Algorithms and data structures are crucial for application performance. This course teaches you tools that you can use to build efficient applications. It starts with an introduction to algorithms and explains bubble, merge, quicksort, and other popular programming patterns. You’ll also learn about data structures such as binary tree, hash table, and graphs. The course progresses to advanced concepts, such as algorithm design paradigms and graph theory. By the end of the course, you will know how to correctly implement common algorithms and data structures within your applications.
- Understand some of the fundamental concepts behind key algorithms
- Express space and time complexities using Big O notation.
- Correctly implement classic sorting algorithms like merge and quicksort, using native Java data structures
- Correctly implement basic and complex data structures (like hash tables and binary trees)
- Learn about different algorithm design paradigms, such as greedy, divide and conquer, and dynamic programming
- Apply powerful string matching techniques and optimize your application logic
- Master graph representations and learn about different graph algorithms, such as cycle detection, traversal, and shortest path
For an optimal student experience, we recommend the following hardware configuration:
- Processor: 2.6 GHz or higher, preferably multi-core
- Memory: 4GB RAM
- Hard disk: 10GB or more
- A projector
- An Internet connection
You’ll also need the following software installed in advance:
- Operating System: Windows (8 or higher).
- Command Prompt or PowerShell on Windows
- Terminal on macOS
- Java SE Development Kit, JDK 8 latest