How Much Coding is Required For Placements?

The amount of coding required for placements will depend on the specific job you are applying for. In general, technical roles such as software engineering, data science, or web development will require a significant amount of coding knowledge and experience.

Have you ever seen people on LinkedIn getting placed at big tech companies? Well, If you are here, we will make sure you also post the same. ???

 

Before going directly to how much coding, We should understand the fact that Why Coding?

Many times the student is confused, that Why we need to solve such problems that are of no use, Why do we need to learn DSA or Problem-solving? So the answer to this question is very simple. The organization to which you are going to apply is seeking a candidate who is logically strong and technically sound. They want a person who can implement the fundamentals of computer programming into physical entities and solve real-life problems.

It’s worth noting that some companies may have specific coding languages or frameworks that they use, so it’s a good idea to research the company and its technology stack before applying to ensure you have the necessary skills.

For the same cause, it becomes necessary for an individual to learn coding in order to get placed.

But Don’t worry, to get you placed in your dream company, we are here with a well-planned strategy and valuable resources. If you are a computer science student or want to work in the tech industry, you must be familiar with coding. However, the question here is exactly-

How Much Coding is Required For Placements? 

To prepare for coding interviews and technical assessments, you should have a strong understanding of programming fundamentals, algorithms, data structures, and problem-solving skills. You should also be comfortable with at least one programming language, such as Java, Python, or C++. The journey of your learning starts with a quest that which section of the IT sector you are targeting to get placed in. 

In addition to coding skills, employers may also evaluate your ability to work in a team, communicate effectively, and learn quickly. It’s important to demonstrate these soft skills in addition to your technical abilities.

Majorly there are two types of Companies for Freshers:

1. Service Based 
2. Product Based 

To enter any of the above-mentioned, you have to choose a Programming Language in which you are going to be proficient.

1. Selection of Programming Language

To get started as a Software Developer it is necessary to choose a programming language that seems to be comfortable according to you. The selection of the programming language can be based upon several factors such as – Purpose, Advancement, Future scope, Learning curve, Job preference, and at last Personal preference. 

When selecting a programming language, it’s important to consider your goals and the requirements of your project. Here are some factors to consider when selecting a programming language:

• Purpose: What do you want to build? Different programming languages are better suited for different tasks. For example, if you want to build a mobile app, you might consider Java or Swift. If you want to build a website, you might consider HTML, CSS, and JavaScript.
• Learning curve: How difficult is the language to learn? Some programming languages are easier to learn than others, especially for beginners. For example, Python is often considered an easy-to-learn language, while C++ can be more challenging.
• Community support: How large and active is the community around the language? Programming languages with large communities tend to have more resources, such as documentation, tutorials, and libraries.
• Performance: How fast and efficient is the language? Some programming languages are better suited for high-performance applications, while others are better suited for rapid development.
• Job market: What are the job prospects for the language? Some programming languages are more in demand than others, and knowing a language that’s in high demand can make it easier to find work.

Now, If you are reading this article, we assume that you are familiar with at least one programming language. And if you are still confused, then do visit – Programming Language For Placement – C++, Java, or Python.

2. DSA Concepts 

DSA (Data Structures and Algorithms) is a fundamental topic in computer science and software engineering. It includes the study of various data structures, algorithms, and their applications in solving real-world problems. To build your concepts and strengthen them you can take DSA Self Paced, mentored by Mr. Sandeep Jain (CEO, neveropen) which covers all important concepts of DSA. Also, go through the Complete Roadmap To Learn DSA From Scratch.

 

Learning data structures and algorithms enables us to write efficient and optimized computer programs.

For Service-Based Companies:

1. Arrays

In DSA we will start with arrays. Arrays are the building block of Data structures and algorithms. You must solve at least 30-40 questions on arrays. You might think these are a lot of questions, but they aren’t. It will help you if you make your concepts strong in an array because it is used almost everywhere. You must thoroughly practice logical questions from the array.

Sample Questions: 

• Program to Reverse the Array
• Find a Peak Element that is Not Smaller than its Neighbors
• Find the Kth Largest and Kth Smallest Number in an Array
• Write a Program to Sort the Given Array
• Write a Program to Sort an Array of 0s, 1s, and 2s
• Trapping Rain Water

To Practice, more questions on Array, refer to Array GFG Practice.

2. Strings

The next most important topic is Strings. You should practice at least 30-40 questions in order to grasp the concept in a good manner. If you are thinking by doing only some specific or standard questions, you will be able to crack the placement, then it is a clear myth as the placement requires your thought process and problem-solving techniques.

Sample Questions: 

• Program to Check Whether the Number is Palindrome or Not
• Longest Valid Parenthesis
• Check Whether Two Strings are Anagrams of Each Other
• Write a Program to Print all Permutations of a Given String

To Practice, more questions on Strings, refer to String GFG Practice.

3. Recursion

Next comes – Recursion. It is one of the most important topics because it has many use cases like LinkedList, graph, DP, etc. You should understand Recursion well and you have to solve 30-40 problems in order to make a strong grip on recursion. Why only 20-25 questions, as recursion is used in further concepts as well so there you can learn more about it?

Sample Questions:

• Program to Calculate pow(x, n)
• Print Sums of All Subsets of a Given Set
• Program for Tower of Hanoi Algorithm
• Print all Non-Increasing Sequences of a Sum Equal to a Given Number x
• Find Ways an Integer can be Expressed as the Sum of the n-th Power of Unique Natural Numbers
• Recaman’s Sequence

To Practice, more questions on Recursion, refer to Recursion GFG Practice

4. Linked List

After recursion, you may now jump to the LinkedList. Here, you will learn about dynamic memory allocation. Linked lists will be very useful in trees. About the questions, you must solve 30-40 questions.

Sample Questions:

• Print the Middle of a Given Linked List
• Flattening a Linked List
• Detect Loop in a Linked List
• Remove Duplicate Elements From the Sorted Linked List
• Rotate a Linked List
• Delete the Last Occurrence of an Item From the Linked List
• Delete the Elements in a Linked List Whose Sum is Equal to Zero

To Practice, more questions on Linked List, refer to Linked List GFG Practice

5. Stack and Queues

The next comes – Stack and Queues. You must solve 20 questions on each topic. You should also know the application of Stack and Queues. You will use these concepts in the future as well, so better you do it in a better way. You must understand how Stack and Queue are created.

Sample Questions:

• Reverse a Stack Using Recursion
• Sort a Stack Using Recursion
• Sort a Stack Using a Temporary Stack
• Reverse a Stack Without Using Extra Space In O(N)
• Delete The Middle Element of a Stack
• Sorting an Array Using Stacks
• Delete Array Elements That Are Smaller Than The Next Or Become Smaller
• Check If a Queue Can Be Sorted Into Another Queue Using a Stack
• Reverse Individual Words
• Count Subarrays Where The Second Highest Lies Before The Highest
• Check If an Array is Stack Sortable

To Practice, more questions on Stack and Queues, refer to Stack and Queues GFG Practice

6. Hashing

Hashing is again a must-go-through topic when it comes to learning DSA. Like other topics, it is also an important topic. You must understand its working, its complexities, and its usage in programming. It has better time complexity hence is very important to practice. About the questions, you must solve 20-30 questions on Hashing.

Sample Questions:

• Find Whether an Array is a Subset of Another Array
• Union And Intersection of Two Linked Lists
• Find a Pair With the Given Sum
• LRU Cache Implementation
• Find the Itinerary From a Given List of Tickets
• Find Four Elements A, B, C, And D in an Array Such That A+B = C+D
• Find the Largest Subarray With 0 Sum

To Practice, more questions about Hashing, refer to Hashing GFG Practice

7. Greedy Algorithms

Next, you may proceed with Greedy algorithms as it has a great role in the Dynamic Programming concept. The advantage of comprehending Greedy algorithms is that you will learn how to think about a particular problem. Greedy algorithms are often used as a brute-force approach. Sometimes, we get optimized solutions using brute force approaches. About the questions, you must solve at least 30-35 questions on Greedy.

Sample Questions:

• Activity Selection Problem
• Kruskal’s Minimum Spanning Tree Algorithm
• Huffman Coding
• Efficient Huffman Coding For Sorted Input
• Prim’s Minimum Spanning Tree Algorithm
• Prim’s Mst For Adjacency List Representation
• Dijkstra’s Shortest Path Algorithm

To Practice, more questions on Greedy Algorithms, refer to Greedy Algorithms GFG Practice

8. Algorithms

After this, you can now jump to solve Algorithm questions. Algorithms are the core of programming helping to develop optimized methods with a good time and space complexity is itself one of the most important skills. Although there is no such number to be called sufficient for algorithms but about 40-50 questions can well develop anyone’s algorithmic skills in programming.

Sample Questions:

• Search Pattern (Kmp-Algorithm) 
• Search Pattern (Rabin-Karp Algorithm)
• Search Pattern (Z-Algorithm)
• Search an Element in a Sorted and Rotated Array(Binary Search)
• A Median of Two Sorted Arrays(Binary Search)
• Maximum And Minimum of an Array Using a Minimum Number Of Comparisons
• K Largest(Or Smallest) Elements in an Array | Added Min Heap Method
• Find the Number of Pairs (X, Y) In an Array Such That X^Y > Y^X

To Practice, more questions on Algorithms, refer to Algorithms GFG Practice

For Product-Based Companies

All the Concepts that are covered in Service Based Companies + Some more topics are mentioned below.

1. Bit Manipulation

Bit-Manipulation is one of the most important concepts of programming there are very less chances to encounter a direct question of bit manipulation but the concept is very helpful for fast calculation and can help to find optimized methods for many questions. You can solve about 10-15 questions for good control over the topic.

Sample Questions:

• Compute Xor From 1 To N (Direct Method)
• Count of Numbers (X) Smaller Than Or Equal to N Such That N+X = N^X
• How to Know If a Number is a Power of 2?
• Find the Xor of All Subsets of A Set
• Find the Number Of Leading, Trailing Zeroes And Number Of 1’s
• Convert Binary Code Directly Into an Integer in C++
• Check if a Number Has Bits in an Alternate Pattern

To Practice, more questions on Bit Manipulation, refer to Bit Manipulation GFG Practice

2. Heap and Priority Queue

The next topic is Heap and Priority Queue. Although heap seems to be a topic not much necessary but is recognized as very effective for problems where data needs to be in sorted. You have to solve around 20-25 questions. Don’t just directly use STL. First, understand how the heap is created. After that, you may use STL.

Sample Questions:

• K’th Largest Element in an Array
• K’th Smallest/Largest Element in Unsorted Array | Set 1
• Merge K-Sorted Arrays 
• Heap Sort
• Tournament Tree (Winner Tree) And Binary Heap
• Check if a Given Binary Tree Is Heap
• How To Check if a Given Array Represents a Binary Heap?
• Connect N Ropes With Minimum Cost

To Practice, more questions on Heap and Priority Queue, refer to Heap and Priority Queue GFG Practice

3. Trees

Trees are one of the most important data structures as can be directly related to real life. Because of this trees are considered one of the most important and frequently asked topics. There are multiple types of trees in programming but binary trees and binary search tree questions can be mostly observed. You must solve 30-40 questions trees. You should know the difference between a Tree and a Binary Search tree and how to implement it in the real world.

Sample Questions:

• The Sum of all Nodes in a Binary Tree
• The Sum of all the Parent Nodes Having Child Node X
• Print Left View of a Binary Tree
• Find The Sum of All Left Leaves in a Given Binary Tree
• Find The Sum of All Right Leaves in a Given Binary Tree
• Find The Sum of All Nodes of the Given Perfect Binary Tree
• Diagonal Sum of a Binary Tree
• Find If There is a Pair In Root To a Leaf Path With a Sum Equal to the Root’s Data

To Practice, more questions on Trees, refer to Tree GFG Practice

4. Graphs

Next, we are going to talk about the topics which are the heart of the placement- Graphs and DP. You must understand Graphs and the working of their algorithms BFS and DFS. To ace the interview rounds, you must solve at least 30-40 questions on graphs alone.

Sample Questions:

• Dijkstra’s Shortest Path Algorithm
• Dijkstra’s Algorithm For Adjacency List Representation
• Bellman–Ford Algorithm
• Floyd Warshall Algorithm
• Johnson’s Algorithm For All-Pairs Shortest Paths
• Shortest Path in Directed Acyclic Graph
• Shortest Path with Exactly K Edges in a Directed and Weighted Graph
• Dial’s Algorithm
• Printing Paths in Dijkstra’s Algorithm

To Practice, more questions on Graphs, refer to Graphs GFG Practice

5. Dynamic Programming

The next is DP(Dynamic Programming). Many people get scared of this topic, but with the strategic approach, you can easily understand it. As we have said above, Recursion is the heart of DP. So, if you know how to code recursively then understanding DP isn’t difficult. Otherwise, you will have to suffer a lot. You have to solve at least 30-40 questions of DP. This might look like a big number but DP is a vast concept and it requires a lot of practice.

Sample Questions: 

• 0-1 Knapsack Problem
• Lobb Number
• Eulerian Number
• Delannoy Number
• Entringer Number
• Rencontres Number
• Palindrome Partitioning
• Word Wrap Problem
• Mobile Numeric Keypad Problem

To Practice, more questions on Dynamic Programming, refer to Dynamic Programming GFG Practice

Advanced-Data Structures

Now, we will discuss some advanced topics which only a few companies ask about in their hiring process. If you have prepared and followed the prior strategy well, then only proceed to the advanced topics. 

1. Tries

It is a type of tree and its applications are many in real life. Programming Trie code is quite complex as compared to other data structures but there are only a few types of questions where trie is used. You may solve 10-15 questions to comprehend the concept well.

Sample Questions:

• Find The Maximum Subarray Xor In A Given Array
• Word Boggle
• Phone Directory
• Count Of Strings Whose Prefix Matches With The Given String To A Given Length K
• Unique Rows In The Boolean Matrix
• Palindrome Pairs

To Practice, more questions on Tries, refer to Tries GFG Practice

2. Segment Tree

The next advanced topic is the Segment Tree. Like in Tries, you can solve 10-15 questions here as well.

Sample Questions:

• Length of Longest Increasing Subsequences (Lis) Using Segment Tree
• Maximize the Length of The Longest Subarray Consisting of the Same Elements By at Most K Decrements
• Generate Original Permutation From a Given Array of Inversions
• Maximum of All Subarrays Of Size K Using Segment Tree
• Build a Segment Tree For N-Ary Rooted Tree
• Length of Longest Subarray With Same Elements in Atmost K Increments
• Count the Number of Increasing Sub-Sequences: O(Nlogn)

To Practice, more questions on Segment Tree, refer to Segment Tree.

3. Fenwick Tree

Fenwick Tree is also one of the most important concepts of DSA which you must definitely read and learn. You should solve 4-5 questions to get some idea about its usage.

Sample Questions:

• Count Inversions in an Array | Set 3 (Using BIT) 
• Two Dimensional Binary Indexed Tree or Fenwick Tree 
• Counting Triangles in a Rectangular Space using BIT

These three were advanced topics; very few companies will ask you, but if you want your preparation in advanced concepts, consider doing them. Please refer to the below-mentioned table to get an idea of how much coding is required for each topic of Data Structures and Algorithms.

Now, a question may arise in your mind, how many easy, medium, and hard questions you should solve? We highly recommend you build your thought process by solving the easy questions first. The most important thing is to think about logic. Building logic is very important while solving a problem, be it easy, medium, or hard-level. 

 

Conclusion

Hope this article has provided you with clarity and a full-fledged strategy to prepare for the placements. You have to be consistent and regular when solving problems. To crack an interview, regular learning and practicing problems are required. Hence, the above-mentioned concepts are some of the most important and must-go-through for any learner. Cultivate a habit of solving at least 5 easy and 2 medium to hard level questions on a regular basis and increase your question count as you grasp the concept. 

Frequently Asked Questions(FAQs)

1. What are the myths about coding?

There are numerous myths about Coding when you start practicing programming: 

• “Coding is only for geniuses“: This myth suggests that coding is a skill that only a select few people are capable of mastering. In reality, coding is a learned skill that anyone can acquire with time and practice.
• “Coding is a solitary activity“: While coding does involve a lot of individual work, it’s also a collaborative process. Coders often work in teams to develop and maintain software projects.
• “Coding is a boring job“: Coding can be a highly engaging and creative profession. Developers have the opportunity to solve complex problems, design new features, and build innovative products.
• “Coding is all about math“: While some areas of coding do require math skills, such as data science or game development, many other areas do not. The ability to think logically and break down problems is more important than mathematical proficiency.
• “Coding is only for young people“: Anyone can learn to code at any age. There are many successful developers who started their careers later in life.

One of the main reasons people are afraid of learning a programming language is that they believe it will be too difficult. While programming jargon can be intimidating, it is often simple to learn. It’s much easier to catch up once you understand the fundamentals.

3. Is basic coding sufficient for getting a job?

It depends on the organization for which you are seeking a job. Nonetheless, Most companies are unlikely to require exceptional programmer experts. While your coding skills are important, keep in mind that technical skills can be learned and improved at any time.

4. How much time should I give to DSA for getting a job?

It should take six months to a year to get a job in software development. Depends on whether you’re a beginner or someone who has already known the DSA concepts. If you’re starting from scratch, it can take anywhere from seven to twelve months to study and get a coding job.