Expliquewatch · explain · prove

← all topics

langchain ile müşteri destek dokümantasyonu otomasyonu

5 lessons · 4:54 · updated 9/5/2026
19 of the lessons are not in Turkish; each one says which language it is in.

Watch them in order, then explain the topic in your own words below.

Nobody with subject knowledge has checked this course yet. It was put together automatically.

What you will do in this course

  • LangChain Nedir
  • Ortamı Kurma
  • Gelişmiş RAG Chatbot
  • Basit RAG Uygulaması
  • LLM Hatalarını Ayıkla
0 / 5 lessons watched

Getting started

18 lessons

1. LangChain Course 1 - Introduction | 10 + examples

in English

LangChain Nedir

Ahmad Teaches · watch the original · 1:20

2. What You’ll Learn

in English

Test Troop Academy · watch the original · 1:35

3. Python & Ollama Setup

in English

Test Troop Academy · watch the original · 2:00

4. Major components in Langchain

in English

CodingCupcakes · watch the original · 1:11

5. InstructGPT

in English

CodingCupcakes · watch the original · 2:25

6. Tools and agents (the audo gets better)

in English

CodingCupcakes · watch the original · 4:56

7. VS Code (agents using wikipedia and arxiv tools)

in English

CodingCupcakes · watch the original · 8:15

8. OpenAI Chat Model ve API Bağlantısı

Emrullah Yaprak | Yapay Zeka & Otomasyon · watch the original · 2:14

9. AI Agent Hafıza Yönetimi (Simple Memory)

Emrullah Yaprak | Yapay Zeka & Otomasyon · watch the original · 3:57

10. Google Sheets AI Agent: Müşteri Otomasyonu

Emrullah Yaprak | Yapay Zeka & Otomasyon · watch the original · 6:08

11. Background: Chatbot Design Challenges

in English

AI Agent VN · watch the original · 1:23

12. Tutorial Roadmap: From Simple to Complex

in English

AI Agent VN · watch the original · 4:12

13. Set up Development Environment

in English

AI Agent VN · watch the original · 3:14

14. Part 1: Designing a Simple Zero-Shot Agent

in English

AI Agent VN · watch the original · 6:04

15. Part 2: Add User Confirmation

in English

AI Agent VN · watch the original · 3:29

16. Part 3: Conditional Interrupts

in English

AI Agent VN · watch the original · 5:33

17. Zero-shot Design Limitations and Solutions

in English

AI Agent VN · watch the original · 2:18

18. Part 4: Specialized Workflows (Intro)

in English

AI Agent VN · watch the original · 2:18

Check yourself

Four questions on this section. Wrong answers are the point: each one explains itself.

Now you explain it

Close what you watched and explain the topic in your own words in 30 seconds. What you can explain is what you have learned. You are marked against this course's lessons and nothing beyond them.

Explain how you would do this: Getting started — LangChain Nedir.

You are judged on these, and nothing else in the course:

  • LangChain Nedir

Doing it properly

3 lessons · short section, not a full path on its own

1. Langchain & Langgraph Documentation Chatbot Walkthrough

in English

Ortamı Kurma

Rutam Bhagat (rutamstwt) · watch the original · 1:21

2. RAG - 15 lines of code - Langchain + python + OpenAI

in English

Basit RAG Uygulaması

The AI Dude - Tamil · watch the original · 0:41

3. Why LLM Calls Fail: Context vs. Model — Debugging with Traces in LangSmith

in English

LLM Hatalarını Ayıkla

Luca Berton · watch the original · 0:45

Check yourself

Four questions on this section. Wrong answers are the point: each one explains itself.

Now you explain it

Close what you watched and explain the topic in your own words in 30 seconds. What you can explain is what you have learned. You are marked against this course's lessons and nothing beyond them.

Explain how you would do this: Doing it properly — LLM Hatalarını Ayıkla.

You are judged on these, and nothing else in the course:

  • Ortamı Kurma
  • Basit RAG Uygulaması
  • LLM Hatalarını Ayıkla

Going deeper

1 lessons · short section, not a full path on its own

1. I will build advanced rag chatbot with langchain and local llms

in English

Gelişmiş RAG Chatbot

AI DEVELOPMENT · watch the original · 0:47

Check yourself

Four questions on this section. Wrong answers are the point: each one explains itself.

Now you explain it

Close what you watched and explain the topic in your own words in 30 seconds. What you can explain is what you have learned. You are marked against this course's lessons and nothing beyond them.

Explain how you would do this: Going deeper — Gelişmiş RAG Chatbot.

You are judged on these, and nothing else in the course:

  • Gelişmiş RAG Chatbot