← Back to Home
Code-Alongs for Unit 7 Sprint 27
Graphs Recommendation Code-Along
Practice implementing graph data structures and algorithms to build a recommendation system. You'll learn how to represent graphs in code, traverse them using BFS and DFS, and identify cycles and paths in the graph structure.
Key Learning Objectives
- Assemble a graph from provided relationships between items
- Implement both breadth-first and depth-first traversal algorithms
- Identify cycles in a graph to avoid infinite recommendations
- Apply graph traversal to find the shortest path between items
- Build a product recommendation system based on graph relationships
View on GitHub
Database Normalization Code-Along
Explore the principles of database normalization and learn how to design efficient database schemas. This code-along walks you through the process of normalizing a database to reduce redundancy, eliminate anomalies, and ensure data integrity.
Key Learning Objectives
- Identify unnormalized data and associated problems in a database
- Apply normalization techniques to create properly structured tables
- Design primary key and foreign key relationships between tables
- Ensure referential integrity in a relational database
- Write SQL statements to interact with normalized tables
View on GitHub
RDBMS Associations Code-Along
Learn how to implement various types of associations between database tables, including one-to-one, one-to-many, and many-to-many relationships. You'll practice creating properly structured tables and writing SQL queries to retrieve data across multiple related tables.
Key Learning Objectives
- Design and implement one-to-one, one-to-many, and many-to-many associations
- Create junction tables for many-to-many relationships
- Write inner join SQL statements to retrieve data from multiple tables
- Ensure referential integrity with proper foreign key constraints
- Design an entity relationship diagram (ERD) for a business scenario
View on GitHub
Service Design Patterns Code-Along
Explore common service design patterns and best practices for building scalable and maintainable applications. You'll learn how to identify appropriate design patterns for specific requirements and implement them in a service-oriented architecture.
Key Learning Objectives
- Implement adapter pattern to integrate incompatible interfaces
- Create facade services to simplify complex interactions
- Design proxy services to control access to sensitive resources
- Build an aggregator service to combine data from multiple sources
- Analyze trade-offs between different AWS compute options (Lambda, ECS, EC2)
View on GitHub