Artificial Intelligence AI Tutor
Jarvis AI teaches AI fundamentals — machine learning, neural networks, transformers and LLMs — with maths derivations, code and diagrams for A-Level, IB and undergraduate.
What is Artificial Intelligence?
From linear regression through backpropagation to attention mechanisms in transformers, Jarvis explains AI the way a graduate-level lecturer would, then shows working Python code.
Why Artificial Intelligence matters
AI is the defining technology of the decade — foundational for every engineering, product and research career.
Key facts
- Every derivation shows the calculus (chain rule, gradients).
- Diagrams (network, attention, transformer stack) render inline.
- Code is in PyTorch or scikit-learn with runnable examples.
- Evaluation metrics come with a confusion-matrix walkthrough.
- LLM answers cover tokenisation, embeddings, attention and decoding.
What Jarvis covers in Artificial Intelligence
ML Fundamentals
Supervised, unsupervised, reinforcement learning and evaluation.
Neural Networks
Perceptrons, backprop, CNNs and RNNs.
Transformers & LLMs
Attention, positional encoding and instruction tuning.
Computer Vision
Convolutions, YOLO, segmentation and vision transformers.
NLP
Tokenisation, embeddings, BERT/GPT families and RAG.
Ethics & Alignment
Bias, safety, RLHF and evaluation of AI systems.
How Jarvis fixes the hardest bits
I don't understand backprop.
Jarvis walks through a 2-layer network by hand, then in code.
Transformers are a black box.
Every transformer answer includes an attention diagram.
I can't pick a model.
Jarvis matches the model to the task, data size and constraints.
Where Artificial Intelligence leads
Related curricula
FAQ
Is the maths shown?
Yes — derivatives, gradients, matrix algebra and probability all with steps.
Which frameworks does it teach?
PyTorch, TensorFlow, scikit-learn, HuggingFace.
Are transformers explained end-to-end?
Yes — tokenisation, embeddings, attention, decoding, RLHF.
Does it cover computer vision?
Yes — CNNs, YOLO, segmentation and vision transformers.
Is ethics covered?
Yes — bias, alignment, RLHF and evaluation.
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