advanced-git
Advanced Git - interactive rebase, cherry-pick, bisect, reflog, and power user operations
branching
Git branching strategies - create, switch, merge, rebase, and workflows
git-basics
Git fundamentals - init, add, commit, status, log, and core concepts
git-intro
Introduction to Git version control - what, why, and first steps
collaboration
Team collaboration - remote, fetch, pull, push, clone, and team workflows
basic-workflow
Daily Git workflow - add, commit, push, pull cycle for everyday development
github-features
GitHub platform features - PRs, issues, actions, projects, and automation
rag-exploitation
Attack techniques for Retrieval-Augmented Generation systems including knowledge base poisoning
benchmark-datasets
Standard datasets and benchmarks for evaluating AI security, robustness, and safety
data-poisoning
Test AI training pipelines for data poisoning vulnerabilities and backdoor injection
adversarial-examples
Generate adversarial inputs, edge cases, and boundary test payloads for stress-testing LLM robustness
adversarial-training
Defensive techniques using adversarial examples to improve model robustness and security
certifications-training
Professional certifications, CTF competitions, and training resources for AI security practitioners
infrastructure-security
Securing AI/ML infrastructure including model storage, API endpoints, and compute resources
model-extraction
Techniques to extract model weights, architecture, and training data through API queries
automated-testing
CI/CD integration and automation frameworks for continuous AI security testing
code-injection
Test AI systems for code injection vulnerabilities including prompt-to-code attacks and agent exploitation
continuous-monitoring
Real-time monitoring and detection of adversarial attacks and model drift in production
defense-implementation
Implement mitigations, create input filters, design output guards, and build defensive prompting for LLM security
input-output-guardrails
Implementing safety filters, content moderation, and guardrails for AI system inputs and outputs
llm-jailbreaking
Advanced LLM jailbreaking techniques, safety mechanism bypass strategies, and constraint circumvention methods
model-inversion
Privacy attacks to extract training data and sensitive information from AI models
prompt-hacking
Advanced prompt manipulation including direct attacks, indirect injection, and multi-turn exploitation
prompt-injection-testing
Master prompt injection attacks, jailbreak techniques, input manipulation, and payload crafting for LLM security testing
red-team-frameworks
Tools and frameworks for AI red teaming including PyRIT, garak, Counterfit, and custom attack automation
red-team-reporting
Professional security report generation, executive summaries, finding documentation, and remediation tracking
responsible-disclosure
Ethical vulnerability reporting, coordinated disclosure, and bug bounty participation for AI systems
safety-filter-bypass
Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment
secure-deployment
Security best practices for deploying AI/ML models to production environments
security-testing
Comprehensive security testing automation for AI/ML systems with CI/CD integration
testing-methodologies
Structured approaches for AI security testing including threat modeling, penetration testing, and red team operations
vulnerability-discovery
Systematic vulnerability finding, threat modeling, and attack surface analysis for AI/LLM security assessments
ui
XML layouts, ConstraintLayout, Jetpack Compose, Material Design 3.
architecture
MVVM pattern, Clean Architecture, Repository pattern, dependency injection, SOLID principles.
data
Room ORM, SQLite, SharedPreferences, DataStore, encryption.
fundamentals
Master Kotlin syntax, OOP principles, SOLID practices, functional programming, and data structures.
networking
Retrofit, OkHttp, REST APIs, JSON serialization, network security.
platform
Android core components lifecycle, Activities, Fragments, Services, Intent system.
production
Unit testing, performance optimization, security implementation, Play Store deployment.
api-design
Design and build professional APIs with REST, GraphQL, and gRPC. Master authentication, documentation, testing, and operational concerns.
architecture
Master architectural design with SOLID principles, design patterns, microservices, and event-driven systems. Learn to design scalable backend systems.
authentication
Backend authentication and authorization patterns. JWT, OAuth2, session management, RBAC, and secure token handling.
languages
Master programming languages for backend development. Learn language selection, fundamentals, and ecosystem for JavaScript, Python, Go, Java, C#, PHP, Ruby, and Rust.
performance
Optimize application performance through caching strategies, load balancing, database scaling, and monitoring. Build systems handling thousands of concurrent users.
observability
Logging, metrics, and distributed tracing. OpenTelemetry, Prometheus, Grafana, and production debugging.
devops
Deploy applications with Docker and Kubernetes, automate with CI/CD, manage infrastructure with code, and configure cloud platforms and networking.
databases
Master relational and NoSQL databases. Learn PostgreSQL, MySQL, MongoDB, Redis, and other technologies for data persistence, optimization, and scaling.
messaging
Message queues and event-driven backend architecture. RabbitMQ, Kafka, pub/sub patterns, and async communication.
microservices
Microservices architecture patterns and best practices. Service decomposition, inter-service communication, and distributed data management.
security
Secure backend applications against OWASP threats. Implement authentication, encryption, scanning, compliance, and incident response procedures.
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