Building reliable and highly performant software requires knowledge that goes beyond a certain programming language or framework. It requires a solid understanding of how data is organized in memory, how it can be manipulated, sorted or searched into. There’s a reason why all the big tech companies such as Google, Amazon or Netflix focus their technical interviews on those topics. Whether you do mobile apps, websites, games, machine learning or any other work that involves coding, you need a good grasp of Data Structures and Algorithms.

    Many self taught developers and aspiring engineers often feel they lack the knowledge when having to decide on the right data structure or the right approach for solving a problem. If you ever felt that way, this material is the right choice for you. This course packs months of Computer Science subject matter to get you on the same level of proficiency as someone with a Computer Science degree.

What sets us apart ?

    Every video begins with an in depth analysis of the topic at hand. At this stage we won’t write any code yet, but rather learn how to approach the problem, think of ways we could solve it and build a mental model of the solution.

    We then go on to code the algorithm step by step. But we don’t stop there. We take one or more examples and walk through the code line by line. And we mean that literally. You will see how the code runs from top to bottom and how data flows and changes during execution. We find this method the absolute best way to really understand the inner workings of an algorithm.

    We’ll also analyze the time performance and space utilization of every algorithm and method we write using the Big O Notation. We’ll talk about the strengths and weaknesses of each data structure and discuss their real world usage. Apart from all of that, you’ll also learn things like recursion, how computers work under the hood, problem solving techniques, common programming patterns and much more.

What does this course cover ?

• How computers work under the hood

• What a data structure is

• What an algorithm is

• Problem solving techniques

• Big O Notation - how to analyze the time performance and space utilization of algorithms. This is done for every single function/algorithm we write.

• Gain a deeper understanding of how code works

• Recursion

   

Data Structures:

• Arrays

• Hash Tables

• Singly Linked Lists

• Doubly Linked Lists

• Stacks

• Queues

• Binary Search Trees

• Tree Traversal

• Heaps

• Graphs

   

Sorting Algorithms:

• Insertion Sort

• Selection Sort

• Bubble Sort

• Shell Sort

• Heap Sort

• Merge Sort

• Quick Sort

• Radix Sort

Thanks for considering, and I hope this course will help you in your journey. Happy learning!