Mistral AI Fundamentals Training in Astana, Kazakhstan

Mistral AI Fundamentals is a practical, easy-to-understand training program designed for beginners who want to learn how to use Mistral AI for content creation, automation, chatbots, and real-world applications. Learners will explore the Mistral Playground, run models locally for free using tools like Ollama, and learn the basics of prompting, building simple applications, and using Retrieval-Augmented Generation (RAG).

The program keeps technical complexity low and focuses on hands-on learning, real use cases, and clear explanations suitable for non-developers and first-time AI users.

Understanding Mistral AI + Basic Usage

1. What is Mistral AI?

• What is Generative AI?
• What makes Mistral different?
• Mistral’s open-source philosophy (easy explanation)
• Comparing popular models in simple terms:
• Mistral vs GPT
• Mistral vs Llama
• Mistral vs Claude / Gemini
• Overview of Mistral models (high-level):
• Mistral 7B
• Mixtral 8x7B
• Mixtral 8x22B
• Codestral (for code)
• Mistral Small / Large

2. Basic Concepts

• What is a token
• What is a “Mixture-of-Experts”
• Strengths of Mistral
• Where Mistral struggles (limitations)
• Simple guidance on choosing a model

3. Getting Started with Mistral — No Coding Required

• Create a free Mistral account
• How to use the Mistral Playground
• Text completion vs chat models (with examples)
• What are embeddings? (simple use cases only)
• Understanding rate limits & pricing basics

Hands-On Practice:

• Trying your first prompt
• Writing system instructions
• Experimenting with few-shot prompts
• Making the model generate structured output (like JSON)

4. Prompt Engineering

• How to write clear prompts
• How to control tone & style
• Zero-shot and few-shot examples
• Creating simple templates for:
• Q&A
• Summaries
• Creative writing
• Social media content

5. Hands-On Labs

• Build a simple content generator in Playground
• Create a chatbot-style conversation
• Improve answers using better prompt instructions

App Building, Local Models, RAG Basics & Security

6. Using Mistral in Real Applications

• Copy–paste API call example
• Pre-written Python example
• Pre-written JavaScript example
• How chatbots work at a high level
• Using Mistral for:
• Automation
• Content creation
• Business use cases

7. Running Mistral on your system

• Install Ollama
• Download Mistral 7B with one command
• Run simple prompts locally
• Basic performance tips

8. RAG (Retrieval-Augmented Generation)

• What is RAG? (simple example: "upload your documents → ask questions")
• Why RAG is useful
• Simple explanation of vector databases
• High-level flow:
• Upload → Break text → Search → Answer

Hands-On Exercises

9. Intro to Fine-Tuning

• What is fine-tuning?
• Why companies use it
• What is LoRA/QLoRA in simple words
• When to fine-tune vs when to improve prompts

10. Security & Governance

• How to keep API keys safe
• What is prompt injection
• How to avoid unsafe prompts
• Data privacy basics
• Simple logging & audit ideas

11. Practical Use Cases

• Customer support reply generator
• Document summarizer
• FAQ assistant
• Coding helper using Codestral
• Social media content creator