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good background in data structure and vs background in data structure

Both phrases are correct, but they serve different purposes. The first phrase 'good background in data structure and' emphasizes the quality of the background in data structure, while the second phrase 'background in data structure' simply states the presence of such background without specifying its quality.

Last updated: March 21, 2024 • 652 views

good background in data structure and

This phrase is correct and commonly used to emphasize the quality of the background in data structure.

This phrase is used when you want to highlight that the background in data structure is of good quality or extensive.
  • Good background in Data Structure and Algorithms Computer Graphics using OpenGL. Keen interest in research in parallel computing using CUDA ...

Alternatives:

  • strong background in data structure
  • solid background in data structure
  • excellent background in data structure
  • proficient in data structure
  • well-versed in data structure

background in data structure

This phrase is correct and commonly used to indicate the presence of knowledge or experience in data structure.

This phrase is used to simply state that someone has a background in data structure without specifying the quality or extent of that background.
  • Jul 28, 2015 ... Background in Data Structure, Algorithm; 5+ years of experience in Design, SQL and database concepts in a dimensional large data ...
  • Jul 28, 2015 ... Background in Data Structure, Algorithms; Modeling skills including Data Modeling experience; 4+ years of experience in RDMS design and ...
  • Background in Data Structure, Algorithms • Modeling skills including Data Modeling experience • Experience extracting, manipulating, and analyzing data and ...
  • The students are expected to have solid background in data structure and computer system internals. Proficiency in C programming is essential in order to be ...

Alternatives:

  • experience in data structure
  • knowledge of data structure
  • familiarity with data structure
  • understanding of data structure
  • competence in data structure

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