Module 1: Advanced Data Structures

Learning Objectives

• Implement advanced data structures
• Understand self-balancing trees
• Master hashing techniques

Topics Covered

• Advanced trees (AVL, Red-Black)
• Heaps and priority queues
• Hash tables and collision handling
• Trie and suffix trees
• Segment trees
• Fenwick trees

Module 2: Algorithm Design Paradigms

Learning Objectives

• Master algorithm design patterns
• Solve complex optimization problems
• Apply mathematical algorithms

Topics Covered

• Advanced dynamic programming
• Graph algorithms
• Network flow
• String algorithms
• Computational geometry
• Number theory algorithms

Module 1: Advanced Data Structures

Learning Objectives

• Implement advanced data structures
• Understand self-balancing trees
• Master hashing techniques

Topics Covered

• Advanced trees (AVL, Red-Black)
• Heaps and priority queues
• Hash tables and collision handling
• Trie and suffix trees
• Segment trees
• Fenwick trees

Module 2: Algorithm Design Paradigms

Learning Objectives

• Master algorithm design patterns
• Solve complex optimization problems
• Apply mathematical algorithms

Topics Covered

• Advanced dynamic programming
• Graph algorithms
• Network flow
• String algorithms
• Computational geometry
• Number theory algorithms

Module 3: System Design and Scalability

Learning Objectives

• Design scalable systems
• Understand distributed systems
• Apply system design patterns

Topics Covered

• System design fundamentals
• Scalability patterns
• Database design
• Caching strategies
• Load balancing
• Microservices architecture

Module 4: Interview Mastery

Learning Objectives

• Excel in technical interviews
• Develop soft skills
• Build professional network

Topics Covered

• Company-specific preparation
• Mock interviews
• Behavioral interviews
• Negotiation skills
• Portfolio development
• Industry networking