Des guides pratiques sur l'IA & le RAG, l'automatisation, Power BI, l'ingénierie des données, le DevOps et le SEO — tirés de vrais projets — et des notes sur chaque certification.
IA & RAGLa génération augmentée par récupération permet à un LLM de répondre à partir de vos documents au lieu d'inventer. Voici l'architecture que j'ai utilisée dans une vraie plateforme data, étape par étape.
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AutomatisationComment j'ai remplacé des heures de prospection en copier-coller par un seul workflow n8n : OCR, un LLM qui rédige chaque e-mail, envoi Gmail et feuille de suivi.
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Business IntelligenceLa plupart des rapports Power BI lents ou faux ont un problème de modèle, pas de visuels. Voici comment je passe d'exports bruts à un schéma en étoile propre et des KPI fiables.
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Ingénierie des donnéesDes chiffres faux dans un tableau de bord détruisent la confiance plus vite que des rapports lents. Voici mon approche en couches : règles d'abord, statistiques ensuite, machine learning seulement si nécessaire.
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Cloud & DevOpsUne chaîne de livraison complète et reproductible pour une petite équipe : infrastructure as code, un cluster Kubernetes léger et un pipeline qui déploie à chaque push.
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SEO & WebLa recherche a désormais deux publics : Google et les moteurs de réponse IA. Voici la checklist que j'ai appliquée à ce site, avec le code Next.js.
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Full-Stack DevelopmentCodecademy's Full-Stack Engineer Career Path took me through the entire web stack — HTML/CSS, JavaScript, React, Node.js, Express, and SQL databases — the same layers I now use in production-style projects like a MERN blog platform and a Spring Boot/React housing management system.
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Back-End DevelopmentA factual breakdown of Codecademy's Back-End Engineer Career Path — the JavaScript, Node.js, Express, SQL/PostgreSQL, Git, and authentication modules I completed, and how they map onto my shipped production projects.
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Front-End DevelopmentA breakdown of what Codecademy's Front-End Engineer Career Path actually covers — HTML/CSS, JavaScript, React, TypeScript, Git, and automated testing — and how I've applied it on real React and JavaScript projects.
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Computer Science FundamentalsA factual breakdown of Codecademy's Computer Science Career Path — the Python, OOP, data structures, algorithms, Big O, SQL, and Git curriculum behind my software engineering fundamentals.
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Business Intelligence & Data AnalyticsI completed Codecademy's Business Intelligence Data Analyst Career Path — here's exactly what the SQL, Python, pandas, Excel, and Tableau curriculum covers, and how it shows up in my real projects.
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Data EngineeringCodecademy's Data Engineer Career Path took me through Python, SQL, Pandas, PySpark, and MongoDB — the toolkit companies need to move data reliably from source to product, taught through graded, portfolio-grade projects rather than quizzes.
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Data AnalyticsA breakdown of what Codecademy's Data Scientist: Analytics Specialist Career Path actually teaches — SQL, Python, pandas, statistics, Tableau, and Excel — and how it shows up in Anass Essadikine's real project work.
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Data ScienceA breakdown of Codecademy's Data Scientist: Inference Specialist Career Path — the statistics, hypothesis testing, and Python/SQL/R curriculum behind my ability to reason rigorously about data, not just build models with it.
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Data ScienceA first-person look at Codecademy's Data Scientist: Natural Language Processing Specialist career path — the regex-driven text preprocessing, word-embedding, and neural text-generation skills I added on top of my Python data-science stack.
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JavaScript DevelopmentA breakdown of Meta's JavaScript Programming Essentials certification: the actual curriculum modules, tools, and how these core JS skills map onto Anass Essadikine's own full-stack projects.
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Agile & Project ManagementA factual look at what Google's Agile Project Management course actually teaches — Scrum roles, sprint events, backlog refinement, and story-point estimation — and how it maps onto real full-stack and DevOps projects I've shipped.
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Data AnalysisA breakdown of Microsoft's Excel for Data Analysis certification: the real curriculum modules, the formulas and cleaning functions it teaches, and how I've carried those habits into my Python and ML projects.
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AI & Career SkillsA practical breakdown of ALX's AI Career Essentials certification: the prompt engineering, generative AI, ethics, and AI-assisted data analysis skills I apply across my full-stack and data science projects.
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Cloud & DevOpsI completed Codecademy's Intro to Cloud Computing course, covering deployment models, IaaS/PaaS/SaaS, and the AWS/Azure/GCP landscape — the conceptual layer underneath my hands-on cloud deployment work.
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Cloud & DevOpsA breakdown of what Codecademy's Introduction to DevOps course actually covers — DevOps culture, infrastructure, monitoring, resiliency, and CI/CD pipelines — and how each concept shows up in my hands-on Docker/Kubernetes/Terraform deployment work.
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Cloud & DevOpsA factual breakdown of Codecademy's "Working with Containers: Introduction to Docker" certification — the services model, workflow, image anatomy, and Dockerfile skills it covers — and how I've applied every piece of it in a live CI/CD pipeline.
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Cloud & DevOpsI completed Codecademy's "Working with Containers: Introduction to Kubernetes" course to formalize the orchestration concepts behind my hands-on Docker and K3s deployment work — here's exactly what it covers and how it plugs into real infrastructure.
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Cloud & DevOpsA breakdown of what Codecademy's AWS Developer Services & Tools course actually covers — CodeCommit, CodeBuild, CodeDeploy, CodePipeline, Elastic Beanstalk, and CloudFormation — and how it maps to my own AWS CI/CD project.
Lire l'articleJe suis ouvert aux missions freelance, aux stages et aux postes à temps plein dans le web, la data et le cloud.