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Edua

Advanced Top 20 Training

Next Batch Starts on 27th Aug 2018

The course aims at developing both math and programming skills required for a data scientist. It allows us to get insight into data analysis problems that arise in business verticals and solving those problems using statistical and machine learning approaches. The course also focus upon the understanding fundamental math underlying those models. This course is more of practical research oreinted course than developer oriented. It focuses on 6 most common data analysis problems that arise in most business verticals: Classification, Regression, Recommender Systems, Clustering, Association Analysis and Outlier Detection.

Category: Problem Solving, Product Engineering

  • Details
  • Objectives
  • Target Audience
  • Syllabus

Technical Details

Duration 60 Hours
Prerequisites Passion, Interest & Top-20 Course
Class Room Course Available
Video Course Unvailable

Upon successful completion of Advanced Top 20 Training course, participants will be able to:

  • To enhance thinking process to solve problems algorithmically
  • To hone the skills for cracking any product company interview/written tests
  • To nurture the skills for cracking ACM & Olympiad competitions
  • To Understand the practical application of problems&their impact on software products
  • To improve the analysis skills of the algorithmic ideas
  • To 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
  • Anyone who is passionate for solving ACM & Olympiad problems
  • 1. DataStructure(Segment, Fenwik and Tournament Trees) based problem solving
  • Overview of Segment, Fenwik and Tournament Trees
  • Custom implementation vs Library support
  • Applying Segment, Fenwik and Tournament Trees
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 3. Graph problems(traversal) - I
  • Illustrating thinking process for graph problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 5. Graph problems(dag) - III
  • Illustrating thinking process for graph problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 7. Graph problems(flows) - V
  • Illustrating thinking process for graph problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 9. Advanced dynamic programming thinking for problem solving
  • Illustration of Dynamic programming thinking
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 11. Math problems(advanced) - II
  • Illustrating thinking process for solving math problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 13. File problems
  • Illustrating thinking process for solving file based problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 2. DataStructure(Disjoint Set) based problem solving
  • Overview of Disjoint Set
  • Custom implementation vs Library support
  • Applying Disjoint Set
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 4. Graph problems(spanning tree) - II
  • Illustrating thinking process for graph problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 6. Graph problems(shortest paths) - IV
  • Illustrating thinking process for graph problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 8. DataStructure(KD-Tree, QuadTree and R-Tree) based problem solving
  • Overview of KD-Tree, QuadTree and R-Tree
  • Custom implementation vs Library support
  • Applying KD-Tree, QuadTree and R-Trees
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 10. Math problems(basic) - I
  • Illustrating thinking process for solving math problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 12. Geometry problems
  • Illustrating thinking process for solving geometry problems
  • Coding interview problems
  • Competition(ACM & Olympiad) problems
  • 14. Puzzles
  • Illustrating thinking process for solving puzzles
  • Coding interview problems
  • Competition(ACM & Olympiad) problems