Series
Ordered post sequences, grouped by topic.
System Design
1
Backend system design scope
2 Designing RESTful APIs
3 Authentication and session management
4 Database design for backend systems
5 Caching in backend systems
6 Background jobs and task queues
7 File upload and storage
8 Search integration
9 Email and notification delivery
10 Webhooks: design and security
11 Payments integration
12 Multi-tenancy patterns
13 Backend for Frontend (BFF) pattern
14 GraphQL server design
15 gRPC and internal service APIs
1
Design a URL shortener
2 Design a key-value store
3 Design a rate limiter
4 Design a web crawler
5 Design a notification system
6 Design a news feed
7 Design a chat application
8 Design a video streaming platform
9 Design a music streaming service
10 Design a ride-sharing service
11 Design a food delivery platform
12 Design a hotel booking platform
13 Design a search engine
14 Design a distributed message queue
15 Design a code deployment system
16 Design a payments platform
17 Design an ad click aggregation system
18 Design a distributed cache
1
What frontend system design covers
2 Rendering strategies: CSR, SSR, SSG, ISR
3 Performance fundamentals: Core Web Vitals
4 Loading performance and resource optimization
5 State management at scale
6 Component architecture and design systems
7 Client-side caching and offline support
8 Real-time on the frontend
9 Frontend security
10 Scalability for frontend systems
11 Accessibility as a system design concern
12 Monitoring and observability for frontends
1
Monolith vs microservices
2 Microservice communication patterns
3 Service discovery and registration
4 Event-driven architecture
5 Distributed data patterns
6 Caching architecture patterns
7 Search architecture
8 Storage systems at scale
9 Notification systems
10 Real-time systems architecture
11 Batch and stream processing
12 Multi-region and global systems
1
Introduction to low level design
2 SOLID principles
3 Design patterns: Creational
4 Design patterns: Structural
5 Design patterns: Behavioral
6 Designing a parking lot
7 Designing a library management system
8 Designing an elevator system
9 Designing a hotel booking system
10 Designing a ride-sharing model
11 Designing a rate limiter
12 Designing a logging framework
13 Designing a notification system
14 API design and contract-first development
15 Data modeling for system design
1
What is system design and why it matters
2 Estimations and back-of-envelope calculations
3 Scalability: vertical vs horizontal scaling
4 CAP theorem and distributed system tradeoffs
5 Consistency models
6 Load balancing
7 Caching: strategies and patterns
8 Content Delivery Networks
9 Databases: SQL vs NoSQL and when to use each
10 Database replication
11 Database sharding and partitioning
12 Consistent hashing
13 Message queues and event streaming
14 API design: REST, GraphQL, gRPC
15 Rate limiting and throttling
16 Proxies: forward and reverse
17 Networking concepts for system design
18 Reliability patterns: timeouts, retries, circuit breakers
19 Observability: logging, metrics, tracing
20 Security in system design
DevOps
1
Cloud fundamentals and the shared responsibility model
2 Compute: VMs, containers, serverless
3 Networking in the cloud
4 Cloud storage services
5 Managed databases in the cloud
6 Cloud IAM and access control
7 Serverless architecture patterns
8 Cloud cost management
9 Multi-cloud and cloud-agnostic design
10 Cloud Well-Architected Framework
1
What DevOps actually is
2 The software delivery lifecycle
3 Agile, Scrum, and Kanban for DevOps teams
4 Trunk-based development and branching strategies
5 Environments and promotion strategies
6 Configuration management
7 Secrets management
8 Deployment strategies
9 On-call culture and incident management
10 DevOps metrics and measuring maturity
1
Why Kubernetes exists
2 Kubernetes architecture
3 Core Kubernetes objects
4 Kubernetes networking
5 Storage in Kubernetes
6 Kubernetes configuration and secrets
7 Resource management and autoscaling
8 Kubernetes workload types
9 Kubernetes observability
10 Kubernetes security
11 Helm and package management
12 GitOps with ArgoCD
13 Kubernetes cluster operations
14 Service mesh concepts
1
What SRE is
2 Reliability fundamentals
3 SLIs, SLOs, and error budgets in practice
4 Toil reduction and automation
5 Capacity planning
6 Performance testing and load testing
7 Chaos engineering
8 Incident response in practice
9 Postmortems and learning from failure
10 Production readiness reviews
11 Reliability patterns for services
GPU Programming
1
How a CPU actually works: cores, clocks, and execution
2 CPU caches and memory hierarchy: why memory access speed matters
3 CPU pipelines and instruction-level parallelism
4 Memory models and why concurrent CPU code is hard
5 SIMD and vectorization: parallelism on a single CPU core
6 Processes, threads, and context switching
1
GPUs: from pixels to parallel supercomputers
2 Your first CUDA program: kernels, threads, and grids
3 Thread hierarchy in CUDA: threads, blocks, warps, and grids
4 Warps and warp divergence: the hidden performance trap
5 CUDA memory hierarchy: where your data lives matters
6 Memory coalescing: the most important optimization you will learn
7 Shared memory and tiling: the key to fast matrix operations
8 Debugging and profiling CUDA programs
9 Device functions, host functions, and CUDA function qualifiers
10 Synchronization and atomic operations in CUDA
11 Parallel prefix sum and reduction: the core parallel primitives
12 Concurrent data structures on the GPU
13 CUDA streams and asynchronous execution
14 CUDA events and fine-grained synchronization
15 Dynamic parallelism: kernels launching kernels
16 Unified virtual memory: one pointer for CPU and GPU
17 Multi-GPU programming and peer access
18 Memory allocation patterns and multi-dimensional arrays in CUDA
19 Texture and constant memory: specialized caches
20 Occupancy, register pressure, and performance tuning
21 Case study: matrix multiplication from naive to cuBLAS speed
22 Case study: implementing a convolution layer in CUDA
23 Case study: reduction and histogram at scale
24 Heterogeneous computing: CPU and GPU working together
25 Advanced memory patterns: pinned memory, zero-copy, and more
26 Advanced stream patterns and concurrent kernel execution
27 Performance case studies and optimization patterns
28 Where to go from here: CUDA ecosystem and next steps
Cybersecurity
1
How attackers think: the attacker mindset
2 Networking fundamentals for security
3 Cryptography fundamentals
4 Public key infrastructure and certificates
5 Authentication and authorization
6 Web application security: OWASP Top 10
7 Network attacks and defenses
8 Linux privilege escalation
9 Windows security fundamentals
10 Malware types and analysis basics
11 Reconnaissance and OSINT
12 Exploitation basics and CVEs
13 Post-exploitation and persistence
14 Defensive security: hardening and monitoring
15 Incident response
16 CTF skills and practice labs
Deep Learning
1
Neural networks: the basic building block
2 Forward pass and backpropagation
3 Training neural networks: a practical guide
4 Convolutional neural networks
5 Recurrent neural networks and LSTMs
6 Attention mechanism and transformers
7 Word embeddings: from one-hot to dense representations
8 Transfer learning and fine-tuning
9 Optimization techniques for deep networks
10 Regularization for deep networks
11 Encoder-decoder architectures
12 Generative models: an overview
13 Restricted Boltzmann Machines
14 Deep Belief Networks
15 Variational Autoencoders
16 Generative Adversarial Networks: training and theory
17 DCGAN, conditional GANs, and GAN variants
18 Representation learning and self-supervised learning
19 Domain adaptation and fine-tuning strategies
20 Distributed representations and latent spaces
21 AutoML and hyperparameter optimization
22 Neural architecture search
23 Network compression and efficient inference
24 Graph neural networks
25 Practical deep learning: debugging and tuning
Linux
1
What is Linux and how it differs from other OSes
2 Installing Linux and setting up your environment
3 The Linux filesystem explained
4 Users, groups, and permissions
5 Essential command line tools
6 Shell scripting fundamentals
7 Processes and job control
8 Standard I/O, pipes, and redirection
9 The Linux networking stack
10 Package management and software installation
11 Disk management and filesystems
12 Logs and system monitoring
13 SSH and remote access
14 Cron jobs and task scheduling
15 Linux security basics for sysadmins
Maths for ML
1
Why Maths Matters for ML: A Practical Overview
2 Scalars, Vectors, and Vector Spaces
3 Matrices and Matrix Operations
4 Matrix Inverses and Systems of Linear Equations
5 Eigenvalues and Eigenvectors
6 Matrix Decompositions: LU, QR, SVD
7 Norms, Distances, and Similarity
8 Calculus Review: Derivatives and the Chain Rule
9 Partial Derivatives and Gradients
10 The Jacobian and Hessian Matrices
11 Taylor series and local approximations
12 Probability fundamentals
13 Random variables and distributions
14 Bayes theorem and its role in ML
15 Information theory: entropy, KL divergence, cross-entropy
Machine Learning
1
What is machine learning: a map of the field
2 Data, features, and the ML pipeline
3 Linear regression
4 Bias, variance, and the tradeoff
5 Regularization: Ridge, Lasso, and ElasticNet
6 Logistic regression and classification
7 Evaluation metrics for classification
8 Naive Bayes classifier
9 K-Nearest Neighbors
10 Decision trees
11 Ensemble methods: Bagging and Random Forests
12 Boosting: AdaBoost and Gradient Boosting
13 Support Vector Machines
14 K-Means clustering
15 Dimensionality Reduction: PCA
16 Gaussian mixture models and EM algorithm
17 Model selection and cross-validation
18 Feature engineering and selection
ML Optimization
1
What is optimization and why ML needs it
2 Convex sets and convex functions
3 Optimality conditions: first order
4 Optimality conditions: second order
5 Line search methods
6 Least squares: the closed-form solution
7 Steepest descent (gradient descent)
8 Newton's method for optimization
9 Quasi-Newton methods: BFGS and L-BFGS
10 Conjugate gradient methods
11 Constrained optimization and Lagrangian duality
12 KKT conditions
13 Penalty and barrier methods
14 Interior point methods
15 The simplex method
16 Frank-Wolfe method
17 Optimization in dynamic programming and optimal control
18 Stochastic gradient descent and variants