Here's how you can excel in the age of automation with your skills in Algorithms.

Exactly, the basis of getting good at algorithms is by learning the basics right. The basics of programming language (selection - variables, decision - if and switch and repetition - loops) follow by the basics of algorithms itself learning various brute force algorithms of the basic search and sort algorithm. Learning binary search, selection search, bubble sort, find uniques are all basics that are required to be good in algorithmic problems.

If you want to excel in Data Structures and Algorithms, you need to excel in your basics and critical thinking. These two methods help you to understand algorithms in detail which is important to come up with an optimized approach to solve a problem.

Data Structures: Arrays: Understand how to store and manipulate collections of data in a fixed-size structure. Linked Lists: Learn about dynamic data structures that allow for efficient insertions and deletions. Stacks and Queues: Grasp the principles of Last-In-First-Out (LIFO) and First-In-First-Out (FIFO) operations. Trees and Graphs: Explore hierarchical data structures and the relationships between nodes. Hash Tables: Familiarize yourself with key-value pairs for efficient data retrieval.

From my perspective, recognizing algorithmic patterns like recursion, dynamic programming, and the greedy approach has been crucial. These patterns provide a set of strategies that I can apply to various problems. By identifying when and how to use each pattern, I can approach complex challenges more systematically and confidently. This skill is particularly useful in automation, where algorithms must be adaptable and robust without constant human input.

Patterns like BFS, Recursion, Kadens Algorithm, and Dynamic Programming help a lot to excel in Algorithms. These patterns reduces you LOC and also optimizes your code.

Control Flow: Conditional Statements (if/else): Use conditions to control the execution of code blocks. Loops (for, while): Iterate over collections or execute code repeatedly based on conditions. Recursion: Understand how functions can call themselves to solve problems.

It doesn't matter how much you code, what matters is how you code. Solving 1000+ questions on Geeks for geeks without actually trying it on your own is not worth it, else its better to solve 200+ questions with your thinking and algorithms.

Building Blocks: Foundation for Complexity: Fundamental concepts are the basis for understanding more complex algorithms and data structures. Efficient Problem Solving: Mastery of basics allows for more effective problem analysis and solution development.

As mentioned above, it doesn't matter how much you code, what matters is how you code. Optimized code can be achieved through critical thinking. Try to have you code with complexity less than O(n^2). First of all start with a brute force, you may not get optimized code at first but it will help you to understand the problem.

Identify Patterns: Recognize common algorithmic patterns and apply appropriate solutions. Break Down Problems: Decompose complex problems into simpler, manageable components using fundamental concepts.

You need to build a curious mindset to excel in Algorithms as curiosity exposes you to creativity and innovations which are important to excel in problem-solving. Try to come with different approaches to solve a problem like using stack to solve a problem then going for heap and recursion for same problem