Week 1 – Introduction & Kattis Setup

• 🎥 Video lectures:
  • Solve Kattis problem in Kattis editor and in VS Code (Python)
  • Solve Kattis problem in Eclipse (Java)
• 🧩 Example problem: Airfare Grants (Solution)
• 🔗 Additional Resources: Intro slides, Common Kattis Input Patterns
• 📂 Problem set:
  • Metronome
  • Barcelona
  • Cut in Line
  • Hair of the Dog
  • Greedily Increasing Subsequence
• Tip: Go to kattis.com and sort problems by difficulty. Do as many problems as you can in ascending order.

Week 2 – Two Pointer Technique

• 🎥 Mini-lecture: Two Pointer Technique used in mergesort and the two sum problem
• 🧩 Example problem: Merge Sorted Array (Solution)
• 🔗 Additional Resources: Two Pointer Slides
• 📂 Problem set:
  • Merge Sorted Array
  • Two Sum-Input Array Is Sorted
  • Two Sum
  • Valid Palindrome
  • Squares of a Sorted Array
• Tip: For more practice, go to leetcode's official list of Two Pointer problems to practice more problems.

Week 3 – Stacks and Queues

• 🎥 Mini-lecture: Stacks and Queues
• 🧩 Example problem: Bracket Matching (Solution)
• 🧩 Example problem: Eeny Meeny (Solution)
• 🔗 Additional Resources: Stacks and Queues Slides
• 📂 Problem set:
  • This Ain't Your Grandpa's Checkerboard (2D array)
  • Pairing Socks
  • Even up
  • Ferry Loading

Week 4 – Sliding Window

• 🎥 Mini-lecture: Sliding Window Technique
• 🧩 Example problem: Maximum Average Subarray (Solution)
• 🔗 Additional Resources: Sliding Window Slides
• 📂 Problem set:
  • Maximun Average of Subarray of Size k
  • Maximun Number of Vowels in Substring of Given Length
  • Minimum Size Subarray Sum
  • Longest Substring without Repeating Characters

Week 5 – Binary Search and BinaryTrees and Traversals

• 🎥 Mini-lecture:
• 🧩 Example problem: Guess the Number (Solution)
• 🔗 Additional Resources: Binary search and binary trees
• 📂 Problem set:
  • Out of Sorts
  • Ceiling Function

Week 6 – Dynamic Programming I (1D Arrays)

• 🎥 Mini-lecture: DP - coin row and Kadane's algorithm
• 🧩 Example problem: House Robber (Solution)
• 🔗 Slides: Dynamic Programming
• 📂 Problem set (Leetcode):
  • Min Cost Climbing Stairs
  • House Robber II
  • Maximum Subarray Sum

Week 7 – Dynamic Programming II (2D Arrays)

Topic: DP on grids, 2D states, and table-filling patterns.

• 🎥 Mini-lecture: 2D DP tables and transition rules
• 🧩 Example problem: Number of paths in a grid with obstacles
• 📂 **Problem set (Kattis):_
  • Grid path counting or min-cost path
  • Small 2D DP (e.g., edit distance–style problem)

Goals:

• Design a 2D DP state (what does dp[i][j] mean?).
• Handle boundaries and base cases carefully.
• Understand memory and time tradeoffs of 2D DP.

Week 8 – Graphs I (BFS & DFS)

Topic: Core graph algorithms and representations.

• 🎥 Mini-lecture: Adjacency lists, BFS, and DFS
• 🧩 Example problem: Connected components or simple reachability
• 📂 **Problem set (Kattis):_
  • BFS on an unweighted graph
  • DFS for counting components or detecting cycles

Goals:

• Build adjacency lists from input (directed and undirected).
• Choose BFS vs. DFS appropriately.
• Understand how to mark visited nodes and avoid infinite loops.

Week 9 – Graphs II (Shortest Paths & More)

Topic: Weighted graphs and classic shortest path techniques.

• 🎥 Mini-lecture: Dijkstra’s algorithm and common shortest path patterns
• 🧩 Example problem: Shortest path on a weighted graph
• 📂 **Problem set (Kattis):_
  • Dijkstra on a small to medium graph
  • Another graph problem combining ideas from earlier weeks

Goals:

• Recognize when a problem is really a shortest path problem.
• Implement Dijkstra with a priority queue.
• Combine graph insights with earlier techniques (DP, greedy, etc.).