Skip to content
Mentor Subhanu
Book free trial class

Curriculum

What your child will learn, class by class

Every course follows a written plan. Below are the topics for each one, with a PDF to download. After the free trial class, the plan is adjusted to your child's level and exam board.

Free: the full Python 0 to 100 curriculumAll 40 classes with every subtopic.

Ages 7–12

Coding for Kids: Project-Based Scratch

Three levels, 30 projects. Every project is a game, story or app your child builds and can play.

  • 3 levels
  • 30 projects
  • From first animation to a capstone game
About this course
Level 1 - Scratch FoundationsLearn programming through fun animations, stories and beginner games.
  1. Project 1Animated Name CardInteractive introduction
  2. Project 2Dance PartyAnimated dance show
  3. Project 3Virtual PetFeed and play with a pet
  4. Project 4Magic PaintDrawing application
  5. Project 5Catch the AppleScore-based game
  6. Project 6Talking StoryInteractive story
  7. Project 7Maze EscapeMaze game
  8. Project 8Balloon PopBalloon popping game
  9. Project 9Music BandVirtual instruments
  10. Project 10Mini QuizQuiz game
Level 2 - Scratch Game DevelopmentBuild exciting arcade-style games while learning real programming logic.
  1. Project 1Space ShooterArcade shooter
  2. Project 2Flappy BirdFlying game
  3. Project 3Platform JumperPlatform game
  4. Project 4Fruit NinjaFruit slicing
  5. Project 5Snake GameClassic snake
  6. Project 6Car RacingRacing game
  7. Project 7Memory MatchCard matching
  8. Project 8Whack-a-MoleReaction game
  9. Project 9Treasure HuntAdventure game
  10. Project 10Math ChallengeLearning game
Level 3 - Scratch CreatorThink like a programmer and build large polished games ready for Python.
  1. Project 1RPG AdventureRole-playing game
  2. Project 2Tower DefenseStrategy game
  3. Project 3Restaurant SimulatorSimulation game
  4. Project 4City BuilderCreative simulator
  5. Project 5Escape RoomPuzzle game
  6. Project 6Typing Speed TestTyping trainer
  7. Project 7Quiz Show DeluxeAdvanced quiz
  8. Project 8Physics SandboxPhysics simulation
  9. Project 9Dungeon CrawlerAdventure game
  10. Project 10Capstone ProjectStudent-designed masterpiece

Beginner to intermediate

Python 0 to 100

40 classes from a first program to a finished project. Free to download in full.

  • 40 classes
  • 7 milestones
  • School-exam friendly
  • CBSE / ICSE / State board aligned
  • Perfect for Python Olympiads & CS foundation
  • Strong base for Class 11–12 CS / IP
About this course
Milestone 1: Basics of programming, variables, operatorsClasses 1–5 · Skills: Writing simple Python programs
  1. Class 1Introduction to ProgrammingWhat is programming, real-life examples, why Python, applications of Python
  2. Class 2Python Setup & BasicsInstalling Python, IDLE vs editor, first program, print(), comments
  3. Class 3Variables & Data TypesVariables, naming rules, int, float, string, bool, type()
  4. Class 4Input & Outputinput(), type casting, formatted output, escape sequences
  5. Class 5OperatorsArithmetic, relational, logical, assignment operators
Milestone 2: Decision making and loopsClasses 6–11 · Skills: Logical thinking, problem solving
  1. Class 6Conditional Statementsif, if-else, elif, nested conditions
  2. Class 7Practice Class 1Conditional logic problems, number checks, grading system
  3. Class 8Loops – whilewhile loop syntax, infinite loop, break
  4. Class 9Loops – forfor loop, range(), loop patterns
  5. Class 10Loop Control Statementsbreak, continue, pass
  6. Class 11Practice Class 2Loop-based problems, number series, pattern printing
Milestone 3: Strings, lists, sets, dictionariesClasses 12–21 · Skills: Data manipulation skills
  1. Class 12Strings – BasicsString creation, indexing, slicing
  2. Class 13String OperationsString methods, length, case conversion
  3. Class 14String HandlingPalindrome, reverse, count characters
  4. Class 15Lists – BasicsList creation, indexing, slicing
  5. Class 16List Operationsappend, insert, remove, pop, sort
  6. Class 17TuplesTuple creation, immutability, tuple operations
  7. Class 18SetsSet properties, add/remove, set operations
  8. Class 19Dictionaries – BasicsKey-value pairs, dictionary creation, access
  9. Class 20Dictionary OperationsAdding/updating, looping through dictionary
  10. Class 21Practice Class 3Problems using strings, lists, dictionaries
Milestone 4: Functions and modular programmingClasses 22–26 · Skills: Code reusability, structured coding
  1. Class 22Functions – IntroductionWhat are functions, syntax, calling functions
  2. Class 23Function ParametersArguments, return values, multiple returns
  3. Class 24Built-in Functionslen(), max(), min(), sum(), sorted()
  4. Class 25Scope of VariablesLocal vs global variables
  5. Class 26ModulesImporting modules, math, random
Milestone 5: File handling conceptsClasses 27–30 · Skills: Working with real data files
  1. Class 27File Handling – IntroductionWhat is a file, file modes, open()
  2. Class 28File Readingread(), readline(), readlines()
  3. Class 29File Writingwrite(), writelines(), append mode
  4. Class 30File Handling – PracticeFile-based programs (student data, logs)
Milestone 6: OOP fundamentalsClasses 31–35 · Skills: Object-oriented thinking
  1. Class 31Error HandlingTypes of errors, try-except, finally
  2. Class 32Object Oriented Programming – BasicsClass, object, attributes
  3. Class 33Constructors__init__(), instance variables
  4. Class 34Methods in ClassInstance methods, accessing data
  5. Class 35OOP ConceptsEncapsulation, basic abstraction
Milestone 7: Project developmentClasses 36–40 · Skills: End-to-end program building
  1. Class 36Practice Class 4OOP-based programs
  2. Class 37Mini Project – PlanningProblem statement, flow, logic design
  3. Class 38Mini Project – CodingImplementation of project
  4. Class 39Mini Project – EnhancementAdding features, validations
  5. Class 40Revision & AssessmentFull course revision, test, viva

Ages 14–18

Advanced AI: Neural Networks, Transformers and LLMs

40 classes: build a neural network from scratch, then a mini GPT, then fine-tune real language models.

  • 40 classes in 8 modules
  • Every fifth class is a hands-on workshop
  • 3 projects and a capstone showcase
About this course
Module 1: Math & Computing FoundationsClasses 1–5 · Checkpoint: Math + NumPy consolidation lab
  1. Class 1Course Setup, Colab, NumPy & Tensors
  2. Class 2Vectors, Matrices & Neural-Network Data
  3. Class 3Dot Products, Matrix Multiplication & Broadcasting
  4. Class 4Derivatives, Gradients & Chain Rule
  5. Class 5Math + NumPy Consolidation LabWorkshop
Module 2: Neural Network FundamentalsClasses 6–10 · Checkpoint: Forward Propagation Checkpoint
  1. Class 6Artificial Neurons: Weights, Biases & Weighted Sums
  2. Class 7Activation Functions
  3. Class 8Layers & Vectorized Forward Propagation
  4. Class 9Predictions, Softmax & Loss Functions
  5. Class 10Forward Propagation WorkshopWorkshop
Module 3: Backpropagation & LearningClasses 11–15 · Checkpoint: Backpropagation Checkpoint
  1. Class 11How a Neuron Learns: Local Derivatives
  2. Class 12Computational Graphs & the Chain Rule
  3. Class 13Backpropagation Through a Single Layer
  4. Class 14Multi-Layer Backpropagation & Gradient Descent
  5. Class 15Backpropagation Mastery LabWorkshop
Module 4: Training Neural NetworksClasses 16–20 · Checkpoint: Project 1 - NumPy Neural Network
  1. Class 16Build a Neural Network From Scratch
  2. Class 17Batches, SGD, Momentum & Adam
  3. Class 18Training Problems & Regularization
  4. Class 19Project 1: NumPy Neural Network
  5. Class 20Project 1 Review + Foundations AssessmentWorkshop
Module 5: PyTorch & Modern Deep LearningClasses 21–25 · Checkpoint: PyTorch Skills Check
  1. Class 21PyTorch Tensors & Autograd
  2. Class 22nn.Module, Losses, Optimizers & Training Loops
  3. Class 23Datasets, DataLoaders, GPU & Model Workflow
  4. Class 24From Deep Networks to Sequence Models
  5. Class 25PyTorch Consolidation LabWorkshop
Module 6: NLP & AttentionClasses 26–30 · Checkpoint: Attention Checkpoint
  1. Class 26Text, Tokens, Vocabularies & Embeddings
  2. Class 27Attention Intuition + Query, Key, Value
  3. Class 28Scaled Dot-Product Self-Attention From Scratch
  4. Class 29Multi-Head Attention & Causal Masking
  5. Class 30Attention Mastery LabWorkshop
Module 7: Transformers & Mini GPTClasses 31–35 · Checkpoint: Mini-GPT Pre-training Checkpoint
  1. Class 31Transformer Block Anatomy
  2. Class 32Positional Information, LayerNorm, Residuals & FFN
  3. Class 33Decoder-Only Transformer From Scratch
  4. Class 34Language Modelling, Training Data & Next-Token Prediction
  5. Class 35Mini-GPT Build & Debug WorkshopWorkshop
Module 8: Practical LLM EngineeringClasses 36–40 · Checkpoint: Projects 2 & 3 + Capstone Showcase
  1. Class 36Train Mini GPT + Text Generation
  2. Class 37Hugging Face Transformers & Pretrained LLMs
  3. Class 38Fine-Tuning: Datasets, Labels & Training Workflows
  4. Class 39LoRA, QLoRA, PEFT, Evaluation & Saving
  5. Class 40Capstone Showcase, Full Revision & Next StepsWorkshop

Free trial class

Book a free trial class

Share your name, WhatsApp number and course. WhatsApp opens with your details filled in, so you can pick a time for the free 30-minute trial class. Afterwards you can ask for a written learning plan.

WhatsApp
+91 90730 55125
Email
mentorsubhanu@gmail.com
Sessions
Live 1-on-1 video · 60 minutes

Session times: weekdays 8–11pm and Saturdays 7am–5pm India time (IST). Sundays off.

WhatsApp opens with your details filled in. Nothing is sent until you tap send.