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)
4. Philosophy & Humanities
5. Privacy Engineering & Cybersecurity

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: 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)

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)

Resources

• Books: As listed above
• 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: Privacy Engineering & Cybersecurity

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 Certification — Data Protocol (Nishant Bhajaria & Engin Bozdag); 8 courses, 6 hands-on labs, covers data governance, anonymization, consent management, DSAR, privacy-by-design; 6–8 hours self-paced
• 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 for security tools and implementations (Stream 3)
• Connect privacy engineering to philosophical questions about surveillance, identity, autonomy (Stream 4)

Practical Projects: Security & Networking

Ten progressive projects from foundational to intermediate, aligned with Stream 6 and the first half of the year.

Networking Projects (Foundations)

Project 1: Network Traffic Analyzer with Wireshark

What you’ll learn: Protocols (TCP/IP, HTTP, DNS), packet analysis, troubleshooting.

• Capture traffic while browsing the web
• Identify HTTP requests, DNS queries, TCP handshake
• Analyze a TLS/HTTPS session
• Document the protocols found

Deliverable: Report with screenshots showing 5+ different protocols and explanation of each

Project 2: Virtual Network Lab (VirtualBox/VMware)

What you’ll learn: Network configuration, VLANs, basic routing, isolation.

• Create 3–4 VMs (Ubuntu/Debian)
• Configure different network modes (NAT, Host-Only, Bridge)
• Ping between VMs
• Set up a web server on one VM and access it from another
• Implement network segmentation

Deliverable: Network diagram + configuration documentation

Project 3: Secure Web Server with NGINX

What you’ll learn: Web servers, HTTPS/TLS, SSL certificates, reverse proxy.

• Install NGINX on a Linux VM
• Configure a simple static site
• Obtain an SSL certificate (Let’s Encrypt or self-signed)
• Implement HTTP → HTTPS redirect
• Configure security headers (HSTS, X-Frame-Options)

Deliverable: Functional HTTPS site + configuration documentation

Project 4: Network Scanner in Python

What you’ll learn: Sockets, port scanning, network discovery, network programming.

• TCP connect scan for open ports on an IP
• Detect common services (HTTP:80, HTTPS:443, SSH:22)
• Ping sweep across a subnet
• Generate a report of active hosts

Deliverable: Working Python script + scan report of local network

Security Projects (Foundations)

Project 5: Secure Authentication System

What you’ll learn: Hashing, salting, password storage, authentication.

• Build a simple web app (Flask/Python or Node.js)
• Implement user registration with bcrypt or Argon2 password hashing
• Login endpoint with protection against timing attacks
• Add rate limiting
• Optional: 2FA with TOTP

Deliverable: Web app with secure authentication + documentation of security choices

Project 6: Cryptography CLI Tool

What you’ll learn: Symmetric/asymmetric cryptography, AES, RSA, key management.

• Encrypt/decrypt files using AES-256
• Generate RSA key pairs
• Encrypt AES key with RSA (hybrid encryption)
• Implement digital signatures
• Secure key management

Deliverable: Functional CLI tool + usage documentation

Project 7: Home Firewall with pfSense/iptables

What you’ll learn: Firewalls, filtering rules, IDS/IPS, network security.

• Install pfSense in a VM or configure iptables on Linux
• Set up two networks (simulated LAN and DMZ)
• Create firewall rules: block malicious traffic, allow only necessary ports, log connection attempts
• Configure Snort or Suricata (IDS)
• Test with Nmap

Deliverable: Documented configuration + block logs + network diagram

Project 8: Web App Vulnerability Scanner

What you’ll learn: OWASP Top 10, web security, SQL injection, XSS.

• Use DVWA or WebGoat as a target
• Write Python scripts to detect: SQL Injection, reflected and stored XSS, directory traversal, missing security headers
• Generate a vulnerability report

Deliverable: Automated scanner + vulnerability report

Integrated Projects (Networking + Security)

Project 9: SSH Honeypot

What you’ll learn: Intrusion detection, logging, attack analysis, SSH.

• Set up Cowrie as an SSH honeypot on a non-standard port or isolated VM
• Monitor and log login attempts
• Analyze attacker IPs, most-tried passwords, commands executed
• Visualize data with charts

Deliverable: Configured honeypot + attack analysis report (7–14 days of data)

Project 10: Network Monitoring System (Basic SIEM)

What you’ll learn: Log management, SIEM, anomaly detection, dashboards.

• Deploy ELK Stack (Elasticsearch, Logstash, Kibana) or Graylog
• Collect logs from: NGINX/Apache, firewall (pfSense/iptables), OS auth logs
• Build Kibana dashboards: failed login attempts, HTTP traffic by country, security alerts
• Configure basic alerting

Deliverable: Functional SIEM with dashboards + documentation

Suggested Implementation Roadmap

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
  • Philosophy: 3 books completed

  Action: Assess certification pace, adjust Q2 technical load

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  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)
  • GenAI project initiated
  • Philosophy: 6 books completed total

  Action: Plan Q3 project focus (privacy engineering, GenAI)

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  Q3 2026 Review (Late September)

  Completed:

  • GenAI project advancing
  • Privacy engineering project completed
  • Architecture book series started
  • Advanced privacy technologies studied (ZKPs, TEEs, Digital ID)
  • Philosophy: 9 books completed total

  Action: Plan Q4 refinement and documentation phase

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  Q4 2026 Review (Late December)

  Completed:

  • GenAI project documented
  • Privacy engineering portfolio piece completed
  • Book club year concluded (12 philosophy books)
  • Personal privacy regulations reference guide completed

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

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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)

  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)

  Projects Delivered

  • ✓ 1 GenAI application (Q2-Q3)
  • ✓ 1 Privacy engineering project (Q3)
  • ✓ Philosophy synthesis work (ongoing)

  Frameworks Created

  • ✓ Personal privacy regulations reference guide (Q4)