Computer Science is the study of computation, information, and automation. It explores how data is represented, processed, and communicated through algorithms and software, and how these systems are implemented in hardware and networks. The field spans both theoretical foundations (like logic, complexity, and computability) and practical applications (such as programming, data systems, AI, and cybersecurity), enabling the creation of efficient, secure, and scalable technological solutions.
Theory
- Automata & Formal Languages
- Turing Machines
- Computational Complexity
- Logic & Set Theory
Programming
Languages
- Python
- JavaScript
- C/C++
- Java
Paradigms
- OOP
- Functional
- Procedural
Algorithms & Data Structures
- Sorting Algorithms
- Graph Algorithms
- Trees, Hash Tables, Stacks, Queues
- Big-O Analysis
Systems
Operating Systems
Computer Architecture
Networking
- OSI & TCP Models
- Remote Access (HTTPS, VPN)
- DNS & Routing
- CDN & Edge Computing
Software Engineering
- Design Patterns
- Software Architecture
- Architecture Patterns
- SDLC & Agile
- Testing & Debugging
- Version Control (Git)
Testing & QA
Levels of Testing
- Unit Testing (PyTest, JUnit, Jest)
- Integration Testing
- System & E2E Testing (Selenium, Cypress, Playwright)
Methodologies
- TDD (Test Driven Development)
- BDD (Behavior Driven Development)
Cloud
Providers
Core Services
- Virtual Machines
- Serverless (Lambda, Cloud Functions)
- Load Balancing & Auto Scaling
Databases
- SQL
- RDBMS
- NoSQL
- ER Models & Normalization
- Transactions & ACID
Data
Data Fundamentals
- Structured data
- Unstructured data
- Data Governance
Big Data
- Volume, Velocity, Variety
- Batch vs Stream Processing
- Distributed Computing
Data Platforms
- Hadoop Ecosystem (HDFS, Hive, Pig)
- Apache Spark & Flink1
- Cloud Platforms (Glue, BigQuery, Synapse)
Data Engineering
- ETL / ELT
- Data Lakes vs Warehouses
- Data Quality & Validation
Data Orchestration
- Airflow
- DAGs, Schedulers, Triggers
Data Applications
Business Intelligence
Workflow Orchestration
Security
- Secure Coding Practices
- Key Management & Secrets
- Data Security (PET)
Access Control
- Identity & Access Management (IAM)
- Authentication (MFA, SSO)
- Authorization (RBAC, ABAC, DAC)
Cybersecurity
- Encryption & Hashing
- Threat Modeling & Pentesting
- Cloud Security (ZTN)
- Network Security (FW, VPN, IDS/IPS, Secure Protocols)
Infrastructure & Operations
DevOps
- CD Pipelines
- GitOps
- DevSecOps
- Monitoring & Logging (Prometheus, Grafana, ELK)
Infrastructure as Code (IaC)
- Terraform
- Ansible
- Pulumi
- Cloud Formation / Bicep
Containers
MLOps
- Model Versioning , ML Pipelines, Monitoring & Tracking (Kubeflow, MLflow, DVC)
- Model Deployment (SageMaker, KFServe)
- Feature Stores
Artificial Intelligence
- Algorithms & Techniques
- Machine Learning & Deep Learning
- Generative AI
- NLP & Computer Vision
- AI Agents