Data Structures & Algorithms - Course Topics
- Introduction
- What are Data Structures?
- What are Algorithms?
Data Structures & Algorithms
RST Forum’s Data Structures & Algorithms course in Mumbai is a 100-hour instructor-led program (lectures + hands-on labs) designed to equip you with the knowledge, skills, and expertise required to, developing, and implementing highly efficient, stable, and scalable algorithms. Taught live with hands-on lab practice - classroom batches run in Mumbai with the same batch live-online across India.
- Duration
- 100 hours
- Training mode
- Classroom & online
- Course fees
- ₹30,000
- Level
- Advanced
Live, Instructor led (ILT)
Mumbai campus
for working engineers
Course details verified
Please note that the course fees exclude the certification cost.
Overview
Who should attend
This 100-hour (Lectures + hands-on Lab) Data Structures and Algorithms course is designed to equip you with the knowledge, skills, and expertise required to, developing, and implementing highly efficient, stable, and scalable algorithms. Candidates will be educated on formulating sophisticated algorithmic solutions and will traverse through an extensive spectrum of data structures and algorithmic concepts, from rudimentary to advanced levels. Throughout the program, learners will immerse themselves in vital subjects, transitioning from elementary structures like arrays and queues to more complex themes such as trees and graphs. They will also confront real-world algorithmic problems and data structure challenges to fortify their comprehension and acquire hands-on expertise. Additionally, candidates will master the art of algorithmic complexity and performance analysis, crucial competencies in the realm of efficient problem-solving and computational programming. Candidates will undertake myriad coding tasks and projects intended to refine their analytical thinking and solidify the theories expounded in the lectures. This is a lab-intensive, project-based course and objectives are accomplished through hands on learning.
Roles this leads to
Typical India salary
- Software Engineer (SDE)₹6–20 LPA
- Backend Engineer₹6–16 LPA
- Full Stack Developer₹5–14 LPA
- SDET / Test Engineer₹5–12 LPA
Outcomes
Skills you'll gain
- Data Structures & Algorithms - Course Topics
- High Order Array Methods
- Time & Space Complexity
- Hash Tables, Maps & Sets
- Stacks, Queues & Linked Lists
- Binary Trees, BST & Graphs
- Sorting Algorithms
- Arrays
- BST
- Binary Trees
Objectives
What you'll be able to do
The course objectives, as the vendor's own blueprint states them.
- Analyse any algorithm's time and space complexity in Big-O terms, fluently.
- Implement the core structures from scratch: arrays, linked lists, stacks, queues, hash tables, trees, heaps and graphs.
- Apply the classic interview patterns: two pointers, sliding window, BFS/DFS, backtracking, divide and conquer, dynamic programming.
- Choose the right data structure for a problem and justify the trade-offs out loud, interview-style.
- Master sorting and searching algorithms and know when each one wins.
- Traverse and manipulate binary trees, BSTs and graphs with confidence.
- Solve interview-grade problems under time pressure with a repeatable method.
- Handle the system-design round: the fundamentals interviewers probe after the coding round.
- Walk into product-company interviews with drilled, assessed practice behind you.
Included
What you get
- Curriculum based on course outlines defined by industry best practices.
- This Instructor-led classroom course is designed with an aim to build theoretical knowledge supplemented by ample hands-on lab exercises.
- Facility of Lab on cloud available.
- Courseware includes reference material to maximize learning.
- Assignments and tests to ensure concept absorption.
- Repeating of lectures allowed (On approval basis)
- Candidates can attend lectures online.
Credential
Certification details
You leave with an RST Forum certificate of completion and - the real outcome - the problem-solving fluency that clears coding rounds at product companies.
The course is practice-driven: every data structure and algorithm is implemented, analysed for complexity and drilled through interview-grade problems.
After the course
Placements & outcomes
Placement assistance is included: CV preparation, interview drills with real scenario questions, and referrals through our alumni network of 1 million+ engineers trained since 1997.
Learning path
Where this course takes you
This course is one stage of the Artificial Intelligence path - 10–14 months end to end, beginner → expert. Here is what comes before it, and what comes after.
- Python ProgrammingAutomation Engineer · 2–3 months
- Data Structures & Algorithms (with System Design)You are hereSoftware Engineer · 2–3 months
- Artificial Intelligence (ML, DL, RAG, Agentic) EngineeringAI Engineer · 4–6 months
- DevOps (with AIOps & MLOps)MLOps Engineer · 3–4 months
Next up: Artificial Intelligence (ML, DL, RAG, Agentic) Engineering - From NumPy to shipping your own agents - the whole stack, not a demo notebook.
17 modules
Full syllabus
Every module below is taught live and practiced hands-on - nothing here is a slide-only topic.
Understanding Algorithms and Basic Programming Solutions
- Get Sum
- Calculator
- Count Occurences
- Find Max Number
- Title Case
- Reverse String
- Palindrome
- Count Vowels
- Remove Duplicates
- FizzBuzz Array
- Array Intersection
- Display Likes
- Find Missing Number
- Find Missing Letter
- Character Uniqueness
- First Non-Repeating Character
- Dice Game Simulation
- Formating Phone Numbers
- Email Validation
High Order Array Methods
- Using map, filter, find, reduce, every, some
- Sum of Even Numbers
- Calculate Total Sales
- Highest Scoring Word
- Valid Anagrams
- Hashtag Generator
- Valid IPv4
- Analyze Car Mileage
- Password Validator
- Find Missing Letter
Time & Space Complexity
- What is Time Complexity
- Big O Notation
- Constant Time Complexity - O(1)
- Linear Time Complexity - O(n)
- Quadratic Time Complexity O(n^2)
- Logarithmic Time Complexity O(log n)
- Space Complexity
- Max Subarray - Quadratic
- Sliding Window Technique
- Max Subarray - Linear
- Array.reduce Method
- More Array Methods
Hash Tables, Maps & Sets
- Introduction to Hash Tables
- Maps
- Word Frequency Counter
- Phone Number Directory
- Anagram Groupings
- Sets
- Symmetric Difference
- Two Sum
- Longest Consecutive
- Custom Hash Table
- Word Instance Counter with Custom Hash Table
- Add getValues() Method
- Anagram Grouping With Custom Hash Table
Stacks, Queues & Linked Lists
- What is a Stack?
- Implementing a Stack
- Reverse String Using a Stack
- Balanced Parenthesis
- What is a Queue?
- Queue Implementation
- Reverse String with a Queue
- Palindrome with a Queue & Stack
- Introduction to Linked Lists
- Linked List Implementation
- Reverse String with a Linked List
- Fast & Slow Pointers
- Find Middle
- Doubly Linked List
- Doubly Linked List Implementation
- Find Pair Sum
Binary Trees, BST & Graphs
- Introduction to Trees and Binary Trees
- Tree Node Class
- Depth-First Traversal
- Depth-First Traversal Using Recursion
- Breadth-First Traversal
- Maximum Depth
- Introduction to Binary Search Trees
- Binary Search Tree Implementation
- Validate BST
- Introduction to Graphs
- Adjacency Matrix & Adjacency List
- Graph Implementation
- Graph Traversal Visualization
- Graph Depth-First Traversal
- Graph Breadth-First Traversal
Sorting Algorithms
- Introduction to the various Sorting Algorithms
- Why we need them?
- Bubble Sort Algorithm & Implementation
- Insertion Sort Algorithm & Implementation
- Selection Sort Algorithm & Implementation
- Merge Sort Algorithm & Implementation
- Quick Sort Algorithm & Implementation
Arrays
- Validate Subsequence
- Tournament Winner
- Transpose Matrix
- Three Number Sum
- Smallest Difference
- Move Element to End
- Monotonic Array
- Spiral Traversal
- Longest Peak
- Array of Products
- Find Duplicate Value
- Merge Overlapping Intervals
- Best Seat
- Zero Sum Subarray
- Missing Numbers
- Majority Element
- Four Number Sum
- Subarray Sort
- Largest Range
- Min Rewards
- ZigZag Traverse
- Longest Subarray with Sum
- Knight Connection
- Count Squares
- Apartment Hunting
- Calendar Matching
- Waterfall Streams
- Minimum Area Rectangle
- Line Through Points
BST
- Min Height BST
- Find Kth Largest Value in BST
- Reconstruct BST
- Same BSTs
- Validate Three Nodes
- Repair BST
- Sum BSTs
- Right Smaller Than
Binary Trees
- Node Depths
- Merge Binary Trees
- Invert Binary Tree
- Symmetrical Tree
- Split Binary Tree
- Max Path Sums in Binary Tree
- Find Nodes Distance K
- Iterative In-order Traversal
- Flatten Binary Tree
- Right Sibling Tree
- All Kinds of Node Depths
- Compare Leaf Traversal
Popular Algorithms
- Kadane Algorithm
- Stable Interships
- Union Find
- Dijkstra's Algorithm
- Topological Sort
- Kruskal's Algorithm
- Prim's Algorithm
- Knuth-Morris-Pratt Algorithm
- A* Algorithm
Graphs
- Cycle In Graph
- Remove Islands
- Two-Colorable
- Boggle Board
- Largest Island
- Rectangle Mania
- Detect Arbitrage
- Two-Edge-Connected-Graphs
- Airport Connections
Heaps
- Min Heap Construction
- Continous Median
- Sort K-Sorted Arrays
- Laptop Rentals
- Merge Sorted Arrays
Searching
- Search for Range
- Search in Sorted Matrix
- Shifted Binary Search
- Quickselect
- Index Equals Value
- Median of Two Sorted Arrays
- Optimal Assembly Line
Recursion
- Powerset
- Phone Number Mnemonics
- Staircase Traversal
- Black Jack Probablity
- Reveal Minesweeper
- Lowest Common Manager
- Solve Sodoku
- Generate Div Tags
- Non-attacking Queens
Linked Lists
- Find Loop
- Reverse Linked lsit
- Merge Linked Lists
- Shift Linked List
- LRU Cache
- Zip Linked List
- Node Swap
- Linked List Palindrome
28 labs
Hands-on labs
Structured labs on real equipment, with 24/7 lab-on-cloud access through Skillopia - our own lab platform.
Hands-on labs
2801
Implement Basic Algorithms in JavaScript
02
Analyze and Improve Brute-Force Algorithms
03
Advanced Array Manipulations using JavaScript
04
Problem Solving with map, filter, and reduce
05
Implement Recursive Functions
06
Solve Problems using Divide and Conquer Strategies
07
Analyze Algorithm Complexity
08
Optimize Algorithms for Performance
09
Implementing Custom Hash Tables
10
Solve Problems using Maps and Sets
11
Implement Stack and Queue Data Structures
12
Create and Manipulate a Linked List
13
Implement a Binary Search Tree
14
Graph Implementations and Traversals
15
Implement and Analyze Sorting Algorithms
16
Compare and Contrast Sorting Strategies
17
Solve Complex Problems using Data Structures
18
Implement Advanced Algorithms
19
Implement and Analyze Kadane's Algorithm
20
Graph Algorithms and Path Finding
21
Construct and Manipulate a Min Heap
22
Solve Problems using Heap Data Structure
23
Implement and Analyze Search Algorithms
24
Optimized Searching in Structured Data
25
Solve Advanced Recursive Problems
26
Implement Backtracking Strategies
27
Advanced Operations on Linked Lists
28
Solve Problems using Doubly Linked Lists
Batches
Upcoming start dates
No date is published for this course at the moment. Tell us when you want to start and we will build a batch around it.
No scheduled batch right now
This course runs on demand as well as on the public calendar. Ask us for the next planned date, or tell us the window that suits you - classroom in Mumbai or live online, weekday or weekend - and we will put a batch together and confirm it with you.
Investment
Course Fees
Total course fee
₹30,000
Exam fees are not included. The certification cost is paid directly to the vendor.
Pay module by module, or in full. Talk to us about instalments before you enrol.
Answers
Frequently asked questions
- What is the Data Structures & Algorithms course fee at RST Forum?
- The course fee is ₹30,000.
- How long is the Data Structures & Algorithms course?
- 100 hours of live instructor-led training (lectures + hands-on lab practice), across weekday-evening or weekend batches.
- Do I need prior experience to join?
- Basic programming knowledge in any language (Python, Java, C++ or JavaScript).
- Is the training online or classroom?
- Both. Classroom batches run at our Mumbai campus; the same batch streams live for online students across India. Both get identical lab access.
- Are the labs hands-on?
- Yes - this is a lab-intensive course practiced on real equipment, with 24/7 remote lab access through Skillopia, our own lab platform, for practice between classes.
- Do you provide placement assistance?
- Yes. CV preparation, mock interviews with real scenario questions, and referrals through our alumni network of 1 million+ engineers trained since 1997.
- What comes after this course?
- DSA pairs with our Full Stack track - together they are the standard preparation for product-company interviews.
01
02
03
04
05
06
07
Reserve your seat
Watch a real class. Meet your instructor. Then decide.
Hold a place on the next batch and sit in on the opening session. See the teaching, the racks and the labs exactly as students do, then enrol if it's right for you.
1 million+
engineers trained
1997
training since
24/7
Skillopia lab access
Keep exploring
More Software Development courses
Advanced Java - Professional
90 hrs · 45 labs · Advanced
Fee₹20,000
Angular Web Development Framework
80 hrs · 23 labs · Advanced
Fee₹20,000
C++ Programming
60 hrs · 20 labs · Beginner
Fee₹18,000
Full Stack Web Development with AI Integration (TypeScript, React, Node.js)
150 hrs · 124 labs · Beginner
Fee₹30,000