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MINU'S ROBOTICS

A Minu's Games EdTech Lab

30-Day Course · Self-paced

Code & Cognition

Python to AI in 30 Days

One syllabus, two lenses — for young explorers and working professionals.

▶ Start Day 1See the roadmap
🧒

Young Explorers (10–16)

Playful framing, visual outputs, and gentle scaffolding. Build games and a real AI by the end — no experience needed.

💼

Professionals

Real-world framing, industry tooling (NumPy, Pandas, scikit-learn, LLM APIs), and applied tasks you can put in a portfolio.

🎯 What you'll be able to do

  • Write clean Python: variables, control flow, functions, data structures, files, errors
  • Use NumPy, Pandas & Matplotlib to load, clean and visualize real data
  • Explain how machine learning works: data → features → train → evaluate
  • Build & evaluate first ML models (classification + regression) with scikit-learn
  • Use a pre-trained model / LLM API responsibly with basic prompt engineering
  • Reason about AI ethics & bias, and ship a small AI-powered capstone

🗺️ The 30-day roadmap

Phase 1Python FoundationsDays 1–7
Day 1🐍
Hello, Python
Run your first Python program and understand what programming is.
Day 2📦
Variables & Data Types
Store and reuse information using variables and basic types.
Day 3✍️
Strings & Text
Manipulate text — the raw material of language AI.
Day 4➗
Numbers & Math
Do arithmetic and understand the math AI is built on.
Day 5⌨️
Input & Interaction
Make programs that talk with the user.
Day 6✅
Booleans & Comparisons
Ask yes/no questions in code — the basis of decisions.
Day 7🔀
Conditionals (if / elif / else) · Project
Make programs choose different paths — then build a Smart Quiz.
★ PROJECT DAY
Phase 2Logic & Data StructuresDays 8–14
Day 8🔁
Loops with for & range
Repeat actions automatically.
Day 9♾️
while Loops & Control
Repeat until a condition changes; control loops with break/continue.
Day 10📋
Lists
Store many values in one ordered collection.
Day 11🗂️
Dictionaries
Store labelled data as key → value pairs.
Day 12🎯
Tuples & Sets
Use fixed sequences (tuples) and unique collections (sets).
Day 13🧩
Functions
Package reusable logic into named functions.
Day 14🤖
Function Power & Project
Use parameters, defaults, scope — then build a guessing bot.
★ PROJECT DAY
Phase 3Real Python & DataDays 15–21
Day 15🐞
Errors & Debugging
Read errors and fix bugs calmly with try/except.
Day 16💾
Files: Read & Write
Persist data by reading and writing files.
Day 17📚
Modules & the Ecosystem
Reuse code with imports and install packages with pip.
Day 18🔢
NumPy — Arrays & Vectors
Work with fast numerical arrays — the math layer of AI.
Day 19🐼
Pandas — DataFrames
Load and explore tabular data like a spreadsheet in code.
Day 20📊
Visualizing Data
Turn numbers into charts to find patterns.
Day 21🔎
Exploratory Data Analysis · Project
Combine Pandas + charts to interrogate a real dataset.
★ PROJECT DAY
Phase 4Artificial IntelligenceDays 22–28
Day 22🧠
What Is AI, ML & Deep Learning?
Build a clear mental model of the AI landscape.
Day 23🎓
How Machines Learn
Understand data, features, labels, and train/test split.
Day 24🌸
Your First ML Model — Classification
Train a classifier with scikit-learn.
Day 25📈
Regression — Predicting Numbers
Predict continuous values with linear regression.
Day 26🕸️
Neural Networks — The Idea
Grasp how neural networks learn, conceptually.
Day 27🗣️
AI for Language & Images
Use powerful pre-trained models without training from scratch.
Day 28💬
Prompting & Using AI APIs
Get reliable results from an LLM and call it from Python.
Phase 5Ethics & CapstoneDays 29–30
Day 29⚖️
AI Ethics, Bias & Careers
Build AI responsibly and see where this can take you.
Day 30🏆
Capstone — Build & Present
Bring it all together into one AI-powered project.
★ PROJECT DAY

Independent preview module · 30 days · integrates into the main LMS later