1st lesson free
Oluwanifemi
- Rate £12
- Response 1h
£12/hr
Contact
1st lesson free
- Maths
- Science
- Computing
Subject: Mathematics, Sciences, and Computing. Level: GCSE, A-Level stages, university students Location: Zoom/google meet Qual: (MSc) in Data Science, (BSc) in Computer Science. Python, SQL, Java,
- Maths
- Science
- Computing
Lesson location
About Oluwanifemi
As a BSc Computer Science and MSc Data Science graduate, I offer my students a unique blend of academic rigour and real-world technical expertise. My background allows me to bridge the gap between abstract theory and practical application, ensuring that students don't just memorise formulae, but master the logic behind them.
I am a dedicated professional who takes great pride in my students' success. Whether I am introduced to a 7-year-old beginning their journey into logical thinking or a University student navigating complex statistical models, I bring a structured, patient, and results-driven approach to every session.
Junior Learners (Ages 7–11): At this stage, I focus on Conceptual Visualisation. I transform abstract mathematical and logical problems into relatable, everyday scenarios. We use interactive tools to build "computational thinking," which serves as the bedrock for future success in both Maths and Sciences.
GCSE & A-Level Students: My approach is centred on Exam Specification Mastery. I break down complex mark schemes and focus on high-yield exam techniques. We move systematically from foundational theory to guided practice, ensuring students are equipped to handle even the most challenging non-routine questions.
Undergraduate & Adult Learners: For those studying Data Science or Computing, I utilise a Project-Based Approach. We work within real-time coding environments (Python, SQL, R) to apply theory to actual datasets, ensuring the skills learned are industry-ready.
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About the lesson
- All Levels
- English
All languages in which the lesson is available :
English
Junior Students (Ages 7–11): I use "Gamified Learning." We use visual platforms like Scratch for coding and relatable real-world examples for maths to keep engagement high.
For GCSE & A-Level Students: I focus on Pattern Recognition and Exam Technique. We break down complex mark schemes and use "spaced repetition" to ensure formulae and logic pathways are committed to long-term memory.
For Data Science/Degree Students: We use a Project-Based Approach. We work through real datasets using Python or SQL so you can see how theory applies to industry-standard analytics.
Junior Students (7–11): I recommend 45-minute sessions. This matches the natural attention span of younger learners and ensures we finish on a high note.
GCSE, A-Level, and Degree: I recommend 60 to 90-minute sessions. These subjects require "deep work," allowing us enough time to tackle a difficult concept and then apply it to several practice problems.
I bring a high level of technical rigour to my tutoring, backed by advanced academic credentials:
MSc in Data Science: Specialised in high-level statistics, machine learning, and data visualisation.
BSc in Computer Science: Expert knowledge in software development, algorithms, and logic.
Tutoring Experience: I have coached students through the 11+ and GCSE transitions, as well as helping university students debug complex data projects. Being a recent graduate myself, I understand the current pressures of the curriculum and how to navigate modern exam boards.
I offer a Full-Stack educational service, catering to:
Primary/Junior (Ages 7+): Building a strong foundation in "Mental Maths" and "Digital Literacy."
Secondary/GCSE: Focused support in Maths and Computer Science.
A-Level & Further Education: Specialising in Mathematics and Computer Science (coding & theory).
Adults & Career Changers: Introduction to Data Science, Python programming, and Big Data concepts.
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Rates
Rate
- £12
Pack prices
- 5h: £60
- 10h: £120
online
- £12/h
free lessons
The first free lesson with Oluwanifemi will allow you to get to know each other and clearly specify your needs for your next lessons.
- 1hr
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