Loading chapter

Loading courses

ComputingLifeSci

A complete computational biology curriculum — 23 courses covering programming, databases, machine learning, genomics and research infrastructure. Written for biologists, not computer scientists.

support@computinglifesci.com 8052536359

Programming for Biology

Python for Biologists
R for Biologists
Perl for Biologists
MATLAB for Biologists
SAS for Biologists
BioJava for Biologists

Data & Databases

SQL for Biological Databases
Bioinformatics Databases
Big Data Mining for Biologists

AI & Machine Learning

Machine Learning for Biologists
Artificial Intelligence for Biologists
MLOps for Biologists
AI Tools for the Bioinformatics Lab

Home All courses Roadmaps Videos BINC & GATE notes Career Know where you can work Pricing About Contact us Terms Privacy Refunds & delivery

Loading chapter

Artificial Intelligence for Biologists45 chapters

Chapter 7.1 — What are LLMs and How Do They Work?
Chapter 7.2 — Prompt Engineering and Fine-Tuning (Introduction)
Chapter 7.3 — Retrieval-Augmented Generation, Vector Databases, and Knowledge Graphs (Introduction)
Chapter 7.4 — Reasoning, Chain of Thought, Hallucinations, and Evaluating LLMs
What's Next

/Artificial Intelligence for Biologists/PART 7 — LARGE LANGUAGE MODELS (LLMs)

Chapter 24 of 453 min read

Chapter 7.2 — Prompt Engineering and Fine-Tuning (Introduction)

Learning Objectives Understand the difference between prompting and fine tuning Understand instruction tuning at a conceptual level Note : Prompt Engineering receives a full, dedicated deep dive in Part 13 of this…

Sign in to read this

“Chapter 7.2 — Prompt Engineering and Fine-Tuning (Introduction)” is for subscribers. Start with a free account — it takes a name and an email — then subscribe for $1 a month to open it.

Python and R courses free in full

First two chapters of every other course

Everything else — including this one — for $1 a month

Cancel any time

Create a free account I already have one

PreviousChapter 7.1 — What are LLMs and How Do They Work?NextChapter 7.3 — Retrieval-Augmented Generation, Vector Databases, and Knowledge Graphs (Introduction)