← Bootcamps

Enrollment open · classes start March 8, 2027

AI EngineeringBootcamp

From developer to AI Engineer, in 12 weeks.

LLMs, RAG, agents, MCP, cloud, MLOps and AI security, from design to production. Live online classes with experts.

See the program

From €990 (launch price), then €1,990 from February 21 · one-time payment, lifetime access

Classes start Monday, March 8, 2027 · launch price until February 20

Who is it for?

Built for developers

A technical bootcamp for professionals moving from conventional development to AI engineering.

In 10 seconds

Developer or data scientist, the same high bar

You're a developerYou move from conventional code to AI applications: RAG, agents, APIs, and a real production deployment.
You're a data scientistYour models leave the notebook: containerized, deployed to the cloud and monitored in production.
Developers
Data Scientists
ML Engineers
Data Engineers
Software Engineers
DevOps Engineers
Computer science students
Technical prerequisites
Progression

Three levels toward excellence

A structured path that mirrors how AI roles actually evolve inside companies.

🛠
Level 1

AI Developer

Building applications on AI APIs and simple workflows.

  • ✓ Python for AI
  • ✓ Data Engineering
  • ✓ Machine Learning
  • ✓ LLM & Prompt Engineering
⚡
Level 2

AI Engineer

Designing RAG systems and AI agents, cloud deployment, observability and security.

  • ✓ Advanced RAG & Agents
  • ✓ AI Applications (FastAPI, Next.js)
  • ✓ AI Cloud (Docker, K8s, Terraform)
  • ✓ MLOps / LLMOps
💎
Level 3

AI Architect

Distributed architecture, governance, cost optimization and AI platform design.

  • ✓ AI Security & Governance
  • ✓ Business use cases
  • ✓ Capstone project
  • ✓ Reference architecture
Program

36 modules to become an AI Engineer

12 progressive blocks. Every module combines theory, live coding and a hands-on project.

1
Python for AI
01

Advanced Python

Static typing, advanced OOP, async programming, testing and packaging professional Python projects.

02

Python Data Stack

Large-scale data manipulation with the modern Python ecosystem.

2
Data Engineering
03

Advanced SQL

Complex queries, performance tuning and relational modeling for AI.

04

Data Engineering

Building robust, scalable data pipelines with industry-standard tools.

3
Machine Learning
05

Scikit-Learn

Supervised and unsupervised ML fundamentals: classification, regression, clustering and ML pipelines.

06

Feature Engineering

Advanced data preparation techniques to get the most out of your models.

Rest of the program

Blocks 4 to 10: the modules

The detailed content, the tools taught and the project of each module unlock when you enroll.

4
Deep Learning
  • PyTorch
5
LLM & AI Agents
  • LLM
  • Prompt Engineering
  • RAG
  • LangChain
  • LangGraph
  • Model Context Protocol (MCP)
  • AI Agents
6
AI Applications
  • FastAPI
  • Authentication
  • WebSocket & Streaming
  • Next.js - AI Frontend
7
AI Cloud
  • Docker
  • Kubernetes
  • Terraform
  • Azure AI
  • Google Vertex AI
  • AWS Bedrock
8
MLOps / LLMOps
  • MLflow
  • Monitoring
  • CI/CD
  • Observability
9
AI Automation
  • n8n
  • Make
  • AI Workflows
  • Messaging integrations
10
AI Security
  • OWASP LLM Top 10
  • Prompt Injection
  • PII & GDPR
  • AI Governance
4
Deep Learning
07

PyTorch

Tensors, GPU compute, deep architectures (CNN, RNN, LSTM) and Transformers from scratch.

TensorGPUCNNRNNLSTMTransformer
🎯 Project: image recognition
5
LLM & AI Agents
08

LLM

Understanding and using large language models: architectures, APIs, comparisons and use cases.

GPTClaudeGeminiMistralLlamaQwen
🎯 Project: build your first chatbot
09

Prompt Engineering

Advanced prompting techniques for reliable, structured and reproducible outputs.

Zero ShotFew ShotXMLJSONStructured Output
🎯 Project: a production-ready prompt library
10

RAG

Retrieval Augmented Generation: indexing, semantic search, chunking and reranking.

EmbeddingsChunkingChromaQdrantPineconeWeaviate
🎯 Project: a knowledge-base document chatbot
11

LangChain

LLM chains, memory, tools and orchestration for complex AI applications.

🎯 Project: an intelligent business assistant
12

LangGraph

Execution graphs for advanced conversational agents with state handling and branching.

🎯 Project: a multi-step reasoning agent
13

Model Context Protocol (MCP)

MCP architecture: building tools, resources and MCP servers for IDE integration.

MCP architectureToolsResourcesServersIDE
🎯 Project: an MCP server exposing business data
14

AI Agents

Collaborative multi-agent systems with the leading frameworks.

Multi-AgentCrewAIAutoGenOpenAI Agents SDKAgno
🎯 Project: a team of collaborating agents
6
AI Applications
15

FastAPI

Design and expose fast, documented, production-ready AI APIs.

🎯 Project: build a complete AI API
16

Authentication

Securing AI applications with standard authentication and authorization.

JWTOAuthRBAC
17

WebSocket & Streaming

Real-time communication and LLM response streaming for responsive interfaces.

WebSocketLLM streamingSSE
18

Next.js - AI Frontend

Building modern interfaces for AI applications with React and Next.js.

ReactNext.jsAI UI/UX
7
AI Cloud
19

Docker

Containerizing AI applications: Dockerfile, multi-stage builds, volumes and networking.

20

Kubernetes

Container orchestration, autoscaling and deploying AI services on a cluster.

21

Terraform

Infrastructure as Code to provision and manage cloud resources reproducibly.

22

Azure AI

Azure OpenAI services, Cognitive Services, Azure ML and deploying on Azure.

23

Google Vertex AI

ML pipelines, Gemini API, Model Garden and deploying on Google Cloud.

24

AWS Bedrock

Foundation models, SageMaker, Lambda and deploying on Amazon Web Services.

🎯 Project: deploy an AI application to the cloud
8
MLOps / LLMOps
25

MLflow

Experiment tracking, model registry, reproducibility and ML artifact versioning.

26

Monitoring

Monitoring models and LLM pipelines in production.

LangfuseWeights & BiasesOpenTelemetry
27

CI/CD

Automating the AI application lifecycle with GitHub Actions.

GitHub ActionsAutomated testsContinuous deployment
28

Observability

Structured logs, distributed traces and metrics to diagnose AI systems in production.

LogsTracesMetrics
🎯 Project: take an AI service to production
9
AI Automation
29

n8n

Open-source AI workflow automation with native integrations and custom nodes.

30

Make

Visual automation scenarios connecting applications and AI services.

31

AI Workflows

Designing intelligent workflows that combine LLMs, APIs and business logic.

32

Messaging integrations

Deploying AI agents on communication platforms.

WhatsAppMessengerTelegramSlack
🎯 Project: multichannel sales agent
10
AI Security
33

OWASP LLM Top 10

The 10 critical vulnerabilities of LLM applications and how to defend against them.

34

Prompt Injection

Prompt injection attacks, jailbreaks and defense-in-depth techniques.

35

PII & GDPR

Personal data protection, anonymization and regulatory compliance for AI systems.

36

AI Governance

Governance frameworks, the EU AI Act, bias audits and responsible AI in the enterprise.

🎯 Project: secure an AI assistant
🔒

Rest of the program locked

The details of these modules, the tools taught and the project at each step unlock when you enroll.

Block 11

Business use cases

Apply your skills to real problems across 6 industries.

♦

Finance

Automated document analysis, risk scoring and ML fraud detection.

Document analysisScoringFraud
♦

Human Resources

Smart CV matching, a recruitment assistant and HR process automation.

CV matchingRecruitment assistant
♦

Legal

Contract analysis, clause extraction and AI compliance checking.

Contract analysisLegal NER
♦

Healthcare

OCR of medical records, document summarization and clinical decision support.

OCRSummarization
♦

Manufacturing

Predictive maintenance, anomaly detection and industrial process optimization.

Predictive maintenanceIoT
♦

Retail

Recommendation engine, smart support chatbot and customer experience personalization.

RecommendationSupport chatbot

🎓 Capstone Project - Block 12

Each team builds a complete AI solution end to end, ready for production:

✓ Technical architecture
✓ Source code
✓ Unit & integration tests
✓ Documented API
✓ Web interface
✓ Cloud deployment
✓ CI/CD pipeline
✓ Monitoring & alerts
✓ Technical documentation
✓ Final defense
🔒

The final project in detail

The full brief and the guidance come with enrollment.

Example capstone projects

RAG chatbot
Sales agent
Developer copilot
HR assistant
Legal assistant
Document analysis
Financial AI
Content platform
Multi-agent system
Medical assistant

📄 DataSAI AI Engineer certification

To earn the certification, every participant must:

Bonus

Exclusive masterclasses

10 bonus sessions to push your expertise further.

🛠
GitHub Copilot, Cursor, Claude Code and AI-augmented IDEs
💡
Advanced OpenAI API
🤖
Anthropic API - Claude in depth
🌌
Gemini API - Google AI Studio
🔌
MCP in depth - architecture & patterns
💰
Optimizing LLM costs in production
⚙
Fine-tuning and model adaptation
📈
Evaluating RAG systems
🎨
Multimodal AI - text, image, audio, video
🚀
Tracking new technology and AI product design methodology
Format

Your typical week

Twelve weeks, three modules a week. Plan for 15 to 20 hours a week: an intensive pace.

A typical week
Class and live codingTheory and code, live3 h
Guided labLive, on real cases3 h
Code review and Q&ALive, optional1.5 h
Project and practiceSelf-directed8–12 h
Teaching team

Who looks after your training

Classes are taught by the Academy's experts, and by Sylvie herself on some modules.

Sylvie Wendkuni NITIEMA, founder and head of learning at DataSAI Academy
Head of Learning

Sylvie Wendkuni NITIEMA

Founder of DataSAI Academy

An economist, statistician and data scientist, Sylvie has worked in data since 2013. Trained at ENSEA Abidjan and ENSAI Rennes, she led large-scale data projects at PwC, then designed and deployed data science models at scale at BNP Paribas and Renault.

She designs the DataSAI Academy programmes and teaches some of the modules herself. She selects the experts who teach alongside her and ensures the scientific and teaching quality of every course.

  • In data since 2013
  • Eiffel Excellence Scholarship
  • IBM Generative AI certified
Read her full story →
This bootcamp's experts7
Malak GHOURABI, Ph.D.

Malak GHOURABI, Ph.D.

PhD in Artificial Intelligence

RAG systems and AI agents, from research to production.

  • AI agents and RAG
  • IEEE publications
  • Associate professor qualification
Mehdi H.

Mehdi H.

Full-stack and mobile development

Production-ready web and mobile apps, AI included.

  • React Native, Flutter
  • Next.js, Node.js
  • Supabase, Firebase
Isaac PALOMINO ÁLVAREZ

Isaac PALOMINO ÁLVAREZ

AI solutions architecture

Enterprise AI agents, documented, monitored and handed over to teams.

  • OpenAI, Azure OpenAI
  • RAG architectures
  • Copilot Studio
Aansa MUBEEN

Aansa MUBEEN

Full-stack and LLM applications

LLM-powered apps, from the agent to the finished product.

  • Claude, RAG
  • TypeScript, NestJS
  • PostgreSQL, Supabase
David QUIROS

David QUIROS

Cloud and DevOps

Cloud platforms that hold up in production.

  • Kubernetes (CKA)
  • Terraform
  • CI/CD
Sameeran AMARNATH

Sameeran AMARNATH

Generative AI architecture, Coforge

RAG and multi-agent systems for enterprise clients.

  • Azure AI Foundry
  • LangGraph, LangChain
  • Edureka training
Ahmed ALI

Ahmed ALI

AI automation and voice agents

Voice agents and automations built in Python.

  • Python, FastAPI
  • LangChain, OpenAI
  • Retell AI, VAPI

Detailed expert profiles available on request. Message us on WhatsApp →

Close follow-up

You join this bootcamp's cohort: close follow-up from the team, and Sylvie in person on some modules. Your feedback will shape the cohorts that follow.

Plans

Choose your plan

Four levels of support to match your pace and your goals.

Based in West or Central Africa?
Essential

Full access

Support
€990
then €1,990 from February 21
One-time payment · Lifetime access
  • ✓ All 36 modules, delivered live
  • ✓ Source code & notebooks
  • ✓ Exercises & labs
  • ✓ Final project reviewed
  • ✓ DataSAI AI Engineer certification
  • - Exercises and labs reviewed
  • - Code review
  • - Discord community
  • - Bonus masterclasses
Professional

Guided

Support
€1,990
then €3,990 from February 21
One-time payment · Lifetime access
  • ✓ Everything in Essential
  • ✓ Exercises and labs reviewed
  • ✓ Code review
  • ✓ Discord community
  • ✓ Bonus masterclasses
  • - Group mentoring
  • - GitHub portfolio
  • - Capstone on a real project
  • - Technical interview preparation
Recommended plan
Career

Toward employment

Support
€2,990
then €5,990 from February 21
One-time payment · Lifetime access
  • ✓ Everything in Professional
  • ✓ Group mentoring
  • ✓ GitHub portfolio
  • ✓ Capstone on a real project
  • ✓ Technical interview preparation
  • - One-on-one mentoring
  • - Personalized code review
  • - GitHub portfolio audit
  • - 3 months of career support
Complete plan
Executive

Premium

Support
€4,990
then €7,990 from February 21
One-time payment · Lifetime access
  • ✓ Everything in Career
  • ✓ One-on-one mentoring
  • ✓ Personalized code review
  • ✓ GitHub portfolio audit
  • ✓ 3 months of career support
  • ✓ Partner company network
  • ✓ Priority access to future courses
Money-back guarantee

Full refund, on request, until the end of the first week of classes.

Secure payment

By card, through Stripe. One-time payment, lifetime access.

A question before you enroll?

Message us on WhatsApp or book a free discovery call.

What happens after you pay

  1. Your access arrives by emailYou receive a confirmation email and find your course in your DataSAI learning space.
  2. The full program unlocksEvery block, its detailed content, tools and projects open in your learning space.
  3. Classes start on Monday, March 8, 2027Live and online, with the Academy's experts.

And until the end of the first week of classes, you can change your mind: full refund.

For companies

Training a team?

Enroll several employees, or book a private session for your company built around examples from your industry.

  • Invoice in your company's name
  • Pricing based on the number of participants
  • Private sessions in English or French
  • A single point of contact
or book a call
Know someone who would love this bootcamp? Recommend it and earn 20% of their enrollment fee.Become a partner →

Limited spots. The launch price is available until February 20, 2027. Prices go up after that.

💬
Is the price a barrier? Message us on WhatsApp at +1 (904) 243-7876. Installments, pricing adapted to your country, or a scholarship: we look at your situation and find a way. No motivated learner is turned away over money.
FAQ

Everything you need to know before you start

Have another question? Message us on WhatsApp and we’ll get back to you quickly.

When does the bootcamp start?

Classes start on Monday, March 8, 2027, for twelve live weeks. The launch price is available until February 20, 2027. You receive the detailed session calendar in your account after enrolling.

Why is the detailed program only for enrolled learners?

The first blocks are visible on this page. The details of every module, the tools taught and the projects are available in your account as soon as you enroll. You keep the guarantee: a full refund until the end of the first week of classes.

What are the prerequisites?

This bootcamp is for people who already code: Python, Git, SQL, REST APIs and Docker basics. If you are new to programming, start with our Python for Data short courses or the Data Analyst Bootcamp.

How much time should I plan each week?

Plan for 15 to 20 hours a week over twelve weeks: 3 hours of class and live coding, a 3-hour guided lab, an optional 1.5-hour code review and Q&A, and 8 to 12 hours of self-directed project work.

What if I miss a live session?

Every session is recorded. Unlimited session replays are included in every plan, with lifetime access.

Which plan should I choose?

Every plan covers the same program; only the level of support changes. Essential gives you all 36 modules, with your final project reviewed. Professional adds exercise reviews, code review, the community and the masterclasses. Career adds group mentoring, a GitHub portfolio, a real-world project and technical interview prep. Executive adds one-on-one mentoring and three months of career support.

Can I pay in installments?

Yes. Prices shown are for a one-time payment, but we can set up installments: just message us on WhatsApp. If you live in the CFA franc zone, you’ll be offered pricing in CFA francs.

What if I change my mind?

You get a full refund at any time until the end of the first week of classes: just email contact@datasai.fr. After that, if something unexpected stops you from continuing, you can transfer your enrollment to the next cohort for free. If we postpone or cancel a cohort, you choose between a full refund and a transfer. Refunds go back to your original payment method within 14 days of your request.

How do I earn the certification?

The DataSAI AI Engineer certification is included in every plan. To earn it, you complete each block’s exercises and pass the capstone project, a complete production-ready AI solution presented to a panel of recognized experts.

Ready to become an AI Engineer?

Join the March cohort and build production-grade AI systems.

Questions about the program? Book a free discovery call →

AI Engineering BootcampStarts March 8 · from €990
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