Welcome to Your Personalized Tutoring Journey

This handbook is your launch pad, offering an overview of what to expect from our sessions, guidance on setting yourself up for success, and a short questionnaire to help me tailor the learning plan to you—no coding experience needed, just curiosity!

#1

Bring an open mind and every question you can think of. Data science is a journey of discovery, not a test you must pass on day one.

#2

Make sure you have a laptop or desktop (90%+ battery), stable Wi-Fi, a modern browser (Chrome, Firefox, Edge, or Safari), and your coding tool (like Google Colab or VS Code) ready. Headphones and a mic are optional. We can set things up together if needed.

#3

Pre-Session Reflection

Spend five quiet minutes jotting down thoughts on:

What made you interested in AI or coding? A game mod? A cool YouTube demo?
If you could wave a wand and finish one project, what would it be?
Any languages you've touched (Python, Scratch, JavaScript) or none at all?
Is there a topic that feels extra scary? That's perfect—we'll tackle it head-on.

#4

Bring Evidence of Exploration

Screenshots, scribbled notebook pages, bookmarked videos—anything that shows where you've poked around already. They spark great conversation and reveal your natural learning style.

#5

What You Don't Need

Memorised formulae or textbook definitions
A paid software licence
Perfect grammar when you write code (the computer only cares about syntax!)

How Our Sessions Will Run

Stage	Typical Duration	What We'll Do
Warm-up	5 min	Quick recap, set goals for today
Concept Sprint	10 min	Introduce a new idea (e.g. variables, charts, or algorithms)
Guided Practice	20 min	Code together, live share screen
Solo Attempt	15 min	You drive; I coach in the background
Debrief	5 min	Discuss wins, blockers, and agree mini-tasks for next time

Lesson length is flexible—this is a sample for a 60-minute slot.

🧭 Road-map for the First Month

Foundations – Python syntax, data types, and Jupyter/Colab basics
Data Wrangling – Reading CSVs, cleaning messy data with pandas
Visual Storytelling – Building your first plots with matplotlib
Mini-Project – Choose a hobby topic, ask a question, and answer it with data
Machine-Learning Taster – Train a simple classifier (e.g. predict Pokémon types!)

We'll adjust pace and order depending on your questionnaire responses and progress.

🤝 House Rules & Support

Respect – Mistakes are expected; we celebrate them as learning opportunities.
Pace – If it feels too fast or too slow, tell me straight away.
Between Sessions – Quick questions by email are welcome; larger blockers become next session's focus.
Parental Involvement (if under 18) – Guardians receive a brief lesson summary and next-step suggestions.

What Success Looks Like 🏆

By the end of our first month, you should feel confident running Python code cells, understand basic data structures (lists, dicts, DataFrames), be able to produce at least one chart that tells a story, and explain in your own words what a simple machine-learning model does.

I'm excited to start this journey with you.

If you need help completing the questionnaire or setting up your device, just drop me a message and I'll guide you through it.

Book a Tutoring Session