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VERSION:2.0
PRODID:-//Palaner//palaner Single Event//EN
METHOD:PUBLISH
CALSCALE:GREGORIAN
BEGIN:VEVENT
UID:meetup-297ff1ca64@palaner.app
DTSTAMP:20260802T141138Z
DTSTART:20260822T080000Z
DTEND:20260822T093000Z
SUMMARY:Build & Learn: From Data Science to AI Engineering Week 2
LOCATION:Octupus Bar
DESCRIPTION:Saved in Palaner as: saved\n\nPalaner match: 21% · why: lots of
  people going\n\n📅 Week 2: The LLM Application Layer\n\nThis event is part
  of our seven-week AI Engineering program\, where we build an end-to-end A
 I application step by step and present our finished projects during Demo D
 ay in Week 7.\n\nThis week\, we’ll work through the key layers of a modern
  AI application:\n\nGo through the entire OpenAI API documentation and Pyt
 hon SDK (authentication\, requests\, structured outputs\, tool calling).\n
 Learn prompt engineering fundamentals and the core building blocks of LLM 
 systems.\nUnderstand that effective AI systems use as little AI as possibl
 e. Deterministic logic first\, LLMs where they earn their place.\nBuild ag
 ents from scratch before reaching for frameworks\, and learn the 5 levels 
 of AI agents.\nLearn context engineering to understand why agents fail and
  how to feed them the right information.\n\nBy the end of the 7 week cycle
 \, you should have a working AI application in your own GitHub repository 
 and practical experience with AI pipelines\, APIs\, databases\, retrieval\
 , evaluation and deployment.\nYou are welcome to follow the shared project
  or apply the weekly concepts to your own project.\n\n✨ Who is this for?\n
 This cycle is designed for data scientists\, analysts\, software developer
 s and Python users interested in moving toward AI engineering.\nNo previou
 s LLM or AI engineering experience is required. However\, you should alrea
 dy understand basic Python or be willing to complete some preparation inde
 pendently.\n\n✨ Who’s hosting?\nI’m Lindsey\, a senior data scientist work
 ing on AI systems\, causal inference and data products.\nI’ve worked on ma
 chine learning\, uplift modelling\, fraud detection and production LLM sys
 tems. I care about learning through building—and moving beyond AI hype tow
 ard applications that actually work.\n\n💻 Bring: Your laptop\, your projec
 t and your curiosity.\n☕ Please grab a coffee or drink from the Octopus Ba
 r to support the business and thank them for providing the space.
URL:https://www.meetup.com/build-learn-data-science-saturdays/events/315670
 843/
CATEGORIES:palaner,saved
STATUS:TENTATIVE
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