Software Interview Preparation Training

Master Coding Interviews And Join the World's Top 1% Talent

Land lucrative SDE job offers with an Average Salary of $200K per year

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Turn Your Tech Career Aspirations into Reality

Are you an experienced SDE-II with 4 years of experience in a Non-FAANG company? It's time to make your dream tech job a reality. In just 15 weeks, you'll master Data Structures, Algorithms, and System Design, opening doors to top-tier tech companies. This program is your key to unlocking success in technical interviews and securing job offers from the top technology companies.

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Highlights

  • 58 Hours of Instructor-Led Sessions

  • 191 Hours of On-Demand Videos

  • 25 Hours of Doubt-Solving Sessions

  • 1:1 Mock Interviews with FAANG Experts

  • 2 Hours of Behavioural Mock Interview Sessions

  • 4 Hours of Technical Mock Interview Sessions

  • 2 Diagnostic Evaluations

  • 620+ Practical Exercises

  • 7 Real-World Projects

  • Interview Analysis and Feedback 

  • Optional 1:1 DSA and System Design Sessions

  • Resume Review and Expert Guidance

  • Comprehensive Placement Support

Learners Success Stories

temitayo

Temitayo Fagbami

Software Developer

Software Engineer

Sai Charan

Sai Charan

Senior Software Engineer

Senior Software Engineer

mayuresh

Mayuresh Raul

Software Engineer

Senior Software Engineer

harshvir

Harshvir Sidhu

Software Engineer

Senior Software Engineer

Azi Crawford

Azi Crawford

Platform Engineer

Software Engineer

Bharat Ram

Bharat Ram

Solution Architect

Technical Program Manager

Swagatika

Swagatika

Product Manager

Launch Technical Program Manager

George Andraws

George Andraws

Senior SDM

Senior TPM

Why You Should Hone Your Tech Interview Prep Skills

benefits of Software Interview Preparation

Securing a position as a software developer at top technology companies is the ultimate dream for any ambitious developer. Due to a large number of applicants, the top technology companies take nearly two months to close a job listing, indicating the meticulous selection process employed. More than 3 million people applied to Google in 2021, and only 20,000 were hired!

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Fast-track your way to a fulfilling and lucrative Software Engineering career.

Contact Learning Advisor

The KnowledgeHut Edge

Immersive Hands-On Program

Learn hands-on with engaging learning activities, including live virtual classes, coding challenges, mock interviews, assessments, and more.

Learn from Silicon Valley Experts

Interact and engage with industry veterans with a wealth of experience and mastery in tech. Tap into their expertise and gain invaluable insights.

Your Success, Our Commitment

Our commitment is aligned with your success. Pay our placement fee at 10% of your CTC only when we find you that rewarding job.

Gain Technical Mastery: DSA and System Design

Master Data Structures, Algorithms, and System Design and gain the technical expertise that sets you apart from the competition and impresses hiring managers.

Crack Behavioral Interviews

Technical skills alone won't guarantee success. Go beyond the code and learn how to crack behavioral interviews, showcasing your interpersonal skills.

Exclusive 1:1 Technical Interviews

Gain a competitive edge with four 1:1 technical interviews conducted by former FAANG hiring managers. Elevate your performance with insider knowledge.

Resume Reviews to Stand Out

Take advantage of our resume review service, where experts provide detailed feedback to make your resume shine. Increase your chances of landing that dream job!

450,000+ Careers Transformed

We have successfully trained and empowered over 450,000 professionals, enabling them to transform their careers and achieve new heights of success.

prerequisites for Software Interview Preparation

Prerequisites

To enroll for this Bootcamp, candidates must:

  • Be a Software Engineering Professional with a Computer Science Degree
  • Have a minimum of 4+ years of work experience, preferably in service-based companies
  • Be a resident of the United States or Canada
  • Have intermediate or advanced knowledge of programming languages like C/Java/Python
  • Be well-versed in the manipulation of basic strings and writing if-else arguments
  • Be able to solve basic coding problems

All You Need to Crush Your Tech Interviews

Master DSA in 15 Weeks

In just 15 weeks, our comprehensive program will get you tech interview-ready and equip you with the skills to excel in top-tier tech companies.

Highly Optimized Curriculum

Secure dream job offers through an intensive program optimized for Tier-I and II Product-Based Companies.

Adaptive Learning

Receive instant feedback and accelerate your learning through auto-evaluation of assessment questions.

Video Solutions for Assessment Questions

Access comprehensive video solutions for assessments, guiding you through effective problem-solving techniques.

Blend of On-Demand and Live Virtual Classes

Customize your learning experience with flexible self-paced content and interactive live classes by experts.

Personalized Technical Mock Interviews (1:1)

Sharpen your skills and gain confidence through personalized mock interviews with expert evaluators.

Behavioral Mock Interviews

Prepare for behavioral interviews with tailored mock sessions to impress top technology companies.

Resume Review Service

Optimize your resume for technical job applications with professional reviews and valuable recommendations.

Real-Life Scalable Projects in System Design

Gain hands-on experience in designing complex systems to tackle real-world challenges and impress recruiters.

Optional Add-On: 1:1 Mentorship Packs

Supercharge your learning with personalized mentorship for DSA or System Design expertise.

Pool of Stellar Instructors

Our industry-validated curriculum is designed by renowned experts and authors. The program is delivered by top instructors with several years of experience under their belt.

Masud Khan

Senior Software Engineer, Databricks

Mohammad Sharaf

Senior Software Engineer, Allex.ai

Bijaya Bhatta

Technical Lead, Bank of America

Rahul Salota

Program Director, Tech Interview Prep Program

Abdelrahman Soliman

Senior Software Engineer, Hopper

Sujeet Boran

AI Engineer, KLA

Arpit Agrawal

Tech Lead ShareChat, ex-IBM

Who Should Attend This Course

Programmers

Java Developers

Software Developers

Technical Program Managers

Software Development Engineers

Software Development Managers in service-based organizations

Skills You'll Gain

Hashmap Mastery

Linked List Proficiency

Queue Operations

Stack Manipulation

Array Efficiency

String Manipulation

Two Pointers Technique

Binary Search Skills

Recursive Problem Solving

Sorting and Searching Techniques

Tree Manipulation

Breadth-First Search (BFS) Proficiency

Priority Queue Handling

Sliding Window Mastery

Graphing Algorithms

Depth-First Search (DFS) Expertise

Breadth-First Search (BFS) Skills

Graph BFS Techniques

Topological Sorting Abilities

Divide and Conquer Strategies

Backtracking Skills

Connected Components Analysis

Bit Manipulation Proficiency

Dynamic Programming Expertise

Geometry Problem Solving

Mathematical Proficiency

Union-Find Operations

Greedy Algorithm Proficiency

Design and Coding Skills

Segment Tree Handling

Ordered Set Operations

Game Theory Knowledge

Monotonic Stack Skills

System Design Expertise

Impress Recruiters With a Stellar Project Portfolio

For any software designer looking to accelerate their career, end-to-end proficiency in System Design is crucial. Understand how to develop and scale up applications like YouTube, Netflix, WhatsApp and Spotify. This way, you'll learn to build app architecture and plan for proper functionality.

  • YouTube Video Sharing Platform

    An online video sharing platform that allows multiple users to watch and upload videos.

  • tripredictor
    Spotify Audio Streaming and Media Service

    A music listening app with features like playlists, digital audio content library like podcasts and more.

  • Uber Ride Hailing Platform

    A ride-hailing app that allows users to request cabs based on their location and features pricing and options.

  • Netflix Media Streaming Service

    A video streaming web app like Netflix with play/pause feature, movie catalogues, ratings, reviews, and lots more.

  • WhatsApp Centralized Instant Messaging and Voice-Over-IP Service

    Design a WhatsApp-like app with advanced messaging and multimedia sharing features.

  • Zulily Online Retailing Platform

    Build a system capable of managing different processes in inventory management.

  • DDOS Prevention Service Network Security Solution

    Defend online assets against relentless cyber threats enabling enterprises to avoid business downtime.

Tech Career Launch

Get ready to apply all the skills you learn through the course to ace interviews and land your dream job as a Software Development Engineer.

Career Planning and Coaching
  • Goal-Setting 
  • Personalized Career Planning
  • Career Coaching
Interview Preparation
  • Behavioural Mock Interviews
  • Technical Mock Interviews
  • Doubt-Solving Sessions
Dedicated Job Support
  • Target Software Developer Roles
  • Resume, LinkedIn, GitHub Review
  • Comprehensive Placement Assistance

Software Interview Preparation Course Syllabus

Download Curriculum
1.

Learning Objectives: Understand the concept and operations of a hashmap data structure, implement hashmaps using various programming languages, analyze the time complexity of hashmap operations, and comprehend their efficiency in average and worst-case scenarios. By the end of the module, you will be able to apply hashmaps to solve problems that necessitate fast key-value lookup or uniqueness, explore collision resolution techniques in hashmaps like chaining or open addressing, and understand the trade-offs between space complexity and hashmap performance.

Topics:
  • Design Hashmap 
  • Missing Number 
  • Binary Subarrays with Sum 
  • Subarray Sums Divisible by K 
  • Line Reflection 
  • Binary Subarrays with Sum 
  • Make Sum Divisible by P 
  • Subarray Sum Equals K 
  • Simplified Fractions 
  • Count Number of Nice Subarrays 
  • Insert Delete Getrandom 01 
  • Count Triplets That Can Form Two Arrays of Equal XOR 
  • Subarray Sums Divisible By K 
  • Find Two Non-Overlapping Sub Arrays Each with Target Sum 
  • Minimum Operations to Reduce X To Zero 
  • Partition Labels 
  • Task Scheduler 
  • Longest Arithmetic Subsequence 
  • Brick Wall 
  • Flip String to Monotone Increasing 
  • Product Of the Last K Numbers 
  • Count Ways to Make Array with Product 
  • Smallest Range Covering Elements from K Lists 

Learning Objectives: Understand the concept and structure of linked lists, implement them in various programming languages, analyze the time and space complexity of linked list operations, and compare and contrast linked lists with other data structures. By the end of the module, you will be able to apply linked lists to solve algorithmic problems efficiently and explore advanced variations of linked lists, such as doubly linked lists and circular linked lists.

Topics
  • Reverse Linked List 
  • Linked List Cycle 
  • Delete Node in Linked List 
  • Palindrome Linkedlist 
  • Intersection of Two Linked List 
  • Linked List Cycle 2 
  • Remove Nth Node from End of List 
  • LRU Cache 
  • Copy List with Random Pointer 
  • Swap Nodes in Pairs 
  • Linked List Random Node 
3.

Learning Objectives: On completing the queue module, you will gain an understanding of the concept and operations of a queue data structure. You will be able to implement queues using various programming languages and analyze the time and space complexity of queue operations. Additionally, you will have the ability to apply queues to solve problems requiring a first-in, first-out (FIFO) approach, compare and contrast queues with other data structures, and explore advanced queue variations such as priority queues and circular queues.

Topics
  • Binary Tree Right Side View 
  • Jump Game IV 
  • Maximum Sum Circular Subarray 
4.

Learning Objectives: Gain a comprehensive understanding of the concept and operations of a stack data structure. You will be able to implement stacks using various programming languages and analyze the time and space complexity of stack operations. Acquire the skills to apply stacks to efficiently solve problems that follow a last-in, first-out (LIFO) approach, compare and contrast stacks with other data structures, and explore advanced stack variations, including the implementation of stack-based algorithms or stack-based memory management.

Topics
  • Largest Rectangle in Histogram 
  • Maximum Frequency Stack 
  • Remove All Adjacent Duplicates in String II 
  • Minimum Remove to Make Valid Parentheses 
  • Next Greater Element II 
  • Design a Stack with Increment Operation 
  • Basic Calculator II 
  • Score of Parentheses 
  • Find the Most Competitive Subsequence 
5.

Learning Objectives: Understand arrays as efficient memory structures for storing elements, accessing and manipulating them through indexing and operations, and analyzing the time complexity of common operations like insertion, deletion, and searching. Apply arrays to solve data storage and retrieval problems, explore multidimensional arrays for problems with multiple dimensions, and recognize their limitations such as fixed size and memory allocation, considering alternative data structures when needed.

Topics
  • Count Negative Numbers in a Sorted Matrix 
  • Best Time to Buy and Sell Stock II 
  • Squares of a Sorted Array 
  • Sum of All Odd Length Subarrays 
  • Missing Number 
  • Search in Rotated Sorted Array 
  • Minimum Jumps to Reach Home 
  • Ways to Split Array into Three Subarrays 
  • Number of Boomerangs 
  • Find the Smallest Divisor Given a Threshold 
  • Single Element in a Sorted Array 
  • As Far from Land as Possible 
  • Maximum Sum Circular Subarray 
  • Maximum Product Subarray 
  • Max Value of Equation 
6.

Learning ObjectivesUnderstand strings as character sequences, manipulate them through operations like concatenation, substring extraction, and character searching, and analyze the time complexity of string operations. Apply string algorithms to solve problems involving matching, parsing, or manipulation. Explore string manipulation libraries and functions in different programming languages, understand the significance of string encoding, and consider internationalization considerations for handling strings efficiently.

Topics
  • Count Binary Substrings 
  • Add Strings 
  • Permutation in String 
  • Minimum Remove to Make Valid Parentheses 
  • Zigzag Conversion 
  • Basic Calculator II 
  • Score of Parentheses 
  • Reorganize String 
  • Next Greater Element III 
  • Partition Labels 
  • Longest Valid Parentheses 
  • Prefix and Suffix Search 

Learning Objectives: Understand the principles of the Two Pointers technique, apply it to efficiently solve problems involving array or list traversal, and identify and implement the necessary pointers for effective position tracking and element manipulation. Analyze the time and space complexity of algorithms utilizing the Two Pointers approach, optimize algorithms by leveraging the Two Pointers technique to reduce time complexity, and effectively solve a variety of algorithmic problems by leveraging the Two Pointers technique.

Topics
  • Permutation in String 
  • Longest Repeating Character Replacement 
  • Container with Most Water 
  • Next Permutation 
  • 3 Sum 
  • 3 Sum Smaller 
  • Number of Subsequences That Satisfy the Given Sum Condition 
  • Ways To Split Array into Three Subarrays 
  • Minimum Operations to Reduce X To Zero 
  • Valid Triangle Number 
  • 3 Sum Closest 
  • Subarrays With K Different Integers 
  • Find Median from Data Stream 
  • Trapping Rain Water 

Learning Objectives: Understand the principles of Binary Search, implement the Binary Search algorithm in multiple programming languages, analyze the time complexity of Binary Search and its advantages over linear search. Apply Binary Search to efficiently find elements in sorted arrays or lists, handle edge cases and understand the necessary conditions for Binary Search to function correctly, and explore variations of Binary Search.

Topics
  • Count Negative Numbers in a Sorted Matrix 
  • Binary Search 
  • Search In Rotated Sorted Array 
  • Unique Binary Search Trees 
  • Number Of Subsequences That Satisfy the Given Sum Condition 
  • Ways To Split Array into Three Subarrays 
  • Find The Smallest Divisor Given a Threshold 
  • Single Element in a Sorted Array 
  • Count Complete Tree Nodes 
  • Longest Increasing Subsequence 
  • Longest Arithmetic Subsequence 
  • Search a 2D Matrix 
  • Search a 2D Matrix II 

Learning Objectives: Understand recursion and its role in problem-solving, implement recursive algorithms in various domains, analyze the time and space complexity of recursive algorithms, and identify base cases and recursive cases when designing recursive solutions. Explore the relationship between recursion and mathematical induction, and apply recursive thinking to break down complex problems into smaller, manageable subproblems.

Topics
  • Employee Importance 
  • Minimum Distance Between BST Nodes 
  • Nested List Weight Sum 
  • Balanced Binary Tree 
  • Pow X N 
  • Kth Symbol in Grammar 
  • Nested List Weight Sum II 
  • Longest Univalue Path 
  • Swap Nodes in Pairs 
  • Predict the Winner 
  • Minimum Cost Tree from Leaf Values 
  • Expression Add Operators 
  • Word Break II 

Learning Objectives: Understand and compare different sorting algorithms (Bubble Sort, Insertion Sort, Merge Sort, Quick Sort) and their time complexities. Learn to implement efficient sorting algorithms for ordering elements in arrays or lists, explore searching algorithms (Linear Search, Binary Search) and their time complexities, apply searching algorithms to efficiently locate elements in collections (sorted or unsorted), analyze performance trade-offs between sorting and searching algorithms, and understand and implement advanced sorting techniques like Radix Sort or Heap Sort.

Topics
  • Count Negative Numbers in a Sorted Matrix 
  • Squares of a Sorted Array 
  • Wiggle Sort 
  • Sort Colors 
  • Distant Barcodes 
  • H Index 
  • H Index II 
  • Leftmost Column With At Least a One 
  • Sell Diminishing Valued Colored Balls 
  • 3 Sum 
  • 3 Sum Smaller 
  • Number of Subsequences That Satisfy the Given Sum Condition 
  • Maximum Gap 
  • Find Median from Data Stream 
  • Maximum Performance of a Team 
  • Minimum Cost to Hire K Workers 
  • Russian Doll Envelopes 
  • Maximum Profit in Job Scheduling 
  • Least Number of Unique Integers After K Removals 
  • Reorganize String 
11.

Learning Objectives: Understand trees as a fundamental data structure and their properties, implement tree data structures and traversal algorithms in programming languages, and analyze the time complexity of tree operations (insertion, deletion, searching). Apply trees to efficiently solve problems with hierarchical relationships or organized data, explore various types of trees (binary trees, binary search trees, balanced trees), and understand advanced tree concepts including tree balancing techniques such as AVL trees or Red-Black trees.

Topics
  • Diameter of Binary Tree 
  • Balanced Binary Tree 
  • Second Minimum Node in a Binary Tree 
  • Sum of All Odd Length Subarrays 
  • Symmetric Tree 
  • Complete Binary Tree Inserter 
  • Implement Trie (Prefix Tree) 
  • Unique Binary Search Trees 
  • Binary Tree Vertical Order Traversal 
  • Maximum Difference Between Node and Ancestor 
  • Count Complete Tree Nodes 
  • Binary Tree Right Side View 
  • Word Search II 

Learning Objectives: Understand the concept and mechanics of Breadth-First Search (BFS) in trees, implement a specialized BFS algorithm for tree traversal, and analyze the time and space complexity of Tree BFS. Apply Tree BFS to efficiently traverse and explore tree structures, utilize Tree BFS to solve problems like finding level order traversal or determining the width of a tree, and understand the differences and similarities between Tree BFS and Graph BFS algorithms.

Topics
  • Cut Off Trees for Golf Event 
  • Closest Leaf in a Binary Tree 

Learning Objectives: Understand the concept and operations of a priority queue data structure, implement a priority queue in various programming languages, analyze the time complexity of priority queue operations and their efficiency across different implementations, and apply priority queues to solve problems involving prioritization of elements. Explore various implementations of priority queues such as binary heaps or Fibonacci heaps and their trade-offs, and understand the relationship between priority queues and other data structures like heapsort or graph algorithms such as Dijkstra's algorithm.

Topics
  • Last Stone Weight 
  • Find K Pairs with Smallest Sums 
  • Top K Frequent Elements 
  • Swap Adjacent in Lr String 
  • Kth Smallest Element in a Sorted Matrix 
  • Top K Frequent Words 
  • Minimum Cost to Connect Sticks 
  • Split Array into Consecutive Subsequences 
  • Kth Largest Element in an Array 
  • K Closest Points to Origin 
  • Kth Smallest Number in Multiplication Table 
  • Trapping Rain Water 
  • Merge K Sorted Lists 
  • Kth Smallest Prime Fraction 
  • Cheapest Flights Within K Stops 
  • Reorganize String 
  • Network Delay Time 
  • Jump Game VI 
  • Path With Maximum Probability 

Learning Objectives: Understand the concept and mechanics of the Sliding Window technique, apply it to efficiently solve problems involving subarray or substring operations, and identify and implement the necessary data structures such as arrays or queues to implement the Sliding Window technique. Analyze the time and space complexity of algorithms, optimize the algorithms to reduce redundant computations, and effectively solve a variety of algorithmic problems by leveraging the Sliding Window technique.

Topics
  • Maximum Average Subarray 
  • Permutation in String 
  • Maximum Points You Can Obtain from Cards 
  • Binary Subarrays with Sum 
  • Number of Sub Arrays of Size K and Average Greater Than or Equal to Threshold 
  • Number of Substrings Containing All Three Characters 
  • Replace the Substring for Balanced String 
  • Fruit into Baskets 
  • Sliding Window Maximum 
  • Minimum Swaps to Group All 1's Together 
  • Longest Repeating Character Replacement 
  • Longest Continuous Subarray with Absolute Diff Less Than or Equal to Limit 
  • Minimum Size Subarray Sum 
  • Max Consecutive Ones III 
  • Longest Substring with at Most K Distinct Characters 
  • Maximum Average Subarray I 
  • Longest Turbulent Subarray 
  • Subarrays with K Different Integers 
  • Arithmetic Slices 
  • Jump Game VI 
  • Longest Substring with at Most Two Distinct Characters 
  • Shortest Subarray with Sum At Least K 
  • Minimum Window Substring 
  • Max Value of Equation 
  • Subarrays With K Different Integers 
15.

Learning Objectives: Understand and implement graph data structures and traversal algorithms, analyze their time and space complexity, and apply them to solve problems related to connectivity, shortest path, and traversal. Explore different graph representations and their trade-offs, and apply graph algorithms to real-world scenarios like network routing or social network analysis.

Topics
  • Find the Town Judge 
  • Network Delay Time 
  • House Robber 
  • Walls and Gates 
  • Number of Distinct Islands 
  • Detect Cycles In 2d Grid 
  • Count Servers that Communicate 
  • House Robber III 
  • Open the Lock 
  • Shortest Path with Alternating Colors 
  • Shortest Bridge 
  • Number of Closed Islands 
  • Find Eventual Safe States 
  • Tree Diameter 
  • 01 Matrix 
  • Cheapest Flights Within K Stops 
  • Find The Celebrity 
  • Minimum Number of Vertices to Reach All Nodes 
  • Is Graph Bipartite? 
  • Network Delay Time 
  • Number Of Operations to Make Network Connected 
  • Minimum Height Trees 
  • Path With Maximum Probability 
  • Longest Consecutive Sequence 
  • Alien Dictionary 
  • Sort Items by Groups Respecting Dependencies 

Learning Objectives: Understand and implement Depth-First Search (DFS) in multiple programming languages, analyze its time and space complexity, and apply DFS to traverse and explore graphs and trees. Identify and solve problems suited for DFS, and comprehend its relationship with other graph traversal algorithms like Breadth-First Search (BFS).

Topics
  • Flood Fill 
  • Surrounded Regions 
  • Pacific Atlantic Water Flow 
  • Is Graph Bipartite
  • Cheapest Flights Within K Stops 
  • Binary Tree Right Side View 
  • House Robber III 
  • Shortest Bridge 
  • Number of Provinces 
  • Network Delay Time 
  • Jump Game III 
  • Jump Game 
  • Maximum Difference Between Node and Ancestor 
  • Number Of Operations to Make Network Connected 
  • Minimum Height Trees 
  • Balanced Binary Tree 
  • Symmetric Tree 

Learning Objectives: Implement Breadth-First Search (BFS) in multiple programming languages, analyze its time and space complexity, and apply BFS to traverse and explore graphs and trees. Identify and solve problems well-suited for BFS, and understand its relationship with other graph traversal algorithms like Depth-First Search (DFS).

Topics
  • Word Ladder 
  • Perfect Squares 
  • As Far from Land as Possible 
  • Rotten Oranges 

Learning Objectives: Understand the concept and mechanics of Breadth-First Search (BFS) in graphs, implement BFS algorithms in multiple programming languages, analyze the time and space complexity of BFS, and apply BFS to efficiently traverse and explore graphs. Utilize BFS to solve problems like finding the shortest path or detecting connected components in a graph, and gain an understanding of the differences and similarities between BFS and other graph traversal algorithms, such as Depth-First Search (DFS).

Topics
  • Cheapest Flights Within K Stops 
  • Binary Tree Right Side View 
  • Surrounded Regions 
  • Pacific Atlantic Water Flow 
  • Perfect Squares 
  • Rotting Oranges 
  • Shortest Bridge 
  • Is Graph Bipartite? 
  • Network Delay Time 
  • Jump Game III 
  • Minimum Jumps to Reach Home 
  • Number Of Operations to Make Network Connected 
  • Minimum Height Trees 
  • As Far from Land as Possible 
  • Hard Breadth First Search 
  • Sort Items by Groups Respecting Dependencies 
  • Word Ladder 

Learning Objectives: Understand the concept and significance of Topological Sort in directed acyclic graphs (DAGs), implement algorithms like Depth-First Search (DFS) or Breadth-First Search (BFS) to perform Topological Sort, and identify the applications of Topological Sort in task scheduling or determining dependencies in a project, analyze the time and space complexity of Topological Sort algorithms. Apply Topological Sort to solve problems involving ordering or sequencing constraints, and gain an understanding of the relationship between Topological Sort and other graph algorithms, such as detecting cycles or finding shortest paths.

Topics
  • Minimum Height Trees 
  • Sort Items by Groups Respecting Dependencies 
  • Alien Dictionary 

Learning Objectives: Understand the concept and principles of the Divide and Conquer algorithmic paradigm, apply it to efficiently solve problems by breaking them into smaller subproblems, analyze the time complexity of Divide and Conquer algorithms using recurrence relations, and identify and implement an appropriate divide and combine steps for different problem domains. Utilize recursion and merge techniques in implementing Divide and Conquer algorithms, and solve a variety of algorithmic problems effectively by leveraging the Divide and Conquer approach.

Topics
  • Majority Element 
  • Best Time to Buy and Sell Stock 
  • Reverse Pairs 
  • The Skyline Problem 
  • Count Of Smaller Numbers After Self 
  • Best Time to Buy and Sell Stock III 
  • Median Of Two Sorted Arrays 
  • Beautiful Array 
  • Different Ways to Add Parentheses 
  • Best Time to Buy and Sell Stock II 

Learning Objectives: Understand the concept and principles of backtracking as a problem-solving technique, apply it to solve problems involving exhaustive search and constraint satisfaction, and implement necessary strategies such as pruning and optimization to improve backtracking efficiency. Analyze the time complexity of backtracking algorithms and identify applicable cases, utilize recursion and backtracking to explore and generate all possible solutions to a problem, and effectively solve a variety of algorithmic problems by leveraging the backtracking approach.

Topics
  • Subsets 
  • Combination Sum III 
  • Subsets II 
  • Factor Combinations 
  • Combination Sum II 
  • Letter Combinations of a Phone Number 
  • Generate Parentheses 
  • Combination Sum 
  • Combinations 
  • Word Search II 

Learning Objectives: Understand the concept and importance of connected components in graph theory, identify and classify connected components in a given graph, and implement algorithms like Depth-First Search (DFS) or Breadth-First Search (BFS) to find connected components. Analyze the time and space complexity of connected component algorithms, apply connected component analysis to solve problems related to graph connectivity, and explore the relationship between connected components and other graph properties such as strongly connected components or bipartite graphs.

Topics
  • Number Of Provinces 
  • Number Of Operations to Make Network Connected 
  • Smallest String with Swaps. 
  • Regions Cut by Slashes 

Learning Objectives: Understand binary representation and bitwise operations, perform basic bit manipulation operations like bitwise AND, OR, XOR, and bit shifting, utilize bit manipulation techniques for code optimization and problem-solving involving bitmasking and bit masking. Apply bit manipulation for arithmetic operations using bitwise operations, explore advanced bit manipulation techniques such as bit counting and reversing bits, analyze the time and space complexity of bit manipulation operations, and understand the practical applications of bit manipulation in cryptography and low-level programming.

Topics
  • Number of 1 Bits 
  • Counting Bits 
  • Count Triplets That Can Form Two Arrays of Equal XOR 

Learning Objectives: Understand Dynamic Programming as an algorithmic paradigm, apply it to efficiently solve problems by breaking them into overlapping subproblems, and identify and define recurrence relations or state transitions for Dynamic Programming problems. Utilize memorization or tabulation techniques to optimize subproblem computation, analyze the time and space complexity of Dynamic Programming algorithms, and effectively solve a variety of algorithmic problems using the Dynamic Programming approach.

Topics
  • Cheapest Flights Within K Stops 
  • Target Sum 
  • House Robber III 
  • Perfect Squares 
  • Longest Happy String 
  • Predict the Winner 
  • Unique Binary Search Trees 
  • Jump Game II 
  • Jump Game VI 
  • Minimum Jumps to Reach Home 
  • Minimum Sideway Jumps 
  • Maximum Absolute Sum of Any Subarray 
  • Find Two Non-Overlapping Sub Arrays Each with Target Sum 
  • As Far from Land as Possible 
  • Maximum Sum Circular Subarray 
  • Maximum Product Subarray 
  • Minimum Path Sum 
  • Longest Common Subsequence 
  • Minimum Number of Refueling Stops 
  • Best Time to Buy and Sell Stock III 
  • Stone Game III 
  • Russian Doll Envelopes 
  • Edit Distance 
25.

Learning Objectives: Understand geometry's fundamental concepts, including points, lines, angles, and shapes, and apply geometric formulas and theorems to solve problems related to areas, perimeters, and angles of various figures. Analyze geometric properties and relationships between shapes, utilize coordinate geometry to describe and manipulate points and shapes on a coordinate plane, explore geometric transformations, and apply geometric concepts to solve real-world problems.

Topics
  • Island Perimeter 
  • Surface Area of 3D Shapes 
  • Rectangle Area 
  • Minimum Area Rectangle II 
  • Minimum Area Rectangle 
  • Valid Square 
  • Rectangle Overlap 
  • Valid Boomerang 
  • Largest Perimeter Triangle 
  • Max Points on a Line 
  • Line Reflection 
  • Circle And Rectangle Overlapping 
  • Maximum Number of Visible Points 
  • Erect the Fence 
  • Erect the Fence II 
  • Rectangle Area II 
  • Perfect Rectangle 
  • Maximum Number of Darts Inside of a Circular Dartboard 
26.

Learning Objectives: Understand and apply fundamental mathematical concepts, including arithmetic, algebra, geometry, and calculus, and analyze and interpret mathematical data. Learn to utilize mathematical reasoning and critical thinking skills to solve problems, explore mathematical modeling and its real-world applications, and develop computational and problem-solving skills through mathematical exercises and practice.

Topics
  • Missing Number 
  • Excel Sheet Column Number 
  • Palindrome Number 
  • Reverse Integer 
  • Prime Arrangements 
  • Factorial Trailing Zeroes 
  • Global and Local Inversions 
  • Check If Array Pairs are Divisible by K 
  • Count Numbers with Unique Digits 
  • Reach a Number 
  • Rotate Image 
  • Count Primes 
  • Sparse Matrix Multiplic 
  • Fraction Addition and Subtraction 
  • Minimum Factorization 
  • Multiply Strings 
  • Rectangle Area 
  • Perfect Squares 
  • Maximum Swap 
  • Predict the Winner 
  • Next Permutation 
  • Unique Binary Search Trees 
  • Count Triplets That Can Form Two Arrays of Equal XOR 
  • Integer Break 
  • Prime Arrangements 
  • Permutation Sequence 
  • Remove 9 
  • Consecutive Numbers Sum 
  • Number of Digit One 
  • Orderly Queue 
  • Stone Game III 
  • Three Equal Parts 

Learning Objectives: Understand the concept and operations of the Union-Find data structure, implement it using various techniques, and analyze its time complexity. Apply it to solve connectivity and disjoint set problems, explore optimization techniques for improved performance, and understand its relationship with other graph algorithms such as Kruskal's algorithm for minimum spanning trees.

  • Redundant Connection 
  • Surrounded Regions 
  • Number of Provinces 
  • Smallest String with Swaps 
  • Number of Islands 
  • Friend Circles 
  • Evaluate Division 
  • Accounts Merge 
  • Sentence Similarity II 
  • Longest Consecutive Sequence 
  • Making a Large Island 
  • Shortest Path Visiting All Nodes 
  • Swim in Rising Water 
28.

Learning Objectives: Understand the concept and principles of the Greedy algorithmic paradigm, apply it to solve optimization problems, and analyze problem properties suitable for Greedy algorithms. Identify and implement strategies for designing and optimizing Greedy algorithms, explore their applications in different problem domains, and understand their trade-offs and limitations compared to other approaches.

Topics
  • Best Time to Buy and Sell Stock II 
  • Sell Diminishing Valued Colored Balls 
  • Car Pooling 
  • Reorganize String 
  • Longest Happy String 
  • Gas Station 
  • Monotone Increasing Digits 
  • Jump Game 
  • Jump Game II 
  • Find The Most Competitive Subsequence 
  • Minimum Sideway Jumps 
  • Task Scheduler 

Learning Objectives: Understand software design principles and apply them to create modular and reusable code, analyze requirements and use design patterns to design solutions. Implement clean and maintainable code, test and debug for correctness and robustness, and collaborate with team members to create scalable and efficient software solutions.

Topics
  • Design a Stack with Increment Operation 
  • Product of the Last K Numbers 
  • All O`One Data Structure 
  • Implement Trie (Prefix Tree) 
  • My Calendar I 
  • Largest Rectangle in Histogram 
  • Stone Game III 
  • Three Equal Parts 
  • Making a Large Island 
  • Maximum Performance of a Team 
  • Minimum Cost to Hire K Workers 
  • Russian Doll Envelopes 
  • Maximum Profit in Job Scheduling 

Learning Objectives: Understand segment trees as a data structure for efficient interval querying and updating, and implement them in various programming languages. Learn to analyze their time complexity, apply them to solve interval-based query problems, explore advanced techniques like lazy propagation, and understand their relationship with other data structures such as binary indexed trees or range minimum query structures.

Topics
  • My Calendar I 
  • My Calendar III 

Learning Objectives: Understand and implement ordered sets, analyze their time complexity for operations like insertion, deletion, and searching, apply them to solve problems requiring sorted collections, and explore advanced variations like balanced binary search trees. Understand the trade-offs between ordered sets and other data structures such as arrays or hash-based sets.

Topics
  • My Calendar I 
  • My Calendar III 

Learning Objectives: Understand and apply the principles of Game Theory to model and analyze strategic interactions in various types of games, and analyze strategies and equilibria using concepts like dominant strategies and Nash equilibrium. Explore solution concepts such as minimax and mixed strategies, apply game theory to real-world scenarios, and analyze the impact of factors like information asymmetry and repeated interactions on game outcomes.

Topics
  • Predict The Winner 
  • Stone Game III 

Learning Objectives: Understand the concept and properties of a monotonic stack data structure, implement it in different programming languages, analyze its time complexity, and apply it to solve problems involving the nearest greater/smaller elements or sliding windows. Explore advanced applications such as histograms or circular arrays, and understand their relationship with other data structures like monotonic queues or dynamic programming techniques.

Topics
  • Find The Most Competitive Subsequence 

Learning Objectives: Understand fundamental principles of system design, analyze requirements, apply architectural patterns, select technologies, and design reusable components. Learn to optimize performance, ensure fault tolerance and security, make informed decisions, and collaborate with stakeholders for successful system implementation.

Topics
  • 9 Steps to System Design 
  • High-Level System Design
  • Communication Channels
  • API Design Best Practices 
  • Database Design Best Practices 
  • DB Choices
  • Caching 
  • Message Queue Design 
  • Realtime Websockets, SSE etc.
  • Doubt Solving 

Learning Objectives: Learn resilient system design to withstand failures and protect data during disasters. Explore data sharding for efficient data storage distribution. Implement transactional systems for consistent and reliable inventory management, akin to Zulily. Design secure messaging apps like WhatsApp and develop DDOS prevention services. Enhance user experiences by creating features like pause in platforms such as Netflix. Gain expertise in building scalable platforms like Uber, YouTube, and Spotify to cater to diverse user needs.

Topics
  • HA and Disaster recovery 
  • Sharding 
  • Transaction Zulily Inventory Management System
  • Design Whatsapp
  • DDOS prevention service 
  • Netflix pause feature 
  • Design Uber 
  • Design YouTube 
  • Design Spotify 

This session is designed to help you get prepared for technical interviews and increase your chances of securing job offers at top technology companies. Through comprehensive training, you will develop a strong foundation in technical concepts, sharpen your problem-solving skills, and gain the confidence needed to excel in challenging and competitive interviews. Benefit from effective interview strategies by experts who've been there and done that. By the end of this session, you will be equipped with the necessary skills, knowledge, and mindset to succeed in technical interviews and stand out as a top candidate in the job market.

Topics
  • Evaluation for System Design Module 
  • Behavioural Learning 
  • Resume Review 
  • Behavioural Mock Interview - I 
  • Technical Mock Interview – I 

In this session, take your interview preparation to the next level and further enhance your skills for securing job offers at top technology companies. Building upon the foundation established in previous sessions, this session will provide you with more challenging interview scenarios, simulate real-world interview conditions, and focus on refining your problem-solving techniques.


Through intensive practice, personalized feedback, and targeted coaching, you will gain the ability to tackle complex technical problems with ease, effectively communicate your thought process, and demonstrate your expertise to potential employers. By participating in these Mock Interviews with industry experts who know what it takes to get into top tech companies, you will develop the resilience, adaptability, and confidence necessary to excel in even the most demanding technical interviews and position yourself as a standout candidate in the competitive job market.

Topics
  • Technical Mock Interview - II 
  • Behavioural Mock Interview - II 
  • Technical Mock Interview - III 
  • Technical Mock Interview - IV 

Software Engineering Interview Prep Course FAQs

Software Engineering Interview Prep Course

Cracking Software Development Engineer (SDE) interviews in Tier 1 tech companies call for solid fundamentals in data structures, algorithms, and system design. A large number of candidates make it to a few interview rounds at the top technology companies but fail to successfully clear them. For instance, while more than 3 million people applied to Google in 2021, only 20,000 were hired.

A robust program such as ours helps you gain the much-needed proficiency, which will in turn prepare you to clear both the technical and behavioral interview rounds typical of top product-based organizations.

This course is for anyone who is serious about getting into high-paying top-tier technology companies as a software development engineer. Typical candidate profiles include:  

  • Software Development Engineers 
  • Technical Program Managers 
  • Software Development Managers in service-based organizations 

KnowledgeHut's comprehensive Software Engineering Interview Prep Bootcamp is your pathway to achieving your dream tech job and securing a high-paying salary. In just 15 weeks, you'll gain mastery in data structures, algorithms, and system design, unlocking opportunities at top-tier tech companies. But our program goes beyond technical skills. Here's what you can accomplish:

  • Crack behavioral interviews and make a lasting impression on hiring managers.
  • Hone your interview skills and gain the confidence to ace any interview.
  • Access a comprehensive program covering essential skills for success.
  • Pay only when you succeed - a 10% placement fee of your CTC when we find you that rewarding job.
  • Benefit from four 1:1 technical interviews with former FAANG hiring managers to elevate your performance.
  • Receive a professional resume review service, getting detailed feedback to make your resume stand out.
  • Dive into the content, attend classes regularly, and solve practice questions to pave your way to success.

KnowledgeHut’s Software Engineering Interview Prep course will help you master a range of skills with the aim of helping you ace both the technical and behavioral interviews typical of top-tier technology companies. 

By the end of the course, you will be able to acquire practical skills that will help you stand out including:

  • Proficiency in Data Structures and Algorithms (DSA) to efficiently solve complex problems and optimize code
  • Understanding of various data structures such as arrays, linked lists, stacks, queues, trees, graphs, and hash tables
  • Knowledge of algorithmic techniques like searching, sorting, dynamic programming, and greedy algorithms
  • Ability to analyze and evaluate the time and space complexity of algorithms
  • Practical experience in designing scalable and efficient system architectures
  • Knowledge of system design principles, including scalability, fault tolerance, and performance optimization
  • Familiarity with designing distributed systems, microservices, and API architectures
  • Experience in evaluating trade-offs and making design decisions based on system requirements and constraints
  • Ability to apply design patterns and best practices in System Design
  • Proficiency in using relevant tools and technologies for System Design, such as UML diagrams and design frameworks
  • Practice in solving real-world system design problems and developing practical solutions

This course typically prepares you for senior Software Development Engineer (SDE) roles in Tier-1 technology companies. 

To benefit from this program, learners will need to be able to solve basic coding problems and be well-versed in the manipulation of basic strings and writing if-else arguments. In addition, they must have intermediate or advanced knowledge of programming languages like C/Java/Python. Learners also need to have a minimum of 4+ years of work experience, preferably in service-based companies.


Our comprehensive Interview Prep course will help you land senior Software Engineer jobs by providing you with the necessary skills, knowledge, and confidence to excel in technical interviews. Here's how the course will support your job search:

1) You will have acquired:

  • Deep understanding of core technical concepts and principles.
  • Mastery of problem-solving skills and effective approaches to technical questions and challenges.
  • Development of coding proficiency, enabling you to write clean, efficient, and readable code.

2) You will hone your interview prep skills with:

  • Practice of technical interview skills, including communication, collaboration, and time management.
  • Personalized feedback and mentorship to refine your skills and approach.

3) Increase your chances of success in technical interviews:

  • Mock interviews by industry experts
  • Enhance your ability to showcase your skills and stand out in competitive job interviews
  • Interview analysis and feedback

4) Placement support

  • Access to resume reviews by experts and guidance to optimize your resume for job applications.
  • Networking opportunities with industry professionals and fellow learners.
  • The reputation and recognition of completing a reputable and comprehensive course

By equipping you with the right skills, knowledge, and preparation, this course significantly increases your chances of securing a high-paying job in the tech industry. It provides you with a strong foundation and competitive edge, positioning you as a highly desirable candidate for technology roles.

Mentors in our immersive learning program are Silicon Valley Experts and Tech Leaders from FAANG and Tier-1 companies. These mentors bring a wealth of experience in Data Structures and Algorithms (DSA) and System Design, ensuring that you receive top-notch guidance and insights from industry professionals.

Their expertise and knowledge will empower you to excel in these areas and gain a deeper understanding of the concepts and practices that are valued in the industry. You can trust that our mentors will provide valuable insights, real-world perspectives, and practical advice to help you succeed in your learning journey.

Absolutely! Mock interviews are a crucial component in preparing for the technical and behavioral rounds of top-tier interviews. Our program offers 1:1 mock interviews with Silicon Valley experts who provide invaluable guidance and practice opportunities.

By simulating real interview scenarios, our mock interviews ensure that you are well-prepared to showcase your technical proficiency and effectively demonstrate your behavioral competencies. You'll gain the experience and confidence needed to excel in technical and behavioral interviews and increase your chances of securing your dream job in the tech industry.

Our comprehensive bootcamp goes beyond providing technical knowledge and skills. It also offers comprehensive placement support to help you succeed in your career as a Software Engineer.

From practicing technical interview skills to receiving personalized feedback and mentorship, the placement support aims to enhance your abilities and increase your chances of securing job offers at top technology companies. Benefit from four 1:1 technical interviews with former FAANG hiring managers to elevate your performance. With this valuable assistance, you can confidently navigate the job market and position yourself for a highly-rewarding career in tech.

To enroll for this Bootcamp, candidates must meet the following criteria:

  • Be a Software Engineering Professional with a Computer Science Degree.
  • Have a minimum of 4+ years of work experience, preferably in service-based companies.
  • Be a resident of the United States or Canada.
  • Have intermediate or advanced knowledge of programming languages like C/Java/Python.
  • Be well-versed in the manipulation of basic strings and writing if-else arguments.
  • Be able to solve basic coding problems.

Course Experience

Yes! Upon completing the course and meeting all the requirements, you will receive a certificate of completion issued by KnowledgeHut. Thousands of KnowledgeHut alumni use their course certificates to demonstrate skills to potential employers and across their LinkedIn networks. 

KnowledgeHut’s tech programs are well-regarded by many top employers, who contribute to our curriculum and partner with us to train their teams.

Yes, you can! We have both weekend and weekday batches designed to help busy professionals with full-time work commitments. For example, as a part of the weekend batch, you can attend live instructor-led sessions on the weekend and then complete assignments/projects during your free time on weekdays.  

You have the option to pause the program for 14 days. Before rejoining, you would need to catch up with the Program by watching the recorded instructor-led sessions. You may opt for this option after discussing it with your Student Success Manager.  

You also have the option to defer a program, provided there is a valid reason offered to your Student Success Manager and is approved by the Program Director. Once you are back, you can discuss with your Student Success Manager to know which batch of the course you can join.  

Please contact your Learning Advisor for more information about this. 

What Learners are Saying

R
Ronan Ortiz Software Development Engineer
5
I got a whole confidence boost because I finally felt that landing a high-paying job with a top technology company was within reach, during the course. Thanks to the entire team at KnowledgeHut for this offering.

Attended Software Interview Preparation workshop in December

A
Asad Muhammad Technical Program Manager
5
This is THE course to enroll for if you want to be a software engineer in top product-based. Not only do they make you an expert in DSA and system design, but they also prepare you thoroughly for behavioral interviews.

Attended Software Interview Preparation workshop in December

B
Blessy Joseph Programmer
5
Thanks to this course, I was finally able to understand how tough software interviews are at top-tier tech companies, and the depth of learning they actually required.

Attended Software Interview Preparation workshop in December

R
Rita Willis Java Developer
5
If not for this program, my grasp of Data Structures and Algorithms would be severely lacking, and I wouldn't have offers from two top-tier tech companies in hand today. Thanks, team KH!

Attended Software Interview Preparation workshop in December

S
Shanaya Bora Software Development Manager
5
This course is complete bang for your buck because it helped me get a job at Meta as a Software Engineer. Speaking from my personal experience, this course is very through in terms of the topics covered and the instructors deliver its well.

Attended Software Interview Preparation workshop in December