455 CARDS · 41 WEEKS · EVERY SOURCE THE PLAN NAMES

Everything you could
study, filtered.

Every video, chapter, paper and repository in the programme, as one card each, with the time it costs and why it is there. Filter by how long you have.

Type Watch Read Run Track Biology AI & stats Build Craft Depth Core Optional Time ≤15 ≤30 ≤60 Week This week Clear all

1/12 Watch 15 min W34 Tuesday Biology

Lewis et al. (2020), "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks"

Lewis et al. (2020), "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", NeurIPS, abstract + figure 1 (15 min)

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2/12 Watch 30 min W34 Tuesday Biology

Es et al. (2023), "RAGAS: Automated Evaluation of Retrieval Augmented Generation"

Tuesday · after Lewis et al. (2020), "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks"

Es et al. (2023), "RAGAS: Automated Evaluation of Retrieval Augmented Generation", arXiv:2309.15217 (30 min)

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3/12 Watch 30 min W34 Tuesday Biology

Stanford CS224N lecture on retrieval/RAG

Tuesday · after Es et al. (2023), "RAGAS: Automated Evaluation of Retrieval Augmented Generation"

Stanford CS224N lecture on retrieval/RAG (web.stanford.edu/class/cs224n; verify current lecture list) (30 min)

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4/12 Read 30 min? W34 Saturday Sandbox optional

Anthropic, "Introducing Contextual Retrieval"

Saturday sandbox

Anthropic, "Introducing Contextual Retrieval" (engineering blog, 2024)

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5/12 Read 30 min? W34 Saturday Sandbox optional

Thakur et al. (2021), "BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information R…

Saturday sandbox · after Anthropic, "Introducing Contextual Retrieval"

Thakur et al. (2021), "BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models", NeurIPS Datasets and Benchmarks

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6/12 Read 30 min? W34 Saturday Sandbox optional

Faysse et al. (2024), "ColPali: Efficient Document Retrieval with Vision Language Models"

Saturday sandbox · after Thakur et al. (2021), "BEIR: A Heterogeneous Benchmark for Zero-shot Evaluation of Information R…

Faysse et al. (2024), "ColPali: Efficient Document Retrieval with Vision Language Models", arXiv:2407.01449 — retrieval directly on page images

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7/12 Read 30 min? W34 Saturday Sandbox optional

Zheng et al. 2023 LLM-as-a-judge

Saturday sandbox · after Faysse et al. (2024), "ColPali: Efficient Document Retrieval with Vision Language Models"

Zheng et al. 2023 LLM-as-a-judge (carry over)

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8/12 Run 30 min W34 Build

vibrantlabsai/ragas

Compute context recall and faithfulness on 10 of your Q&A; compare with your human labels before trusting it

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9/12 Run 30 min W34 Build

run-llama/llama_index

Only as a reference implementation of chunking and citation; keep your own pipeline small

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10/12 Run 30 min W34 Build

illuin-tech/colpali

Try page-image retrieval on 20 scanned SOP pages; compare recall@5 with text chunks

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11/12 Run 30 min W34 Build

UKGovernmentBEIS/inspect_ai

Wrap the 60 Q&A as an eval with a model-graded scorer and your human labels

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12/12 Run 30 min W34 Build

ggml-org/llama.cpp

Serve the embedding model locally on the mini PC for the on-prem story

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