31 concepts · ~258 min
Learning path,
one concept at a time.
Beginner
What is a large language model?
10 min ReadWhat is a tokenizer?
10 min ReadTokens in large language models
7 min ReadEmbeddings and vector representations
8 min ReadVector representations for AI systems
9 min ReadParameters and weights in AI models
9 min ReadPrompt engineering
10 min ReadMultimodal AI
10 min ReadPre-training AI models
7 min ReadOpen-weight AI models
6 min Read
Intermediate
LLM architecture and attention
8 min ReadInference — how models generate output
10 min ReadFine-tuning a pre-trained model
10 min ReadEncoder-decoder models
7 min ReadTransformers and BERT
10 min ReadContext engineering
10 min ReadPost-training AI models
6 min ReadHuman-in-the-loop AI systems
8 min ReadAttention mechanism
9 min ReadRecurrent neural networks (RNNs)
7 min ReadVector distance and similarity metrics
8 min ReadCosine similarity
9 min Read