🤖
AI & LLM FUNDAMENTALS
NEXLEVR LEARNERS // FREE RESOURCES
Intro to machine learning, LLMs, prompt engineering and practical AI use-cases.
📋 PROOF-OF-WORK TASKS
BBEGINNER
- →Build a demo prompt-flow that answers common Nexlevr FAQs and share examples on social media
- →Fine-tune a small model on Nexlevr FAQs (or simulate with embeddings) and post a short demo
IINTERMEDIATE
- →Implement a RAG pipeline for Nexlevr knowledge and publish a demo with code samples
- →Create an evaluation report comparing prompt strategies and share insights publicly
4
VIDEOS
FREE
ALWAYS
4
TASKS
YOUTUBE RESOURCES
ENGLISH
4 RESOURCESROADMAPS & DOCUMENTATION
🗺️ROADMAP
roadmap.sh
Foundational mathematics, data preprocess pipelines, neural net structures, and LLM theory.
VISIT PLATFORM
🎓REFERENCE
GeeksforGeeks
Tokenizers, transformer encoders, prompt optimization patterns, and fine-tune models.
VISIT PLATFORM
📄OFFICIAL DOCS
OpenAI Docs
Official API reference guides, assistants model configs, and foundation tools specification.
VISIT PLATFORM
🎓COURSE
Intro to ML
Curated additional study materials and practical guides for AI & LLM Fundamentals.
VISIT RESOURCE