AI Engineer Roadmap – How to Learn AI in 2025

This comprehensive AI Engineering roadmap will walk you through the essential skills and techniques every aspiring AI Engineer should master by 2025. From fundamental mathematics and key machine learning algorithms to deep learning, AI Engineering best practices, and large language models—you’ll get hands-on AI Engineering experience and invaluable career insights that will set you on the fast track to success in this rapidly evolving field.

Course developed by Tatev Aslanyan from @LunarTech_ai

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⭐️ Contents ⭐️
(0:00:00) AI Engineering Roadmap Introduction
(0:03:59) What is AI Engineering
(0:05:47) AI Engineering Applications
(0:08:31) Must-Have Skills for an AI Engineer
(0:09:05) Mathematical Foundations
(0:17:38) Statistics Essentials
(0:23:37) Data Science Skills
(0:28:05) Traditional Machine Learning
(0:32:36) Deep Learning Foundations
(0:38:36) Practical Implementation in Python
(0:40:54) Generative AI Fundamentals
(0:46:39) Large Language Models (LLMs)
(0:51:07) Fine-tuning Large Language Models
(0:52:05) Reinforcement Learning with Human Feedback (RLHF)
(0:53:05) Retrieval-Augmented Generation (RAG)
(0:53:28) Evaluating & Optimizing LLMs
(0:54:14) AI Engineering Ethics & Safety
(0:56:44) Additional Resources & Career Paths
(0:57:34) Outro & Final Remarks

🎉 Thanks to our Champion and Sponsor supporters:
👾 Drake Milly
👾 Ulises Moralez
👾 Goddard Tan
👾 David MG
👾 Matthew Springman
👾 Claudio
👾 Oscar R.
👾 jedi-or-sith
👾 Nattira Maneerat
👾 Justin Hual

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