School of Software Engineering · Intermediate–Advanced
Data Structures & Algorithms (DSA) for Coding Interviews Course
Master the coding patterns behind technical interviews with structured practice, complexity analysis, DSA mastery and mock interviews.
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Complexity and Problem-Solving FrameworkArrays, Strings and Two-Pointer PatternsLinked Lists, Stacks and QueuesTrees, BSTs, Tries and Heaps
Any interview language (Python or Java recommended)Online judgeCoding platformGitHub
How you will learn
What you will learn, module by module
Master data structures, algorithms, problem solving and technical interview patterns. Progress from Complexity and Problem-Solving Framework to Interview Simulation and DSA Capstone through guided labs, assessed projects, and portfolio evidence.
01Module 1 · 6 hoursComplexity and Problem-Solving FrameworkAnalyse and optimise a set of baseline solutions while explaining trade-offs aloud.
Topics you will cover
- Big-O time/space
- Constraints
- Brute force to optimized
- Test cases
- Invariants
- Communication
- Interview problem-solving workflow
- Tools and platforms
- Any interview language; Python/Java recommended
- Portfolio evidence
- Complexity cheat sheet + solved set
- Assessment
- Timed analysis
02Module 2 · 10 hoursArrays, Strings and Two-Pointer PatternsSolve a curated set of interview problems and classify patterns.
Topics you will cover
- Arrays
- Strings
- Hashing
- Prefix sums
- Sliding window
- Two pointers
- Sorting patterns
- Frequency maps
- Subarray problems
- Tools and platforms
- Python/Java, Online judge optional
- Portfolio evidence
- Solved array/string portfolio
- Assessment
- Pattern checkpoint
03Module 3 · 8 hoursLinked Lists, Stacks and QueuesImplement core structures and solve cycle, stack and queue pattern problems.
Topics you will cover
- Linked-list operations
- Fast/slow pointers
- Stacks
- Monotonic stack
- Queues/deques
- Expression parsing
- Cache concepts
- Tools and platforms
- Python/Java
- Portfolio evidence
- Data-structure implementations
- Assessment
- Coding assessment
04Module 4 · 10 hoursTrees, BSTs, Tries and HeapsSolve tree traversal, heap and top-K problems under time constraints.
Topics you will cover
- Tree traversal
- Recursion/iteration
- BST operations
- Heaps/priority queues
- Tries
- Top-K
- Interval/scheduling use cases
- Tools and platforms
- Python/Java
- Portfolio evidence
- Tree/heap problem set
- Assessment
- Timed challenge
05Module 5 · 10 hoursGraphs and Graph AlgorithmsSolve dependency, pathfinding and connectivity interview problems.
Topics you will cover
- Representations
- BFS/DFS
- Connected components
- Topological sort
- Shortest paths
- Union-find
- Grid graphs
- Cycle detection
- Tools and platforms
- Python/Java
- Portfolio evidence
- Graph algorithms notebook/repo
- Assessment
- Graph practical
06Module 6 · 8 hoursRecursion, Backtracking and SearchSolve combinatorial search problems and document pruning strategies.
Topics you will cover
- Recursion trees
- Subsets/permutations
- Combinations
- Constraint search
- Pruning
- Memoisation
- Divide-and-conquer
- Search space reasoning
- Tools and platforms
- Python/Java
- Portfolio evidence
- Search-pattern problem set
- Assessment
- Backtracking checkpoint
07Module 7 · 12 hoursDynamic Programming and Greedy PatternsSolve progressively harder DP and greedy problems using a repeatable framework.
Topics you will cover
- State definition
- Transitions
- Memoisation/tabulation
- 1D/2D DP
- Knapsack patterns
- Subsequences
- Interval DP awareness
- Greedy proof intuition
- Tools and platforms
- Python/Java
- Portfolio evidence
- Dynamic programming portfolio
- Assessment
- DP assessment
08Module 8 · 16 hoursInterview Simulation and DSA CapstoneComplete multiple mock coding interviews and a final curated 50-75 problem mastery set.
Topics you will cover
- Mixed pattern recognition
- Coding under time
- Clarifying questions
- Communication
- Testing
- Optimization
- Behavioral handoff
- Mock interviews
- Tools and platforms
- Coding platform, GitHub
- Portfolio evidence
- Interview-ready DSA repository
- Assessment
- Mock interview rubric
Projects you will build
2 portfolio projects plus module evidence
75-Problem Pattern Mastery Portfolio
Complete a curated problem set across core interview patterns with explanations and complexity analysis.
GitHub repository · Pattern notes · Optimised solutionsMock Interview Sprint
Complete timed mock interviews and track improvement across speed, correctness and communication.
Interview scorecards · Weak-area plan · Final readiness report Course value
Why this course
Coding-interview readiness comes from recognising patterns, choosing suitable data structures, reasoning about complexity, and explaining trade-offs under time pressure.
The curriculum progresses from Complexity and Problem-Solving Framework to Interview Simulation and DSA Capstone, with guided labs, assessments, and two portfolio projects: 75-Problem Pattern Mastery Portfolio and Mock Interview Sprint.
Who this course is for
Students and developers preparing for software-engineering coding interviews.
Intermediate–AdvancedFull-Stack Software Engineer
PrerequisitesLearners should be comfortable writing basic programs in Python, Java, C++, or another interview language.
What you will be able to do
- Analyse and optimise a set of baseline solutions while explaining trade-offs aloud.
- Solve a curated set of interview problems and classify patterns.
- Implement core structures and solve cycle, stack and queue pattern problems.
- Solve tree traversal, heap and top-K problems under time constraints.
- Solve dependency, pathfinding and connectivity interview problems.
- Solve progressively harder DP and greedy problems using a repeatable framework.
- Complete multiple mock coding interviews and a final curated 50-75 problem mastery set.
Technology you will use in this course
Any interview language (Python or Java recommended)Online judgeCoding platformGitHub
Career relevance
Full-Stack Software Engineer
This course supports the development of skills for software engineering interviews and graduate developer career preparation. The strongest learner outcome is a portfolio that shows the problem, implementation, testing or evaluation, documentation and a clear explanation of decisions—not a certificate alone.
Course evidence and instruction
Discuss your learning pathway
Review prerequisites, learning format and project expectations with admissions before enrolment.
Get course guidanceExplore the course projects
Review the project briefs and deliverables to understand the work expected during the course.
Review project expectationsTechnology references
Technology names identify learning tools and do not imply an employer partnership or endorsement.
Microsoft
Clear answers before you enrol
Is the DSA for Coding Interviews course suitable for beginners?
This course progresses from intermediate to advanced level. Learners should be comfortable writing basic programs in Python, Java, C++, or another interview language.
What will I build during the course?
You will complete guided labs in every module and build two portfolio projects: 75-Problem Pattern Mastery Portfolio and Mock Interview Sprint. Deliverables include working files or code, documentation, testing or evaluation evidence, and a final presentation.
Which tools and platforms are covered?
You can use any interview language; Python or Java is recommended. Practical work also uses an online judge, a coding platform and GitHub.
How long does the course take?
The course includes approximately 80 guided learning hours across 8 modules, normally delivered over 10–12 weeks depending on batch intensity and learner practice time.
Which career paths can this course support?
The curriculum supports the development of skills for software engineering interviews and graduate developer career preparation. Career outcomes depend on prior experience, project quality, interview readiness and market conditions; employment is not guaranteed.
Will I receive mentor and career support?
The course includes live instruction, lab support, assignment feedback, project reviews and career preparation covering portfolio development, CV writing, LinkedIn profile improvement, and interview guidance.
Ready to start?
A-56, Sector-64, Noida, Uttar Pradesh – 201301Ready to start your Data Structures & Algorithms (DSA) for Coding Interviews journey?
Review the full curriculum, experience a live class and confirm the right starting point before enrolling.