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Phase 1: Foundations + AI-103 + Positioning (Weeks 1–4)

Objective: Build the technical and positioning foundation for entering the v4 plan: applied Python, professional presence, and AI-103 readiness.

🎯 Expected Outcomes

By completing this phase:

  • Solid understanding of what AI is and how it transforms industries
  • Functional basic Python for automation
  • Git/GitHub operational with your own repository
  • AI-103 readiness defined by domain (with a gap matrix)
  • LinkedIn and GitHub configured professionally

Week 1: AI Foundations

Objective

Understand how AI is changing the labor market and industries.

Main Resources

ResourceLanguageTypeDuration
Elements of AI🇪🇸 SpanishFree course6-8 hrs
Microsoft AI Skills Navigator🇬🇧 EnglishLearning paths4-6 hrs
Google AI Essentials🇪🇸 SpanishCourse4 hrs
IBM AI Fundamentals🇬🇧 EnglishCourse3 hrs

Daily Activities (Monday to Friday)

DayActivityTime
MondayElements of AI — Chapters 1-22 hrs
TuesdayElements of AI — Chapters 3-42 hrs
WednesdayMicrosoft AI Skills — Module 12 hrs
ThursdayGoogle AI Essentials — Module 12 hrs
FridayReflection + learning journal1 hr

Weekly Deliverables

  1. Updated LinkedIn profile

    • Headline: "IT Professional | Transitioning to AI & Cloud Security"
    • About: Include forensics experience + AI vision
    • Skills: Add AI, Cloud Computing, Cybersecurity
  2. GitHub account created

    • Professional photo
    • Descriptive bio
    • Profile README
  3. Learning Journal (document in GitHub)

    • What did I learn this week about AI?
    • How does it connect to my prior experience?
    • What opportunities do I see?

Connection to Prior Experience

Your background in digital forensics gives you an advantage:

  • Pattern analysis → foundation of Machine Learning
  • Chain of custody → AI Governance and audit trails
  • Investigation → analytical thinking for AI
  • Documentation → transferable skills for AI compliance

Week 2: Python for AI Professionals

Objective

Basic Python programming focused on automation and data handling.

Main Resources

ResourceLanguageTypeDuration
Python para Todos (Py4E)🇪🇸 Spanish (subtitles)Free course + book10-12 hrs
Microsoft Learn: Python🇪🇸 SpanishLearning Path6 hrs
Codecademy Python🇬🇧 EnglishInteractive8 hrs
Automate the Boring Stuff🇬🇧 EnglishFree bookReference

Daily Plan

DayTopicResource
MondayVariables, data types, stringsPy4E Cap 1-2
TuesdayConditionals and loopsPy4E Cap 3-5
WednesdayFunctionsPy4E Cap 4
ThursdayFiles and CSVPy4E Cap 7
FridayBasic APIs (requests)Microsoft Learn
SaturdayProject of the week

🔨 Project: Security Log Automator

"""
Proyecto: Security Log Collector
Objetivo: Leer archivos de logs, extraer eventos críticos, generar CSV
Conexión con forensics: Automatización de lo que antes hacías manualmente
"""

# Habilidades demostradas:
# - Lectura de archivos
# - Parsing de texto
# - Escritura de CSV
# - Funciones reutilizables

Deliverable: GitHub repository with:

  • Functional script
  • README.md explaining the project
  • Input/output example
  • Documentation on how to run it

Week 3: Git and GitHub

Objective

Master the Git workflow for code and documentation management.

Main Resources

ResourceLanguageTypeDuration
GitHub Skills🇬🇧 EnglishInteractive4-6 hrs
Pro Git Book🇪🇸 SpanishFree bookReference
Microsoft Learn: Git🇪🇸 SpanishLearning Path3 hrs
Git Immersion🇬🇧 EnglishLabs2 hrs

Daily Plan

DayTopicPractice
MondayInstallation, config, first commitGitHub Skills: Intro
TuesdayBranches, merge, conflictsGitHub Skills: Branch
WednesdayPull requests, reviewsGitHub Skills: PR
ThursdayGitHub Pages, basic ActionsStatic deploy
FridayRepo organization, templatesCreate portfolio repo

🔨 Project: Professional Portfolio Repository

Create and publish an organized repository with:

portfolio/
├── README.md # Presentación profesional
├── projects/
│ └── security-log-collector/ # Proyecto semana 2
├── certifications/ # Tracking de certificaciones
├── notes/ # Notas de aprendizaje
└── docs/ # Documentación

Deliverable: Public GitHub repository with a professional structure.


Week 4: Azure AI Foundations for AI-103

Objective

Map Azure AI and agent fundamentals to the AI-103 domains so gaps are closed early.

Main Resources

ResourceLanguageTypeDuration
AI-103 Certification Page🇬🇧 EnglishOfficial reference1 hr
AI-103 Study Guide🇬🇧 EnglishOfficial guideReference
Step 1: Your First Agent🇬🇧 EnglishGuided lab1-2 hrs
Azure AI Foundry Training🇬🇧 EnglishLearning paths4-6 hrs

Daily Plan

DayAI-103 DomainTopic
MondayDomain 1Plan and manage Azure AI solutions
TuesdayDomain 2Implement generative AI and agentic solutions
WednesdayDomain 3Implement computer vision solutions
ThursdayDomain 4Implement text analysis solutions
FridayDomain 5Implement information extraction solutions
SaturdayPracticeGap matrix + objective-based rehearsal

Certification milestone: AI-103 readiness

  • Cost: Price by region (Pearson Vue)
  • Exam language: English (validate current availability)
  • Format: Proctored assessment, 120 minutes
  • Passing score: 700/1000
  • Recommended preparation: Initial 2-week sprint + domain gap closure

Connection to Prior Experience

  • IT Management → You already understand infrastructure, now in cloud
  • Forensics → Cloud forensics is a growing field
  • Operations → Cloud Operations (CloudOps) is high demand

📋 Phase 1 Checklist

  • LinkedIn updated with the new professional focus
  • GitHub account with complete profile
  • Elements of AI completed
  • Functional basic Python (log script)
  • Git workflow mastered
  • Portfolio repository created
  • AI-103 domain matrix completed
  • AI-103 gap closure plan defined
  • Learning journal up to date

v4 Operations

⏭️ Next Phase

Phase 2: Technical Portfolio — RAG, Agents, and Evaluation →