at school.

  A lesson I learned early is that confidence follows structure. When I started teaching through my tutoring work, I noticed students often believed they were “bad at coding”, when really they were missing a simple framework: break the problem down, test small parts, and iterate. One moment that stays with me is seeing students go from stuck and frustrated to independently solving problems once they learned how to debug logically. That’s also reflected in outcomes I care about: consistently strong course feedback and helping students achieve meaningful goals, not just “finish the lesson”.

• 6) What would you say to an uncomfortable person in front of a screen who says that “IT is too complicated”?

  I’d say: “It’s not too complicated, you’ve just not been shown it in the right order.” IT is a stack of small ideas that build on each other. If you skip the foundations, everything feels confusing. My approach is calm and practical: we start with the basics, we build confidence with small wins, and we practise until it feels normal. I also remind people that struggling at the beginning is expected. Nobody is “naturally good at IT”; they become good through repetition and clear explanations.

• 7) What are your other passions, related or non-related to computers?

  Outside of tech, I’m interested in activities that reward discipline and steady improvement; sports and training, and continuous learning through reading and audiobooks. That mindset carries directly into teaching. Progress is predictable when you practise consistently and measure what matters.

• 8) What makes you a Superprof in IT?

  Two things: technical range and teaching ability. And I take the second one more seriously.
  
  Technically, I can teach Python, programming fundamentals, data analysis, and practical skills like SQL and working with real datasets. But what makes students stay is that I’m structured, patient, and outcome-focused. I don’t just explain; I check understanding, I adapt to the student, and I build independence so they can solve problems alone. I also bring reliability and professionalism: clear communication, strong lesson structure, and a focus on real progress, whether that’s school support, career upskilling, or building confidence from scratch.