During your coding tests and technical interviews, you’ll be tested on Data Structures & Algorithms. This is EXTREMELY important, as if you’re unable tackle coding challenges, you will be unable to progress through the application process. They are fairly tough to learn, especially if you don’t have a background in computer science, however with enough time and practice, you’ll have a strong grasp with the concepts.
Data Structures: #
What are they?
At its core, a data structure is a way to organize and store data in a computer so that it can be accessed and modified efficiently. Think of it like different types of containers for your stuff. Some containers are better suited for certain tasks than others.
Common Data Structures:
- Arrays: Like a shelf where you store books in a row. You can quickly grab a book if you know its position on the shelf.
- Linked Lists: Imagine a treasure hunt where each clue (or item) points to the next one.
- Stacks: Think of a stack of plates. You add (push) or remove (pop) plates from the top.
- Queues: Picture a line (queue) of people waiting for a bus. The first one in line gets on the bus first.
- Trees: Like a family tree, but it can branch out in many directions.
- Hash Tables: Like a super-efficient librarian that knows exactly where to find a book based on its title.
Algorithms: #
What are they?
An algorithm is a set of step-by-step instructions to solve a particular problem. It’s like a recipe in a cookbook. Just as there are many ways to bake a cake, there are many algorithms to solve a problem. Some are faster or more efficient than others.
Why are they important in coding tests?
In technical interviews, companies want to see if you can solve problems efficiently. They’re not just looking for any solution—they’re looking for the best one. That’s where algorithms come in.
Common Algorithmic Concepts:
- Sorting: Imagine you have a deck of shuffled cards, and you need to arrange them in order. Sorting algorithms help do that with data.
- Searching: Finding a specific item in a data structure. Like looking for a friend’s name in a phonebook.
- Recursion: A function that calls itself to break down a problem into smaller chunks. It’s like a Russian doll, where opening one reveals another.
- Dynamic Programming: Breaking down a big problem into smaller, more manageable sub-problems and solving each only once, saving time.