[FR] IA Full-Stack avec Ollama : Llama, Deepseek, Mistral

[FR] IA Full-Stack avec Ollama : Llama, Deepseek, Mistral – taught by School of AI – is a hands‑on Udemy course that lets you build real‑world AI applications without costly cloud APIs. Updated July 2026, the training covers model deployment, prompt engineering, and full‑stack integration, delivering a practical path from zero to production‑ready AI services. Whether you search for a free IA full‑stack course, an Udemy course on LLMs, or want to learn IA online, this program provides concrete projects, certification, and lifetime access.

What You'll Learn

• Build end‑to‑end AI applications using Ollama, FastAPI, and Python, targeting real‑time data streams.
• Master deployment of open‑source LLMs such as LLaMA 3, Mistral, Mixtral, DeepSeek‑R1, and CodeLlama on local hardware.
• Learn NLP techniques for summarization, information extraction, and sentiment analysis on French and multilingual texts.
• Understand prompt‑engineering strategies that maximize model accuracy and reduce hallucinations in production.
• Create intelligent chatbots, support‑assistant tools, and automated résumé generators powered by LLMs.
• Implement code‑generation and debugging assistants with CodeLlama to accelerate software development cycles.
• Apply API integration skills to fetch live data, process it through LLMs, and display results in responsive web interfaces.
• Analyze performance metrics and optimize inference speed using Ollama configuration and hardware‑aware tuning.

Course Details

• Instructor: School of AI
• Rating: 4.0 stars (reviews not disclosed)
• Language: French (fr‑FR)
• Enrolled students: 545 248
• Certificate: Yes, upon completion
• Includes: Lifetime access, mobile‑friendly playback, downloadable resources

What This Course Covers

Module 1 – Introduction & Ollama Setup

• Install Ollama on Windows, macOS, and Linux, verifying hardware compatibility.
• Configure local LLM repositories and manage model versions with simple CLI commands.
• Run first inference tests with LLaMA 3 and verify output quality.
• Troubleshoot common installation issues and optimize GPU/CPU usage.

Module 2 – Core Language Models & Prompt Engineering

• Explore architecture differences between LLaMA 3, Mistral, Mixtral, and DeepSeek‑R1.
• Design effective prompts for text summarization, question answering, and code completion.
• Compare zero‑shot vs. few‑shot prompting techniques on French corpora.
• Evaluate model responses using BLEU, ROUGE, and custom relevance scores.

Module 3 – Full‑Stack Development with FastAPI

• Build a FastAPI backend that serves LLM inference via REST endpoints.
• Secure the API with token‑based authentication and rate‑limiting middleware.
• Connect a React/Vue front‑end to display generated content in real time.
• Deploy the full stack locally using Docker Compose for reproducible environments.

Module 4 – Practical Projects & Automation

• Create an intelligent news‑summarizer that fetches RSS feeds and generates concise briefs.
• Develop a code‑review assistant that suggests fixes and refactors Python snippets.
• Implement a customer‑support chatbot capable of handling multilingual queries.
• Automate résumé parsing and candidate scoring using NLP pipelines.

Module 5 – Performance, Scaling & Best Practices

• Profile inference latency and memory consumption across different hardware setups.
• Apply quantization and knowledge‑distillation to reduce model size without losing accuracy.
• Set up batch processing pipelines for high‑throughput document analysis.
• Document best practices for version control, testing, and continuous integration of AI services.

Who Should Take This Course

• Beginners and autodidacts who want to start building AI solutions without prior experience.
• Startup founders and product innovators looking to prototype AI‑driven features quickly.
• Data analysts and researchers needing automated text extraction and summarization tools.
• Tech entrepreneurs and product managers responsible for integrating LLMs into business workflows.
• Developers and programmers eager to add AI capabilities to web applications using Python and FastAPI.

Prerequisites

• No prior experience needed — this course is beginner‑friendly and guides you step by step.
• Basic familiarity with Python syntax is recommended to accelerate hands‑on exercises.

Why Enroll in This Course

This training delivers a complete, production‑ready AI stack, letting you skip expensive cloud subscriptions. A free coupon provides 100 % off for a limited time, making the full curriculum accessible without financial risk. Compared with generic AI tutorials, this course focuses on open‑source LLMs, local deployment, and real‑world projects that directly translate to job‑ready skills.

Course Highlights

• Lifetime access to all video lectures, code samples, and future updates.
• Self‑paced learning allows you to progress according to your schedule and revisit complex topics.
• Certificate of completion validates your expertise for resumes and professional profiles.
• 30‑day money‑back guarantee ensures satisfaction and reduces enrollment hesitation.