Programs and syllabi

The robotics track takes a student from "what makes it move" to a robot that completes a task with no one touching the controller. Students work in pairs on shared kits; every unit ends in a demo day.

R1Machines that move10 weeks — ages 8–11

• wk 1–2Levers, wheels, and gears: build three machines that trade speed for strength.
• wk 3–4First motor: wire it, reverse it, control its speed.
• wk 5–6Chassis design: build a drivebase that survives the ramp test.
• wk 7–8Remote driving challenges: precision, not speed.
• wk 9–10Demo build: a machine that solves one household-scale problem.

R2Sensing the world10 weeks — ages 10–13

• wk 1–2What a sensor really returns: numbers, noise, and why readings jitter.
• wk 3–4Touch and light sensors: a robot that stops at an edge.
• wk 5–6Ultrasonic distance: follow a wall without touching it.
• wk 7–8Line following — the classic, done properly with thresholds.
• wk 9–10Demo: navigate a course blind, sensors only.

R3Closed-loop control10 weeks — ages 12–16

• wk 1–2Open vs closed loop: why "drive 2 seconds" drifts and "drive 50 cm" doesn't.
• wk 3–5Proportional control: smooth line following, straight driving with gyro correction.
• wk 6–7Tuning: what P, I, and D each fix, discovered by breaking things.
• wk 8–10Demo: a robot that parks itself in a marked bay, repeatably.

R4Capstone: the autonomous task robot10 weeks — ages 13–16

• wk 1–2Pick a task, write the spec, defend it to the cohort.
• wk 3–7Build–test–rebuild cycles with weekly milestones and an engineering notebook.
• wk 8–9Reliability week: the robot must succeed three runs out of five.
• wk 10Demo day for parents: live run plus a short technical talk.

The coding track builds fluency: reading code, writing it, and — most neglected in kids' programs — fixing it when it breaks. Younger students start with blocks; the track lands in real Python projects with version control.

C1Logic before language10 weeks — ages 8–10

• wk 1–2Sequences and bugs: program a classmate to make a sandwich, watch it fail.
• wk 3–5Loops and events in block code: animations and a simple game.
• wk 6–8Conditionals and variables: a quiz game that keeps score.
• wk 9–10Demo: each pair ships a playable game to the cohort arcade.

C2Python, from zero10 weeks — ages 10–14

• wk 1–2From blocks to text: same logic, new spelling. First scripts.
• wk 3–5Functions, lists, and loops — drilling until they're boring.
• wk 6–8A text adventure engine, built up feature by feature.
• wk 9–10Demo: cohort plays each other's adventures and files bug reports.

C3Data, files, and small tools10 weeks — ages 12–16

• wk 1–2Reading and writing files; a program that survives being closed.
• wk 3–5Working with real datasets: clean it, count it, chart it.
• wk 6–8Build a small tool someone else would actually use.
• wk 9–10Demo: hand your tool to another pair and watch them use it cold.

C4Capstone: ship it10 weeks — ages 13–17

• wk 1–2Project pitch and scope cut — half of every first idea gets removed.
• wk 3–4Version control: commits, branches, and why professionals bother.
• wk 5–8Build sprints with weekly code review from instructors.
• wk 9–10Publish the project with a readme and present it on demo day.

Not "prompt tricks." Students train, test, and break small models so they understand what machine learning is — and build the judgment to question what it tells them. Requires Python (C2) or equivalent.

A1How a model learns10 weeks

• wk 1–2Prediction by hand: guess, measure error, adjust, repeat. That's the whole trick.
• wk 3–5Features and labels: build a dataset about something you care about.
• wk 6–8Train a first classifier; chart how more data changes accuracy.
• wk 9–10Demo: explain your model's best and worst predictions to the room.

A2Break it on purpose10 weeks

• wk 1–3Image classifiers: train one, then hunt for inputs that fool it.
• wk 4–6Bias in, bias out: skew your training data and measure what happens.
• wk 7–8Where AI shouldn't decide alone: cases, debated properly.
• wk 9–10Demo: present your model's failure catalog — the honest spec sheet.

A3AI on robots10 weeks

• wk 1–3Camera on the robot: detect a colored target, then an object class.
• wk 4–6Perception to action: drive toward what the model sees.
• wk 7–8Confidence thresholds: teach the robot to say "not sure" and stop.
• wk 9–10Demo: a sorting robot that explains each decision on screen.

A team program shaped around a competition season rather than fixed units. Our goal is to field Junaid Academy teams in established robotics leagues and coding contests in our first full year. Entry is by instructor conversation, not test scores — commitment matters more than current skill.

P1Pre-season: read the game like an engineer6 weeks

• wk 1–2Dissect a past season's game manual; score strategies on paper first.
• wk 3–4Team roles: drive, build, code, scout, notebook — everyone learns two.
• wk 5–6Mock kickoff: 72-hour design sprint on a practice challenge.

P2Season: design–build–test on a clockleague calendar

• cycleWeekly iteration loops: one measurable improvement per session, logged.
• cycleEngineering notebook kept to judged standard from day one.
• cycleScrimmages against the clock, with post-match debriefs.
• cycleJudged-presentation practice: every member can explain every subsystem.