Data Structures and AlgorithmsSelf Paced CourseLearn Data Structures & Algorithms at your own pace.

This course is a complete package that helps you learn Data Structures and Algorithms from basic to an advanced level. The course curriculum has been divided into 10 weeks where you can practice questions & attempt the assessment tests according to your own pace. The course offers you a wealth of programming challenges that will help you to prepare for interviews with top-notch companies like Microsoft, Amazon, Adobe etc.

You will learn algorithmic techniques for solving various problems with full flexibility of time. With this course, you can study at your own pace and need not hurry or puzzle yourself.

This course does not require any prior knowledge of Data Structure and Algorithms, but a basic knowledge of any programming language ( C++ / Java) will be helpful

What You Will Learn

• Learn Data Structures and Algorithms from basic to advanced level

• Learn Topic-wise implementation of different Data Structures & Algorithms

• Improve your problem-solving skills to become a stronger developer

• Develop your analytical skills on Data Structures and use them efficiently

• Solve problems asked in product-based companies’ interviews

• Solve problems in contests similar to coding round for SDE role

Course Features

• 200+ algorithmic coding problems

• Lifetime access to the Course

• Track-based learning

• Weekly assessment tests

• Premium Lecture videos by Mr. Sandeep Jain (CEO & Founder, GeeksforGeeks)

• Course Completion Certificate trusted by top universities and companies

• Internship Opportunities at GeeksforGeeks

• Access to the GeeksforGeeks Jobs portal

Course Content   Introduction

• Analysis of Algorithm 
  

  • Background analysis through a Program and its functions.

• Order of Growth 
  

  • A mathematical explanation of the growth analysis through limits and functions.

  • A direct way of calculating the order of growth

• Asymptotic Notations
  

  • Best, Average and Worst case explanation through a program.

• Big O Notation
  

  • Graphical and mathematical explanation.

  • Calculation

  • Applications at Linear Search

• Omega Notation
  

  • Graphical and mathematical explanation.

  • Calculation.

• Theta Notation
  

  • Graphical and mathematical explanation.

  • Calculation.

• Analysis of common loops
  

  • Single, multiple and nested loops

• Analysis of Recursion
  

  • Various calculations through Recursion Tree method

• Space Complexity 
  

  • Basic Programs

  • Auxiliary Space

  • Space Analysis of Recursion

  • Space Analysis of Fibonacci number

• Practice Problems
  

  • This track contains many practice problems for the users which are considered important and must-do as far as Data Structure and Algorithm is concerned.

  Mathematics   Bit Magic   Recursion   Arrays   Searching Show More

FAQs