★★★★★
"The structure, the practice exams, the instructor — all top tier. Passed first try."
AS
Ranjan PradhanSenior Project Manager
— The journey
Course Outline
What the programme covers, module by module.
Module 1: Introduction to Data Structures & Algorithms
- Data structures
- Algorithms
- Abstract data types
- Algorithm characteristics
- Problem-solving process
- Choosing appropriate structures
Module 2: Algorithm Complexity Analysis
- Time complexity
- Space complexity
- Big O notation
- Big Omega
- Big Theta
- Complexity comparison
Module 3: Arrays
- Array fundamentals
- Traversal
- Insertion
- Deletion
- Searching
- Multidimensional arrays
Module 4: Strings & String Processing
- String representation
- Character processing
- Pattern concepts
- String comparison
- Substrings
- Common string problems
Module 5: Linked Lists
- Singly linked lists
- Doubly linked lists
- Circular linked lists
- Insertion
- Deletion
- Traversal
Module 6: Stacks
- Stack concepts
- Push and pop
- Stack implementation
- Expression processing
- Parentheses matching
- Stack applications
Module 7: Queues
- Queue concepts
- Enqueue and dequeue
- Circular queues
- Priority queues
- Deques
- Queue applications
Module 8: Hashing & Hash Tables
- Hash functions
- Hash tables
- Key-value storage
- Collisions
- Collision resolution
- Hashing applications
Module 9: Recursion
- Recursive thinking
- Base cases
- Recursive calls
- Call stack
- Recursive algorithms
- Recursion complexity
Module 10: Searching Algorithms
- Linear search
- Binary search
- Search conditions
- Iterative searching
- Recursive searching
- Search complexity
Module 11: Basic Sorting Algorithms
- Bubble sort
- Selection sort
- Insertion sort
- Algorithm comparison
- Stability
- Sorting complexity
Module 12: Advanced Sorting Algorithms
- Merge sort
- Quick sort
- Heap sort
- Divide-and-conquer
- Partitioning
- Performance comparison
Module 13: Trees
- Tree terminology
- Tree representation
- Binary trees
- Tree traversal
- Depth and height
- Tree applications
Module 14: Binary Search Trees
- BST properties
- Searching
- Insertion
- Deletion
- Traversal
- Complexity analysis
Module 15: Balanced Trees
- Need for balancing
- AVL trees
- Rotations
- Balanced search
- Tree height
- Performance considerations
Module 16: Heaps & Priority Queues
- Heap structure
- Min heaps
- Max heaps
- Heap operations
- Heap construction
- Priority queue implementation
Module 17: Graph Fundamentals
- Vertices and edges
- Directed graphs
- Undirected graphs
- Weighted graphs
- Adjacency lists
- Adjacency matrices
Module 18: Graph Traversal
- Breadth-First Search
- Depth-First Search
- Visited tracking
- Connected components
- Cycle concepts
- Traversal applications
Module 19: Graph Algorithms
- Shortest-path concepts
- Dijkstra's algorithm
- Minimum spanning trees
- Prim's algorithm
- Kruskal's algorithm
- Topological sorting
Module 20: Greedy Algorithms & Backtracking
- Greedy strategy
- Greedy choice
- Backtracking
- State-space exploration
- Constraint problems
- Problem-solving patterns
Module 21: Dynamic Programming
- Overlapping subproblems
- Optimal substructure
- Memoisation
- Tabulation
- State definition
- Dynamic programming problems
Module 22: Algorithmic Problem-Solving & Optimisation
- Problem decomposition
- Selecting data structures
- Selecting algorithms
- Complexity optimisation
- Space-time trade-offs
- Solution evaluation
— 01.2 · Is it right for you?
Who it's for & what's included
Pick a delivery method to see exactly who it suits and everything you receive.
Who it's for
Classroom
Best for learners who want face-to-face tuition and to network with peers in person.
What's included
Everything you get
- ✓ Live instructor on-site
- ✓ Printed workbook & materials
- ✓ Group exercises & case studies
Who it's for
Online Instructor-Led
Best for learners who want a live instructor and a fixed schedule, without the travel.
What's included
Everything you get
- ✓ Live instructor via video call
- ✓ Digital workbook & resources
- ✓ Session recordings
Who it's for
Self-Paced
Best for self-motivated learners who need maximum flexibility around work and life.
What's included
Everything you get
- ✓ On-demand video lessons
- ✓ Interactive quizzes
- ✓ 24/7 access on any device
— About this course
Course Overview
The Data Structures & Algorithms program equips working professionals with practical skills to design efficient solutions to computational problems. Participants learn algorithm analysis, Big O notation, arrays, linked lists, stacks, queues, hashing, recursion, searching, sorting, trees, heaps, graphs, greedy algorithms, backtracking, dynamic programming, and optimisation techniques applicable to software development and technical problem-solving.