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 Read 30 min? W07 Monday Craft

Zheng et al. (2023), "Judging LLM-as-a-judge with MT-Bench and Chatbot Arena"

Monday build block · Read it inside Monday's build block

Build-block reading · Zheng et al. (2023), "Judging LLM-as-a-judge with MT-Bench and Chatbot Arena", NeurIPS Datasets & Benchmarks, sections 1-3 (judge biases you must avoid in week 14)

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In: LABLOOP-W07 Notebook

2/12 Watch 50 min W07 Tuesday Biology

MIT OCW 7.016 lectures on protein structure and enzymes

MIT OCW 7.016 lectures on protein structure and enzymes (ocw.mit.edu/courses/7-016-introductory-biology-fall-2018), ~50 min

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In: LABLOOP-W07 Notebook

3/12 Watch 15 min W07 Tuesday Biology

Khan Academy "Steady states and the Michaelis Menten equation"

Tuesday · after MIT OCW 7.016 lectures on protein structure and enzymes

Khan Academy "Steady states and the Michaelis Menten equation" (MCAT section) (15 min)

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In: LABLOOP-W07 Notebook

5/12 Run 30 min? W07 Saturday Sandbox optional

Anthropic Claude Cookbooks (github.com/anthropics/claude-cookbooks) — "extracting structured JSON"

Saturday sandbox

Anthropic Claude Cookbooks (github.com/anthropics/claude-cookbooks) — "extracting structured JSON" and "tool use" recipes

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In: LABLOOP-W07 Notebook

6/12 Read 30 min? W07 Saturday Sandbox optional

DSPy (Stanford NLP) documentation "Optimizers"

Saturday sandbox · after Anthropic Claude Cookbooks (github.com/anthropics/claude-cookbooks) — "extracting structured JSON"

DSPy (Stanford NLP) documentation "Optimizers" — how to tune prompts against a metric instead of by feel

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In: LABLOOP-W07 Notebook

8/12 Watch 15 min? W07 Saturday Sandbox optional

Ninja Nerd "Enzyme kinetics" lecture

Saturday sandbox · after Karpathy, "Deep Dive into LLMs like ChatGPT"

Ninja Nerd "Enzyme kinetics" lecture (YouTube) for Michaelis-Menten in depth

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In: LABLOOP-W07 Notebook

9/12 Run 30 min W07 Build

567-labs/instructor

Define your schema as a Pydantic model and let instructor enforce valid JSON from Claude and Ollama; kills 80% of parsing bugs

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In: LABLOOP-W07 Notebook

10/12 Run 30 min W07 Build

google/langextract

Run an example in examples/notebooks with a local Ollama model; compare its grounded spans with your provenance sentences

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In: LABLOOP-W07 Notebook

11/12 Run 30 min W07 Build

stanfordnlp/dspy

Tutorial on "information extraction" in the docs: define a signature, a metric (your F1), and let an optimizer improve the prompt. Only after your manual baseline exists

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In: LABLOOP-W07 Notebook

12/12 Run 30 min W07 Build

lmfit/lmfit-py

Fit Michaelis-Menten to a small public dataset with confidence intervals on Km and Vmax

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In: LABLOOP-W07 Notebook