Sameer A. provides algorithms assignment help for university students who want expert explanations of problem solving, complexity and implementation. He holds an MTech in Computer Science from the Indian Institute of Technology Bombay, India, awarded in 2015, and has 8 years of experience in computing, algorithms and Python.
Sameer works in English, Hindi and Urdu, so students in the UK and Saudi Arabia can discuss difficult topics in the language that suits them best.
Through FIZ Business Solutions, students can get help understanding algorithm design, analysing running time, debugging Python code, writing proofs of correctness and reviewing technical reports.
Algorithms assignments Sameer can help with
Algorithms and data structures modules are core to most computer science degrees. Assessments test both theory and practical coding, and many students find the step from lecture notes to written proofs challenging.
- Data structures assignment help: arrays, linked lists, stacks, queues, heaps, hash tables and trees
- Sorting and searching algorithms with complexity analysis
- Graph algorithms: BFS, DFS, Dijkstra, Bellman-Ford, Prim and Kruskal
- Dynamic programming and greedy algorithm problems
- Recursion, divide and conquer and recurrence relations
- Python programming help for implementation and testing
Key theory and methods
Strong algorithm analysis shows clear reasoning, not only a working program. Sameer explains the theory students need to justify their solutions:
- Big O, Big Omega and Big Theta notation
- Best, average and worst case analysis
- The Master Theorem and substitution method for recurrences
- Loop invariants and proofs of correctness
- Amortised analysis for dynamic arrays and similar structures
- Introductory complexity classes: P, NP and NP-completeness
Common mistakes and what UK markers look for
Students often lose marks by stating a time complexity without showing how it was derived. Markers want to see the reasoning: which operations dominate, how many times loops run and how recursive calls grow.
Other frequent issues include ignoring edge cases such as empty inputs, confusing space and time complexity, using built-in functions that hide the algorithm being assessed, and submitting code without tests. Pseudocode that does not match the final implementation is also a common problem.
UK markers look for precise definitions, correct notation, clean and commented code, sensible test cases and a short evaluation of efficiency. Sameer reviews work with these expectations in mind and explains how to improve it.
Example algorithms topics
A good project topic lets students show both coding skill and analytical depth. Sameer can help students choose a topic that is challenging but achievable within the deadline. Typical coursework and project topics include:
- Comparing the performance of sorting algorithms on different input sizes
- Shortest path routing for a transport network
- Solving the knapsack problem with dynamic programming
- Implementing and analysing a balanced binary search tree
- Heuristic approaches to the travelling salesman problem
How Sameer supports each stage of your assignment
Algorithms coursework usually asks students to do three things: design a solution, implement it, and analyse it. Many students are comfortable with one of these but not the others. Sameer can support whichever stage is causing difficulty.
At the design stage, he helps students recognise the type of problem they are facing. Knowing whether a task calls for a greedy choice, dynamic programming, graph search or a divide and conquer approach is often the hardest step, and he explains the clues that point towards each technique.
For implementation, Sameer explains how to translate pseudocode into clean Python, choose the right built-in data structures, and write tests that cover normal, boundary and invalid inputs. Students who share their code can get clear explanations of bugs, inefficiencies and style issues.
For analysis, he shows how to count operations, set up and solve recurrences, and present empirical timing results alongside theoretical bounds. Plotting running time against input size and comparing it with the expected growth rate is a simple way to strengthen a report, and he can explain how to do this properly.
- Identifying the right algorithmic technique for a problem
- Writing pseudocode that matches the final implementation
- Designing test cases and measuring performance
- Presenting complexity proofs clearly and concisely
How working with FIZBS works
Getting algorithms assignment help from Sameer is straightforward. Share your brief, marking scheme and any starter code on WhatsApp. FIZBS reviews the task and gives you a clear price, starting from £20 per 1,000 words, with coding tasks quoted according to scope.
You pay 50% to start and 50% on completion. You receive updates until the deadline, so you can ask questions and understand each part of the solution as it develops.