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Thursday, February 1, 2024

5 Free College Programs to Ace Coding Interviews

5 Free University Courses to Ace Coding Interviews
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Given how aggressive the tech job market is true now, it’s best to continually upskill and enhance your technical chops. For any position in knowledge and software program engineering, the interview course of usually begins with a spherical or two of coding interviews. 

Whereas tasks and technical experience will show you how to within the later rounds of the interview, coding interviews are sometimes exhausting to crack—particularly should you haven’t been practising for some time. And having a rock stable basis in knowledge buildings and algorithms is critical.

Even when you do not have a CS diploma, taking university-level programs in programming, knowledge buildings, and algorithms will show you how to put together for coding interviews. As a result of studying the basics adopted by a number of weeks of deliberate observe are each required for cracking coding interviews. 

We’ve compiled a listing of free college programs that can assist you be taught knowledge buildings and algorithms. So let’s go over them.



Programming, Knowledge Constructions, and Algorithms Utilizing Python taught by Prof. Madhavan Mukund at Chennai Mathematical Institute is a good first course in knowledge buildings and algorithms utilizing Python.

When making ready for coding interviews, you usually have to know superior ideas. And chances are you’ll discover some college programs troublesome to observe alongside. So this can be a good first course if you have not beforehand taken a course in knowledge buildings in algorithms.

I took this course throughout my undergrad days and located it tremendous useful. I extremely advocate taking this course first earlier than continuing to the opposite programs. 

This course has about 8 weeks of content material. Right here’s an outline of what the course covers:

  • Introduction to programming 
  • Fundamentals of Python 
  • Search algorithms 
  • Sorting algorithms 
  • Constructed-in knowledge buildings in Python 
  • Exception dealing with, file I/O, and string processing 
  • Backtracking 
  • Knowledge buildings corresponding to stacks, queues, and heaps 
  • Lessons, objects, and user-defined knowledge sorts
  • Dynamic programming

Course hyperlink: Programming, Knowledge Constructions and Algorithms Utilizing Python



Algorithmic Toolbox from UC San Diego is a good course to be taught the basics of drawback fixing strategies that’ll show you how to deal with coding interviews.  

You’ll be taught to first code a brute-force resolution that works, regularly transferring to extra optimum options whereas studying strategies like dynamic programming. You’ll be able to audit the course without cost on Coursera and use a language that you just’re snug programming in. 

This course ought to take you just a few weeks to work via. If you happen to’re , you may as well audit the complete Knowledge Constructions and Algorithms specialization for a extra full studying path.

The course contents embrace:

  • Programming challenges 
  • Looking out and sorting algorithms
  • Grasping algorithms 
  • Divide and conquer
  • Dynamic programming

Course hyperlink: Algorithmic Toolbox



Introduction to Algorithms from MIT is among the hottest extremely really useful algorithms programs.

When you have some programming expertise and are already aware of the fundamentals of information buildings and algorithms, then this course will show you how to degree up. And be taught the fundamentals of widespread knowledge buildings algorithms and algorithmic paradigms.

You’ll be able to entry the course supplies: lecture notes, drawback units, and options without cost on the course web site. Right here’s an outline of what the course covers:

  • Computational complexity of algorithms 
  • Looking out and sorting 
  • Graph algorithms 
  • Dynamic programming

Course hyperlink: Introduction to Algorithms 



Thought by Prof. Tim Roughgarden throughout his time at Stanford college, the Design and Evaluation of Algorithms programs (this half and the subsequent) will show you how to push your self exhausting to enhance your algorithmic considering and problem-solving expertise.

When you have the time throughout interview prep, I like to recommend taking this course and the subsequent. It’ll be useful to have a robust basis from a number of of the earlier programs earlier than you dive into this algorithms course.

Partly 1 of this course on design and evaluation of algorithms you’ll be taught:

  • Large-O notation 
  • Looking out and sorting 
  • Divide and conquer 
  • Randomized algorithms 
  • Knowledge buildings corresponding to hash tables and Bloom filters 
  • Algorithms on graphs 

Course hyperlink: Algorithms: Design and Evaluation, Half 1



On this half 2 of the Design and Evaluation of Algorithms course, you’ll get to be taught extra superior ideas together with:

  • Grasping algorithms 
  • Dynamic programming 
  • NP completeness 
  • Heuristics evaluation 
  • Native search

You’ll be able to watch the lectures on YouTube or audit the course without cost on edX. These programs are additionally obtainable as a five-course specialization on Coursera. So should you want this model, you may audit this Algorithms Specialization without cost on Coursera.

Course hyperlink: Algorithms: Design and Evaluation, Half 2



I hope you discovered helpful assets to assist in your coding interview prep. 

Earlier than you begin making ready for coding interviews, nonetheless, it’s best to refresh programming ideas and give attention to changing into aware of the options of the particular language. It will show you how to select the suitable built-in knowledge buildings to design algorithms with the optimum area and runtime complexity.

Good luck cracking coding interviews and touchdown your dream position! If you happen to’re in search of some actionable recommendations on touchdown knowledge science jobs, try 7 Causes Why You are Struggling to Land a Knowledge Science Job.

Bala Priya C is a developer and technical author from India. She likes working on the intersection of math, programming, knowledge science, and content material creation. Her areas of curiosity and experience embrace DevOps, knowledge science, and pure language processing. She enjoys studying, writing, coding, and occasional! At the moment, she’s engaged on studying and sharing her data with the developer neighborhood by authoring tutorials, how-to guides, opinion items, and extra.

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