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Prompt Engineering 

Guardrails and evaluation criteria

Prompt Engineering Assignment

Context Overflow Agent Assignment

MCP Middleware Assignment

In this lab, Zach walks you through a Python script he created for automated code review. He demonstrates how the script generates comments on pull requests, the setup process involving GitHub tokens, and the prompt engineering for feedback. Recorded on June 20th, 2024. 

LLMs - Using LLMs to provide business value Day 1 Lab

academy/2/course/320/machine-learning-day-1-lab-v4-transcript.json

In this lecture, Zach simplifies the concept of LLM to its basics, emphasizing the importance of starting with simple examples for better understanding. He discussed the impact of LLM on data engineering, highlighting the significance of feedback, soft skills, and best practices in adapting to this evolving technology. Recorded on June 20th, 2024.

LLMs - Using LLMs to provide business value Day 1 Lecture

academy/2/course/319/llms_lecture_day1/llms_lecture_day1.json

This is new content and will be recorded on June11th  2024.

LLMs - Vector database for RAG applications Day 2 Lab

academy/2/course/324/llm_day2_lab/llm_day2_lab.json

LLMs - Vector database for RAG applications Day 2 Lecture

academy/2/course/323/machine-learning-day-2-lecture-v4-transcript.json

Learn the different roles you can play using the ChatGPT Python API, how to interact with GPT-4 using different API configurations, and how to make the most of LLMs to streamline data engineering tasks. In this live lab session, we put GPT-4 to the test and see how well it does at generating an Airflow DAG, writing SQL queries, and crafting dataset documentation.

LLM-Driven Data Engineering Day 1 Lab

academy/2/all-access/large-language-models/day1/lab/lab.json

In this bonus lecture, we dive into one of the hottest topics in tech right now: "Will data engineering be replaced by AI and large language models?" We explore where Large Language Models (LLMs) like GPT-4 are poised to have the most significant impact, identify areas ripe for disruption, and discern the domains where LLMs have a long way to go before they can replace human ingenuity. But most importantly, discover how you can use these insights to harness the power of LLMs and elevate your career as a data engineer.

LLM-Driven Data Engineering Day 1 Lecture

academy/2/course/65/large-language-models-day-1-lecture-transcript.json

In this bonus LLM lab, you will learn how to extend your LLMs capabilities beyond text generation. This includes tasks like sending emails, crafting LinkedIn posts, and exploring the role of agents in aiding you in your technical work such as when bugs arise in your pipeline or database.

LLM-Driven Data Engineering Day 2 Lab

academy/2/course/66/large-language-models-day-2-lab-transcript.json

In this LLM presentation, we explore building applications with LLMs, emphasizing LangChain as a versatile integration point for different LLMs and addressing privacy and security concerns.

LLM-Driven Data Engineering Day 2 Lecture

academy/2/course/67/large-language-models-day-2-lecture-transcript.json

LLMs

Quiz

LLMs - Using LLMs to provide business value Day 1 Lab

LLMs - Using LLMs to provide business value Day 1 Lecture

LLMs - Vector database for RAG applications Day 2 Lab

LLMs - Vector database for RAG applications Day 2 Lecture

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LLM-Driven Data Engineering Day 1 Lab

LLM-Driven Data Engineering Day 1 Lecture

LLM-Driven Data Engineering Day 2 Lab

LLM-Driven Data Engineering Day 2 Lecture

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Prompt Engineering

Guardrails and evaluation criteria

Prompt Engineering Assignment

Context Overflow Agent Assignment

MCP Middleware Assignment

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