Data Structures and Algorithms
Develop the skills to select and assess data structures for real workloads through a learning path centred on Data Structures and Algorithms. Explore concepts, guided practice and an applied project.
Build practical Data Structures and Algorithms skills.
Skills and knowledge developed in this course.
- Complexity
- Core structures
- Algorithms
- Evaluation
- Applied project: Select and assess data structures for real workloads
- Data Structures and Algorithms — validation and review
About this course
This course develops practical capability in Data Structures and Algorithms. Its course-specific content covers Complexity, Core structures, Algorithms, Evaluation, followed by an applied project focused on select and assess data structures for real workloads. The lessons include concrete configuration, design, testing or operational decisions appropriate to the subject.
Who this is for
Administrators, developers and practitioners who work with Data Structures and Algorithms or plan to take on responsibilities in this area.
Before you start
Basic computer literacy and a foundational understanding of software architecture & engineering. Prior experience with the named product helps with the practical exercises.
Select and assess data structures for real workloads
Deliver select and assess data structures for real workloads. Use the module outcomes to state requirements, demonstrate a working result, test an expected failure or boundary case, and document assumptions and follow-up work.
Course content
Course-specific syllabus and practical exercises. Lab release, access arrangements and final delivery scope are confirmed before enrolment.
01Complexity
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- Time and space growth
- Best, average and worst-case reasoning
Practical exerciseApply complexity to the select and assess data structures for real workloads and capture the validation evidence.
02Core structures
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- Arrays, lists, stacks and queues
- Hash tables, trees and graph representations
Practical exerciseApply core structures to the select and assess data structures for real workloads and capture the validation evidence.
03Algorithms
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- Sorting, searching and traversal
- Recursion, greedy methods and dynamic programming
Practical exerciseApply algorithms to the select and assess data structures for real workloads and capture the validation evidence.
04Evaluation
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- Implement alternatives for a stated workload
- Benchmark, explain trade-offs and test edge cases
Practical exerciseApply evaluation to the select and assess data structures for real workloads and capture the validation evidence.
05Applied project: Select and assess data structures for real workloads
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- Define inputs, assumptions and acceptance criteria for: Select and assess data structures for real workloads.
- Implement the project using complexity, core structures, algorithms, evaluation.
Practical exerciseSelect and assess data structures for real workloads.
06Data Structures and Algorithms — validation and review
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- Demonstrate the completed project against its acceptance criteria.
- Exercise an invalid-input or failure scenario and document the observed result.
Practical exercisepresent the project evidence, limitations and a repeatable handover.
Technical references
These primary vendor, project or standards sources inform this independent IT Purview outline. Reference pages checked 25 October 2026; current provider documentation and exam objectives take precedence when versions change.
From understanding to application.
Progress by learning milestone. The schedule is agreed around your starting level and learning goals.
- 01Learning milestone 1 In progress
Set the context
Complexity · Core structures
Establish the Data Structures and Algorithms scope, baseline concepts and operating assumptions. - 02Learning milestone 2 In progress
Build the working skills
Algorithms · Evaluation
Apply the core Data Structures and Algorithms techniques in the course lab and record the result. - 03Learning milestone 3 In progress
Validate and handle exceptions
Check expected behavior, investigate a failure case and capture evidence for select and assess data structures for real workloads. - 04Learning milestone 4 In progress
Deliver the applied project
Complete select and assess data structures for real workloads, explain key decisions and identify a practical next step.
Career outlook after this learning path
Typical roles this roadmap can support, with broad salary ranges by relevant work experience.
| Role | 0–3 years | 3–7 years | 7–12+ years |
|---|---|---|---|
| Software Engineer | ₹5–12 LPA | ₹14–26 LPA | ₹28–48 LPA |
Ranges are indicative India-market compensation estimates in ₹ lakh per annum, not a salary promise. They reflect broad market guides and vary by location, employer, skills and role scope; the experience bands refer to relevant work experience, not time since training. Completing this course does not guarantee employment, a role, compensation or career progression. View market reference ↗