Each session will be 30 minutes and structured as follows:

1. Introduction (2–3 minutes):

• Quick overview of the day's topic.
• Connection to real-world applications or coding challenges.

2. Main Talk (20–25 minutes):

• Deep dive into the algorithm or concept of the day.
• Structure of the Talk:

1. Concept Explanation: Definitions and theory.
2. Illustrative Example: Step-by-step breakdown of an algorithm with visuals.
3. Applications: Use cases in tech, such as search engines, AI, or gaming.

3. Q&A & Wrap-Up (3–5 minutes):

• Answer audience questions.
• Provide links to resources for further learning.

Weekly Topics

Week 1: Introduction to Algorithms

• What are algorithms, and why do we need them?
• Example: Binary Search and its real-world uses.

Week 2: Sorting Algorithms

• Overview of common sorting techniques (e.g., Merge Sort, Quick Sort).
• Example: Visualizing Merge Sort step-by-step.

Week 3: Graph Algorithms

• Understanding graphs and their importance.
• Example: Breadth-First Search (BFS) for shortest path problems.

Week 4: Dynamic Programming (DP)

• Breaking down complex problems into simpler sub-problems.
• Example: Solving the Fibonacci problem using DP.

Week 5: Greedy Algorithms

• How to make optimal choices step-by-step.
• Example: Activity Selection Problem.

Week 6: Divide and Conquer

• Solving problems by dividing them into smaller sub-problems.
• Example: Maximum Subarray Problem.

https://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/