Learning AI Engineer Path AI Agents & Agentic AI - ReAct, RAG (C++)

[voska89]

AI Engineer Path AI Agents & Agentic AI - ReAct, RAG (C++)
Published 6/2026
Created by Real AI Engineering
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 98 Lectures ( 6h 54m ) | Size: 5.5 GB

Build real AI Agents and Agentic AI: ReAct, RAG, tools, memory, multi-agent systems, safety and production workflows
What you'll learn
Build the core agent loop in C++ and understand how goal-driven AI systems operate
Implement the ReAct pattern so an agent can reason step by step through Thought, Action, and Observation.
Build RAG pipelines in C++ using chunking, retrieval logic, and context assembly
Design and manage tool-using agents with structured execution and safer workflows
Create memory-aware agents with working memory, long-term memory concepts, and episodic recall patterns
Understand how multi-agent systems coordinate through orchestration patterns such as pipeline, dispatch, and debate
Evaluate agent quality using practical ideas such as latency, safety, reliability, and test harness thinking
Understand how agent systems evolve toward production-ready architecture with logging, retries, human-in-the-loop controls, and observability
Requirements
AI Systems Engineer 2026: Core AI Systems Engineering in C++ (highly recommended if you're new to C++ development)
A C++ compiler or Qt Creator or Visual Studio or CLion
No prior experience with AI agents & agentic AI is required
No advanced math is required
A willingness to learn how AI systems work beyond prompts and tools
Description
AI agents are no longer just a trend, they are becoming a core part of modern software systems. But most courses stay at the surface, focus only on frameworks, or hide the engineering details behind black boxes.
This course takes a different path.
InAI Engineer Path: AI Agents & Agentic AI - ReAct, RAG (C++), you will learn how to buildagentic AI systems from the ground up in modern C++. Instead of relying on abstractions, you will understand how real agents work, how they reason, use tools, retrieve knowledge, manage memory, coordinate with other agents, handle safety and move toward production-ready system design. The course structure you shared covers exactly that progression from PRAO and tool use to ReAct, RAG, memory, multi-agent coordination, evaluation, safety, human-in-the-loop and observability.
You will not just watch theory. You will build your understanding throughself-contained C++ sectionsdesigned to make every major concept concrete and practical. That means you will see how agent loops work, how tool calling is structured, how retrieval pipelines are assembled, how memory layers can be organized and how advanced systems are evaluated and monitored.
This course is ideal for the ones who want more than "prompting." It is for people who want to understand theengineering mindset behind reliable AI agents.
By the end of the course, you will have a strong foundation for building AI agents that are
more understandable
more controllable
more scalable
and far closer to real-world software systems
If you want to stand out as an AI engineer by combiningmodern AI concepts withreal C++ system design, this course will give you a rare and valuable edge.
What will you learn in this course?
After completing this course, you will be able to
Build the coreagent loop in C++ and understand how goal-driven AI systems operate.
Implement theReAct pattern so an agent can reason step by step through Thought, Action and Observation.
BuildRAG pipelines in C++ using chunking, retrieval logic and context assembly.
Design and managetool-using agents with structured execution and safer workflows.
Creatememory-aware agents with working memory, long-term memory concepts and episodic recall patterns.
Understand howmulti-agent systems coordinate through orchestration patterns such as pipeline, dispatch and debate.
Evaluate agent quality using practical ideas such as latency, safety, reliability and test harness thinking.
Understand how agent systems evolve towardproduction-ready architecture with logging, retries, human-in-the-loop controls and observability.
What are the Requirements or prerequisites for taking your course?
Basic understanding ofC++ syntax (variables, functions, loops, conditionals, classes).
A computer capable of compiling and runningmodern C++ code.
A C++ compiler or IDE such asg++,clang++,Visual Studio orCLion.
Familiarity with basic programming concepts such as functions, data structures and control flow.
No prior experience with agentic AI is required.
No advanced math is required.
A willingness to learn how AI systems work beyond surface-level prompts and tools.
Beginner friendly note
If you already know basic C++ but are new to AI agents, this course is designed to help you enter the topic in a structured, engineering-focused way.
Who is this course for?
This course is for
C++ developers who want to enter the fast-growing field of AI and agentic systems.
AI engineers and software engineers who want to understand how agents work under the hood instead of only using high level frameworks.
Students and self-taught developers who want a practical, modern and differentiated AI skill set.
Engineers building real systems who care about reliability, control, safety, and production-minded design.
Developers interested in ReAct, RAG, memory, planning and multi-agent workflows from an implementation perspective.
Anyone who wants to build a stronger foundation for future work inAI applications, agent systems and intelligent software architecture.
This course may not be ideal for
Absolute beginners with no programming background at all.
ones looking only for no-code AI tools or prompt-only tutorials.
Who this course is for
Anyone who wants to establish an AI startup
C++ developers who want to enter the fast-growing field of AI and agentic systems
AI engineers and software engineers who want to understand how agents work under the hood instead of only using high-level frameworks
Students and self-taught developers who want a practical, modern, and differentiated AI skill set
Engineers building real systems who care about reliability, control, safety, and production-minded design
Developers interested in ReAct, RAG, memory, planning, and multi-agent workflows from an implementation perspective
Anyone who wants to build a stronger foundation for future work in AI applications, agent systems, and intelligent software architecture
Homepage

https://www.udemy.com/course/ai-engineer-path-ai-agents-agentic-ai

RapidGator
https://rg.to/file/4675dbc6f6d4d9675da6bb8ec9bd6f90/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part1.rar.html
https://rg.to/file/0f54dfd05a8468a32c7db2daf07764ca/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part2.rar.html
https://rg.to/file/dd0eac41315914bc95c8542763875767/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part3.rar.html
https://rg.to/file/59a964169c4007fe89ad6456a11ebffd/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part4.rar.html
https://rg.to/file/91f362b129898b02b584514f89daa6fe/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part5.rar.html
https://rg.to/file/0af4b8d81836c97680eb2bebda013c05/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part6.rar.html
[b]AlfaFile[/b]
https://alfafile.net/file/AwuUd/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part1.rar
https://alfafile.net/file/AwuU4/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part2.rar
https://alfafile.net/file/AwuUw/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part3.rar
https://alfafile.net/file/AwuUC/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part4.rar
https://alfafile.net/file/AwuUX/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part5.rar
https://alfafile.net/file/AwuUB/glkti.AI.Engineer.Path.AI.Agents..Agentic.AI..ReAct.RAG.C.part6.rar

No Password - Links are Interchangeable