Have any question? +91 92 4658 2537 info@algorithmica.co.in
Edua

Top 20 Training

Next Batch Starts on 08th Oct 2018

Any successful software product is always produced with the efforts from team of good software engineers. A good software engineer must possess good problem solving skills. Most of the product companies like Google, Wallmart labs, Yahoo, Facebook, MicroSoft, Adobe, Rediff, Amazon, Fair Issac, D E Shaw, QualComm, ComVault, Oracle etc..., need software engineers who had excellent problem solving skills.

This course provides a platform to improve your problem solving skills besides providing strong fundamental knowledge on DataStructues and Algorithms. The course focuses more on discussions in the class which allows the participants to come up with new ideas.

Category: Problem Solving, Product Engineering

  • Details
  • Objectives
  • Target Audience
  • Syllabus

Technical Details

Duration 100 Hours
Prerequisites Passion, Interest
Class Room Course Available
Video Course Unvailable

Upon successful completion of “Top-20 Training” course, participants will be able to:

  • Enhance Thinking process
  • Crack any product company interview/written tests
  • Understand the practical application of problems&their impact on software products
  • Think through the solution techniques to any problem
  • Improve the analysis skills of the algorithms generated by themselves/others
  • Enhance the coding skills to maximum possible level
  • People under any of these following categories

  • Any under-graduate/graduate students from Universities, RECs, NITs, IIITs and IITs
  • Self motivated candidates from any college who want to crack big companies
  • Students who already had job offer(s) and aspire to join Big League
  • Students who want in-depth knowledge in Data Structures, Algorithms&Programming
  • Working software professionals who are looking for better opportunities in product based software companies
  • Any passionate student/working professional who wants to understand the fundamentals of computer science which are mandatory for any software developer
  • 1. Overview of problem solving using computing devices
  • Anatomy of typical computer
  • Understanding computer based problem solving
  • Understanding need of algorithmic thinking
  • Problem solving framework - Algorithmic Analysis(Asymptotic) and coding
  • Coding Interviews vs Competitions(ACM vs Olympiad)
  • Tricks/Tips for winning competitions and interviews
  • 3. Divide & Prune thinking for problem solving
  • Data Life Cycle for Analysis
  • Technologies for Data Science/Analytics
  • Single Machine Analytic Platforms: R, Python
  • Distributed Analytical Platforms: Hadoop, Spark, H20
  • Datasets for doing data science/analytics
  • 5. DataStructure(Set and Map) based problem solving
  • Overview of Set, Map, MultiSet and MultiMap
  • Custom implementation vs Library support
  • Applying Set and Map
  • Coding interview problems
  • Competition(Interview, ACM & Olympiad) problems
  • 7. Linked list problems(advanced) - II
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 9. Binary tree problems(basic) - I
  • Illustrating thinking process for solving tree problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 11. Search tree problems
  • Illustrating thinking process for solving search tree problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 13. DataStructure(Heap & Priority Queue) based problem solving
  • Overview of Heap and Priority Queue
  • Custom implementation vs Library support
  • Applying Heap and Priority Queue
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 15. Dynamic Programming(1-d) thinking for problem solving - I
  • Illustration of Dynamic programming thinking
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 17. Complete Search thinking for problem solving - I
  • Illustration of complete search thinking
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 19. Combinatorics problems
  • Illustrating thinking process for solving combinatorial problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 21. DataStructure(SuffixArray, SuffixTree and Suffix Automata) based problem solving
  • Overview of SuffixArray, SuffixTree and Suffix Automata
  • Custom implementation vs Library support
  • Applying SuffixArray, SuffixTree and SuffixAutomata
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 23. Sorting & Selection problems
  • Illustrating thinking process for solving combinatorial problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 2. Adhoc thinking for problem solving
  • Illustrating adhoc thinking ideas
  • Asymptotic & amortized analysis
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 4. DataStructure(List, Stack, Queue and Deque) based problem solving
  • Overview of List, Stack, Queue and Deque
  • Custom implementation vs Library support
  • Applying Stack, Queue and Deque
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 6. Linked list problems(basic) - I
  • llustrating thinking process for solving linked list problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 8. Recursive thinking for problem solving
  • Illustration of Recursive thinking
  • Recursion vs Divide and conquer thinking
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 10. Binary tree problems(advanced) - II
  • Illustrating thinking process for solving tree problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 12. DataStructure(Sortedset and Sortedmap) based problem solving
  • Overview of SortedSet, SortedMap, SortedMultiset and SortedMultimap
  • Custom implementation vs Library support
  • Applying Sortedset and Sortedmap
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 14. Greedy thinking for problem solving
  • Illustration of Greedy thinking
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 16. Dynamic Programming(2-d)thinking for problem solving - II
  • Illustration of Dynamic programming thinking
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 18. Backtracking thinking for problem solving - II
  • Illustration of Backtracking thinking
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 20. DataStructure(Trie) based problem solving
  • Overview of SimpleTrie, RadixTrie
  • Custom implementation vs Library support
  • Applying SimpleTrie & RadixTrie
  • KNN Regression
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 22. String problems
  • Illustrating thinking process for solving string problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 24. Bitwise thinking for problem solving
  • Illustration of thinking process for solving bitwise problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems