AI General Skills Enhancement Course: Understanding the Inner Logic of Large Models, Mastering Prompts and Agent Building Methods

Course introduction: This course starts with the development history of the AI industry and the basic concepts of AIGC, explains the inner working principles of large models, and distinguishes the usage differences between reasoning models and instruction models. The course focuses on prompt engineering: it progressively teaches conversational, structured and super prompts, and breaks down practical techniques such as locking and reshaping; it also explains the principles of agents and how to build them. The course reviews common misunderstandings in the use of AI tools and shares the instructor's real AI application cases, helping learners build complete AI thinking, scientifically plan their personal AI growth path, and master reusable general AIGC skills. Course outline: 01.01 Preface 02.02 Instructor introduction 03.03 The instructor's AI journey: sharing and cooperation cases 04.04 Course outline and case-inspired insights 05.05 Case warm-up 06.06 Interaction and statement 07.07 Several concepts in AIGC 08.08 The development history of the two AI giants 09.09 How AI technology guides the development of AI tools 10.10 Understand the status quo and plan yourself correctly 11.11 Sustainable AI development planning 12.12 Core operating principles of large models 13.13 Usage differences between reasoning models and instruction models 14.14 How to start using AI tools 15.15 Prompt engineering prologue 16.16 What is prompt engineering 17.17 Prompts – Conversation 18.18 Prompts – Using structured prompts 19.19 Prompts – Using super prompts 20.20 The words you and me in prompts 21.21 Precision prompt techniques – Prologue 22.22 Precision prompt techniques – Locking technique 23.23 Precision prompt techniques – Decomposition technique 24.24 Precision prompt techniques – Decomposition technique – Image generation 25.25 The hidden mechanism of decomposition 26.26 Precision prompt techniques – Reshaping and anti-teaching 27.27 Analysis of practical tips – Online search 28.28 Misunderstandings in using AI tools 29.29 Prompts – Using ultra-structured prompts [markdown] 30.30 Additional supplement – Using reasoning prompts 31.31 Introduction to agents 32.32 Teaching how to build agents 33.33 Conclusion and encouragement