Self-Paced Study Plan 2026

Overview

This study plan integrates five major learning streams with specific milestones, resources, and timelines. The plan is designed to be flexible and self-paced, with quarterly reviews to assess progress and adjust as needed.

Study Streams:

1. AWS & Cloud Architecture
2. Generative AI & LLMs
3. Backend Development (Python & Go)
4. Philosophy & Humanities
5. Spanish Language
6. Privacy Engineering & Cybersecurity
7. Financial Analysis

Study Stream 1: AWS & Cloud Architecture

Goal

Achieve AWS Solutions Architect Professional certification and develop expertise in cloud solutions design.

Timeline & Milestones

Q1 2026 (Jan - Mar)

• Begin AWS Solutions Architect Professional exam prep
• Review core AWS services (EC2, S3, VPC, RDS, Lambda)
• Complete 2-3 practice exams
• Milestone: Complete foundational review by end of March

Q2 2026 (Apr - Jun)

• Deep dive into advanced topics: security, compliance, cost optimization
• Review reference architectures
• Complete 3-4 full practice exams
• Milestone: AWS Solutions Architect Professional Certification (target: June)

Resources

• Course: A Cloud Guru or Linux Academy AWS Solutions Architect Professional course
• Books: AWS Well-Architected Framework whitepaper
• Practice: Tutorials Dojo or Whizlabs practice exams
• Study Cadence: 5-7 hours/week

Integration Points

• Use Go projects (Stream 3) for hands-on Lambda development
• Apply system design knowledge (Stream 3) to architecture problems

Study Stream 2: Generative AI & LLMs

Goals

• AWS AI Practitioner certification
• AWS Generative AI Developer certification
• Build understanding of LLMs from foundational principles
• Complete a project implementing generative AI solutions

Timeline & Milestones

Q1 2026 (Jan - Mar)

• Begin “Build a LLM from Scratch” book (parallel with AWS core study)
• AWS AI Practitioner exam prep
• Set up Python environment for ML/AI work
• Milestone: AWS AI Practitioner Certification (target: March)

Q2 2026 (Apr - Jun)

• Continue “Build a LLM from Scratch” book completion
• AWS Generative AI Developer exam prep
• Start implementing a small GenAI project (e.g., RAG application, fine-tuned model)
• Milestone: AWS Generative AI Developer Certification (target: June)

Q3 2026 (Jul - Sep)

• Complete “Build a LLM from Scratch” book
• Refine and document GenAI project
• Explore advanced topics: prompt engineering, evaluation metrics, model optimization
• Milestone: Complete LLM project with documentation

Resources

• Book: “Build a LLM from Scratch” (Appendix or main text)
• Courses: AWS GenAI Developer course, DeepLearning.AI courses on LLMs
• Practice: Kaggle competitions, personal GenAI projects
• Study Cadence: 6-8 hours/week

Integration Points

• Use Python skills from Stream 3
• Apply backend architecture patterns to GenAI applications
• Document learning in philosophical context (how AI shapes thought)

Study Stream 3: Backend Development

Goals

• Master intermediate-to-advanced Python concepts
• Learn Go and build production-quality projects
• Understand software architecture and system design principles
• Develop practical backend expertise

Sub-Stream 3A: Python Mastery (Optimization for Expert Level)

Timeline & Milestones

Q1-Q4 2026 (Jan - Dec, strategic reading)

• Read “Fluent Python” selectively (focus on advanced sections: metaclasses, decorators, async, type hints)
• Skip foundational chapters given your expertise
• Implement 1-2 advanced patterns per month
• Apply learnings to GenAI projects and production code
• Milestone: Master 3-4 advanced Python concepts (ongoing)

Resources

• Book: “Fluent Python” by Luciano Ramalho (selective, advanced chapters only)
• Study Cadence: 1-2 hours/week
• Project Integration: Apply to GenAI and production backend work

Recommendation: As a Python expert, you don’t need linear progression through Fluent Python. Target specific advanced topics relevant to your current projects rather than completing the whole book.

Sub-Stream 3B: Go Language

Timeline & Milestones

Q2-Q3 2026 (Apr - Sep)

• Learn Go fundamentals (concurrency, goroutines, channels)
• Build 2-3 backend projects in Go
  • Project 1: REST API with database
  • Project 2: Microservice with message queue
  • Project 3: CLI tool or Lambda function alternative
• Milestone: Complete 3 Go projects (target: September)

Q4 2026 (Oct - Dec)

• Refine Go projects, add testing and documentation
• Contribute to open-source Go project or polish personal projects

Resources

• Course: “The Go Programming Language” course (Udemy or similar)
• Book: “The Go Programming Language” by Donovan & Kernighan
• Practice: Exercism, LeetCode (Go track)
• Study Cadence: 5-6 hours/week

Sub-Stream 3C: Software Architecture & System Design

Timeline & Milestones

Q3-Q4 2026 (Jul - Dec)

• Read software architecture books (rotating monthly)
  • Month 1: “Building Microservices” by Sam Newman
  • Month 2: “System Design Interview” preparation
  • Month 3: “The Pragmatic Programmer”
• Study system design patterns and principles
• Document architectural decisions in Go projects
• Milestone: Apply 3 architecture patterns to projects

Resources

• Books: “Building Microservices,” system design resources
• Practice: System design interview prep (Educative, ByteByteGo)
• Study Cadence: 4-5 hours/week

Integration Points

• AWS Lambda and serverless patterns (Stream 1)
• GenAI backend infrastructure (Stream 2)
• Use Go for deploying AI models

Study Stream 4: Philosophy & Humanities

Goal

Develop deep engagement with contemporary philosophy, critical theory, and humanistic thought, particularly focusing on technology, society, and authenticity.

Timeline & Milestones

Full Year 2026: Philosophical Book Club

Structured monthly reading (Jan-Dec) combining philosophy, critical theory, and speculative fiction. Each month includes:

• Two readings (one book/long-form text, one essay/theory)
• Weekly discussion/reflection
• Personal notes and synthesis

Monthly Schedule:

Study Cadence: 6-8 hours/week (reading, reflection, note-taking)

Sub-Project 4A: A Grande Conversa

Timeline: January - December 2026 (ongoing)

• Course: Alex Castro’s course via Facebook
• Commitment: Complete all required readings and course modules
• Integration: Align readings with monthly book club selections where possible
• Study Cadence: 2-3 hours/week

Milestone: Course completion by December 2026

Resources

• Books: As listed above
• Course: Facebook (A Grande Conversa)
• Method: Reading journals, weekly reflection notes, thematic connections document

Integration Points

• Connect technology studies to philosophical frameworks
• Document how GenAI and backend systems relate to philosophical questions about technology, authenticity, and thought
• Use philosophical insights to inform learning in other streams

Study Stream 5: Spanish Language

Goal

Develop conversational and reading proficiency in Spanish throughout 2026.

Timeline & Milestones

Q1 2026 (Jan - Mar)

• Establish daily study habit (20-30 minutes)
• Focus on conversational basics
• Milestone: Complete foundational coursework

Q2 2026 (Apr - Jun)

• Increase speaking practice
• Begin reading Spanish texts (news, philosophy articles in Spanish)
• Milestone: Have basic conversations, understand news articles

Q3 2026 (Jul - Sep)

• Advanced conversation practice
• Read philosophical texts or fiction in Spanish
• Consider speaking exchanges
• Milestone: Conversational competency

Q4 2026 (Oct - Dec)

• Maintain and deepen skills
• Read “Ficciones” - Jorge Luis Borges in Spanish version
• Milestone: Sustained conversational ability

Resources

• App: Lingq
• Conversation: Italk
• Media: Spanish-language podcasts, news (BBC Mundo, CNN en Español)
• Study Cadence: 4-5 hours/week

Study Stream 6: Privacy Engineering & Cybersecurity (NEW)

Goals

• Complete Google Cybersecurity Professional Certificate
• Complete Introduction to Python for Cybersecurity
• Build practical expertise in privacy-preserving technologies
• Understand regulatory frameworks (GDPR, HIPAA)
• Develop hands-on skills with ZKPs, Digital ID, E2EE, TEE, Tokenization

Timeline & Milestones

Q1 2026 (Jan - Mar)

• Complete: Introduction to Python for Cybersecurity (in progress)

• Begin

  Google Cybersecurity Professional Certificate

  • Complete Courses 1-3 (Foundations, Security Risks, Networks)

• Study GDPR fundamentals and privacy principles

• Milestone: Python for Cybersecurity completed, Google Cert 40% complete (March)

Q2 2026 (Apr - Jun)

• Complete

  Google Cybersecurity Professional Certificate

  • Courses 4-8 (Linux, Assets/Threats, Detection, Python automation, Incident response)

• Begin privacy engineering deep dive: E2EE fundamentals

• Explore AWS security and compliance services (integration with Stream 1)

• Milestone: Google Cybersecurity Professional Certificate (target: June)

Q3 2026 (Jul - Sep)

• Deep dive into advanced privacy technologies:
  • Zero-Knowledge Proofs (ZKPs): theory and implementations
  • Trusted Execution Environments (TEEs): Intel SGX, AWS Nitro Enclaves
  • Digital Identity systems: decentralized identity, verifiable credentials
• Build project: Privacy-preserving authentication system or ZKP implementation
• Study HIPAA compliance in detail
• Milestone: Complete 1 privacy engineering project (September)

Q4 2026 (Oct - Dec)

• Advanced topics: Tokenization, differential privacy, secure multi-party computation
• Study privacy engineering in AI/ML contexts (federated learning, privacy-preserving ML)
• Document privacy engineering project
• Create personal reference guide for privacy regulations (GDPR, HIPAA, CCPA)
• Milestone: Privacy engineering portfolio piece completed

Resources

Certifications & Courses:

• Introduction to Python for Cybersecurity (Q1)
• Google Cybersecurity Professional Certificate (Q1-Q2)
• Privacy Engineering courses (Coursera, Udacity, or specialized platforms)

Books:

• “Applied Cryptography” by Bruce Schneier (selective reading)
• “The Privacy Engineer’s Manifesto” by Bamberger & Mulligan
• “Zero Trust Networks” by Gilman & Barth

Technical Resources:

• ZKP libraries: libsnark, bellman, circom
• TEE documentation: Intel SGX SDK, AWS Nitro Enclaves
• Digital ID standards: W3C DID, Verifiable Credentials

Regulatory:

• GDPR official text and guidance
• HIPAA Privacy and Security Rules
• NIST Cybersecurity Framework

Study Cadence: 6-8 hours/week

Integration Points

• Apply cybersecurity principles to AWS architecture (Stream 1)
• Implement privacy-preserving techniques in GenAI projects (Stream 2)
• Use Python and Go for security tools and implementations (Stream 3)
• Connect privacy engineering to philosophical questions about surveillance, identity, autonomy (Stream 4)
• Understand privacy regulations in financial contexts (Stream 7)

Study Stream 7: Financial Analysis

Goals

• Understand financial statements and business valuation
• Develop skills to evaluate startup and public company financials
• Build competency for technical review of finance books
• Prepare for future roles: Advisor, Board Member, Startup Investor

Timeline & Milestones

Q1 2026 (Jan - Mar)

• Begin: Fundamentals of Financial Analysis (Coursera)
• Learn financial statement basics: Income Statement, Balance Sheet, Cash Flow Statement
• Practice reading 10-K and 10-Q reports from public tech companies
• Milestone: Complete Coursera course modules 1-4 (March)

Q2 2026 (Apr - Jun)

• Complete: Fundamentals of Financial Analysis (Coursera)
• Deep dive into financial ratios and metrics (profitability, liquidity, solvency, efficiency)
• Study valuation methods: DCF, comparable companies, precedent transactions
• Analyze 3-5 public tech companies (read their financial statements, create models)
• Milestone: Fundamentals of Financial Analysis completed (June)

Q3 2026 (Jul - Sep)

• Advanced financial modeling and analysis
• Study startup finance: cap tables, equity structures, funding rounds, term sheets
• Read case studies of successful and failed startups (financial perspective)
• Take additional course: Financial Modeling or Venture Capital/Startup Finance
• Milestone: Create financial model for 2-3 startup case studies (September)

Q4 2026 (Oct - Dec)

• Focus on governance and advisory roles: fiduciary duties, board dynamics
• Study how to evaluate early-stage companies (unit economics, burn rate, runway)
• Create personal framework for startup evaluation
• Network and shadow advisors/board members (if possible)
• Begin reviewing finance books with technical lens
• Milestone: Personal startup evaluation framework completed (December)

Resources

Courses:

• Fundamentals of Financial Analysis (Coursera) - Q1-Q2
• Financial Modeling courses (Coursera, Udemy, or CFI) - Q3
• Venture Capital and Startup Finance course (Coursera or similar) - Q3

Books:

• “Financial Intelligence” by Berman & Knight
• “The Interpretation of Financial Statements” by Benjamin Graham
• “Venture Deals” by Brad Feld & Jason Mendelson
• “The Hard Thing About Hard Things” by Ben Horowitz (for operational context)

Practice:

• SEC EDGAR database (read 10-Ks, 10-Qs, proxy statements)
• Company investor relations pages
• Startup pitch decks and financial models (public examples)
• Financial news: WSJ, Financial Times, Bloomberg

Tools:

• Excel/Google Sheets for modeling
• Financial databases: Yahoo Finance, Seeking Alpha
• Cap table tools: Carta, Pulley (for understanding)

Study Cadence: 5-6 hours/week

Integration Points

• Understand financial implications of technology decisions (all technical streams)
• Evaluate AI/ML companies and products (Stream 2)
• Analyze SaaS metrics and cloud economics (Stream 1)
• Consider financial privacy and data governance (Stream 6)
• Apply critical thinking from philosophy to business analysis (Stream 4)

Integration & Weekly Structure

Recommended Weekly Schedule (30-35 hours/week total)

• Quarterly Milestones & Reviews (Revised)

  Q1 2026 Review (Late March)

  Completed:

  • AWS foundational review complete
  • AWS AI Practitioner certified
  • Introduction to Python for Cybersecurity completed
  • Google Cybersecurity Certificate 40% complete
  • Fundamentals of Financial Analysis 50% complete
  • Spanish basics established
  • Philosophy: 3 books completed

  Action: Assess certification pace, adjust Q2 technical load

  ---

  Q2 2026 Review (Late June)

  Completed:

  • AWS Solutions Architect Professional certified
  • AWS Generative AI Developer certified
  • Google Cybersecurity Professional Certificate completed
  • Fundamentals of Financial Analysis completed
  • Fluent Python completed (selective reading)
  • Go learning commenced with first project
  • GenAI project initiated
  • Philosophy: 6 books completed total
  • Spanish conversational basics

  Action: Plan Q3 project focus (privacy engineering, GenAI, Go), evaluate financial analysis depth needed

  ---

  Q3 2026 Review (Late September)

  Completed:

  • GenAI project advancing
  • Privacy engineering project completed
  • 2+ Go projects completed
  • Architecture book series started
  • Startup financial models created (2-3 case studies)
  • Advanced privacy technologies studied (ZKPs, TEEs, Digital ID)
  • Philosophy: 9 books completed total
  • Spanish conversational competency

  Action: Plan Q4 refinement and documentation phase

  ---

  Q4 2026 Review (Late December)

  Completed:

  • 3 Go projects completed
  • GenAI project documented
  • Privacy engineering portfolio piece completed
  • Startup evaluation framework created
  • Book club year concluded (12 philosophy books)
  • A Grande Conversa course completed
  • Spanish sustained competency with reading capability
  • Personal reference guides completed (privacy regulations, financial analysis frameworks)

  Action: Plan 2027 continuation, consider advanced certifications (CISSP, AWS Security Specialty), deeper finance topics

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  Success Criteria (Revised)

  Technical Certifications

  • ✓ AWS Solutions Architect Professional (Q2)
  • ✓ AWS AI Practitioner (Q1)
  • ✓ AWS Generative AI Developer (Q2)
  • ✓ Google Cybersecurity Professional Certificate (Q2)

  Courses Completed

  • ✓ Introduction to Python for Cybersecurity (Q1)
  • ✓ Fundamentals of Financial Analysis (Q2)
  • ✓ A Grande Conversa (Q4)

  Books Completed

  • ✓ Fluent Python - selective reading (Q1-Q2)
  • ✓ Build a LLM from Scratch (Q3)
  • ✓ 12 Philosophy Book Club books (ongoing)
  • ✓ 2-3 Privacy Engineering/Cybersecurity books (selective)
  • ✓ 2-3 Financial Analysis books (Q2-Q4)

  Projects Delivered

  • ✓ 3 Go backend projects (Q2-Q4)
  • ✓ 1 GenAI application (Q2-Q3)
  • ✓ 1 Privacy engineering project (Q3)
  • ✓ 3-5 financial analysis case studies (Q2-Q4)
  • ✓ Philosophy synthesis work (ongoing)

  Frameworks Created

  • ✓ Personal privacy regulations reference guide (Q4)
  • ✓ Startup evaluation framework (Q4)

  Language Goals

  • ✓ Spanish conversational foundation (Q2)
  • ✓ Spanish reading competency (Q4)