Must-Have Prompt Engineering Skills for 2024

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Abstraction: In-demand prompt engineering skills, platforms, and tools

Key points:

ODSC analysis of ~430 prompt engineering job descriptions to map in-demand skills (acknowledged as a rough, biased guide).
Role sparked by a Business Insider piece claiming "$375k salary, no tech background required"; article argues the role is far more technical than typing prompts.
Core skills: AI/ML/DL foundations, data science, fine-tuning, inference efficiency, embeddings (stored in vector DBs like Weaviate for RAG), scaling laws (Chinchilla/DeepMind), NLP, tokenization, transformers.
Platforms cited: ChatGPT (GPT-3.5/GPT-4/GPT-4 Turbo, 128k context), LLaMA-2 (open source), Stable Diffusion, DALL-E, BERT (360M params vs GPT-4's ~1.76T), plus PyTorch/TensorFlow/scikit-learn.
LangChain highlighted for chaining prompts, PromptTemplates, and Memory; noted steep learning curve, with LlamaIndex emerging as alternative.
Python dominates; Azure leads cloud demand (direct OpenAI access) over AWS/GCP.

Connections: Openai · Langchain · Hugging Face · Chatgpt · Prompt Engineering · Fine Tuning · Embeddings · Large Language Models