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Advanced Prompt Engineering: A Game-Changer in My AI Journey

Hey there, fellow tech enthusiasts and curious minds! As I continue to navigate my ever-evolving AI journey, I’m thrilled to share a major milestone. I recently completed the Advanced Prompt Engineering for Everyone course, led by the amazing Professor James White. This is my second course with him, and it was an absolute game-changer!

As someone who’s diving deep into conversational AI and NLP, this course was a treasure chest of insights and practical knowledge. Whether I’m crafting GPTs, building chatbots, or brainstorming new ideas, the tools and techniques I learned have already started to transform my workflow.

One of the coolest things I discovered was using taxonomy to pinpoint my key audience and their roles—right from my LinkedIn interactions. Imagine simply copying and pasting text and prompting, “create a taxonomy as an ASCII tree.” It was that simple and so powerful!

Another standout lesson was using generative AI for text classification—perfect for social media analysis, product reviews, and survey analysis. Talk about a hidden gem! This technique has opened up a whole new world of possibilities for diving deep into data.

Now, let’s talk about one of my favorite parts of the course: teaching an LLM to create templates using Markdown and footnotes. Here’s a format prompt you can use:

Copy and Paste your resume or content from your LinkedIn profile [Source Material] to conduct this prompt.

We are going to create a report on all the things about <your name>
create your report in this format:
# Here are some great things about <your name>
<Insert Table of <your name> Skills>
## Fact 1
"<Insert 10-15 Word great things about <your name> Summary>"
<Describe skills in detail>{^<insert Footnote to Original fact>]
............
# Footnotes
Match with line number of fact <Insert Footnote as Quotes from Source Material>

How cool is that? It’s a super handy way to organize and present information while giving readers a direct line to the original sources.

And let’s not forget about RAG (Retrieval-Augmented Generation). Understanding how it can help save money by reducing tokenization costs through embedding is a real game-changer. It’s all about optimizing and making AI work smarter for us.

This course has added so much value to my AI toolkit, and I can’t wait to integrate these techniques into my projects. If you’re exploring AI, I highly recommend diving into this course to unlock new potentials and elevate your skills.

Stay curious and keep pushing boundaries!

#AI #PromptEngineering #LearningJourney #Innovation