Introduction to Competitive Programming

• What is competitive programming?
• Benefits and importance of competitive programming
• Overview of popular coding platforms and competitions

Java Language Refresher

• Review of fundamental Java concepts and syntax
• Understanding data types, variables, and control structures in Java
• Recap of Java features relevant to competitive programming

Input and Output Techniques

• Efficient input/output methods in Java
• Handling standard input/output streams
• Using file input/output for large test cases

Time and Space Complexity Analysis

• Understanding time and space complexity
• Big O notation and its significance
• Analyzing the complexity of algorithms and data structures

Data Structures

• Array manipulation and searching
• Stack, queue, and deque operations
• Linked lists and their variations
• Trees (binary tree, binary search tree, segment tree, etc.)
• Graph representation and traversal techniques

Sorting and Searching Algorithms

• Implementing various sorting algorithms (selection sort, insertion sort, merge sort, quicksort, etc.)
• Binary search and its variations
• Efficient searching techniques (hashing, binary search trees)

Dynamic Programming

• Understanding the concept of dynamic programming
• Solving problems using dynamic programming techniques
• Memoization and tabulation approaches

Greedy Algorithms

• Overview of greedy algorithm paradigm
• Identifying and solving problems using greedy strategies
• Implementing greedy algorithms effectively

Graph Algorithms

• Graph traversal algorithms (BFS, DFS)
• Shortest path algorithms (Dijkstra's algorithm, Bellman-Ford algorithm)
• Minimum spanning tree algorithms (Prim's algorithm, Kruskal's algorithm)
• Topological sorting and strongly connected components

Number Theory and Combinatorics

• Prime numbers and prime factorization
• Modular arithmetic and number theory algorithms
• Permutations and combinations
• Probability and counting techniques

String Algorithms

• String manipulation and matching algorithms
• Pattern searching (KMP algorithm, Rabin-Karp algorithm)
• String compression and decompression

Advanced Topics (optional)

• Advanced data structures (trie, segment tree, Fenwick tree)
• Computational geometry algorithms
• Game theory and dynamic programming
• Network flows and maximum flow algorithms

Problem Solving Strategies

• Problem-solving techniques and approaches
• Breaking down problems into smaller subproblems
• Implementing efficient algorithms and optimizing solutions

Contest Strategies and Tips

• Effective contest participation strategies
• Time management and problem prioritization
• Debugging and handling test cases during contests