. Data Structures & Algorithms Topics to cover: Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Heaps, Hash Tables, Tries. Algorithmic Techniques: Sorting, Searching, Dynamic Programming, Divide & Conquer, Greedy Algorithms, Backtracking. Complexity Analysis: Time and Space complexity (Big O notation). 2. Cloud Cloud Concepts: Cloud computing models (IaaS, PaaS, SaaS), Cloud providers (AWS, Azure, Google Cloud). Services: EC2, Lambda, S3, RDS, CloudFormation, CDK, Kubernetes. Deployment & Scalability: Autoscaling, Load balancing, Containers, Serverless architecture, CI/CD pipelines. 3. System Design Core Topics: High-level design, Low-level design, Designing scalable systems, Distributed systems, CAP theorem, Consistency, Availability, Partition tolerance. Architecture Patterns: Microservices, Monolithic, Event-driven architecture, CQRS. Tools: Databases (SQL, NoSQL), Caching (Redis, Memcached), Message Queues (Kafka, RabbitMQ). 4. Scalability Vertical vs Horizontal Scaling: When to use each approach. Load Balancing: Types (Round-robin, Weighted, etc.), Algorithms. Caching: Distributed caching systems, Strategies like cache eviction policies, Cache-aside pattern. 5. Behavioral Interview STAR Method: Situation, Task, Action, Result framework for answering questions. Leadership Qualities: Conflict resolution, Team collaboration, Problem-solving approach.