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Given how competitive the tech job market is right now, you need to constantly improve your technical skills. For any position in software and data engineering, the interview process typically begins with one or two rounds of coding interviews.
While projects and technical experience will help you in the later rounds of the interview, coding interviews are often difficult to crack, especially if you haven't been practicing for a while. And it is necessary to have a solid foundation in data structures and algorithms.
Even if you don't have a computer science degree, taking college-level courses in programming, data structures, and algorithms will help you prepare for coding interviews. Because cracking coding interviews requires learning the fundamentals followed by several weeks of deliberate practice.
We've compiled a list of free college courses to help you learn data structures and algorithms. So let's review them.
Programming, data structures and algorithms using Python Taught by Prof. Madhavan Mukund at the Chennai Institute of Mathematics, it is an excellent first course on data structures and algorithms using Python.
When preparing for coding interviews, it is often necessary to understand advanced concepts. And you may find some college courses difficult to follow. So this is a good first course if you haven't previously taken a course on data structures in algorithms.
I took this course during my college days and found it very useful. I highly recommend taking this course first before moving on to the other courses.
This course has approximately 8 weeks of content. Here is an overview of what the course covers:
- Introduction to programming
- Python Basics
- Search algorithms
- Classification algorithms
- Built-in data structures in Python
- Exception Handling, File I/O, and String Processing
- Back
- Data structures such as stacks, queues, and heaps
- User-defined classes, objects, and data types
- Dynamic programming
Course link: Programming, data structures and algorithms using Python
Algorithmic toolbox from UC San Diego is a great course to learn the fundamentals of problem-solving techniques that will help you tackle coding interviews.
You'll first learn how to code a brute force solution that works and gradually move on to more optimal solutions while learning techniques like dynamic programming. You can audit the course for free on Coursera and use a language you are comfortable programming in.
This course should take you a few weeks to complete. If you are interested, you can also audit the entire Specialization in Data Structures and Algorithms for a more complete learning path.
Course contents include:
- Programming challenges
- Search and classification algorithms.
- Greedy algorithms
- Divide and conquer
- Dynamic programming
Course link: Algorithmic toolbox
Introduction to algorithms from MIT is one of the most popular and recommended algorithms courses.
If you have some programming experience and are already familiar with the basics of data structures and algorithms, this course will help you level up. And learn the basics of data structures algorithms and common algorithmic paradigms.
You can access the course materials: notes, problem sets, and solutions for free on the course website. Here is an overview of what the course covers:
- Computational complexity of algorithms.
- Searching and sorting
- Graphic algorithms
- Dynamic programming
Course link: Introduction to algorithms
Thought up by Prof. Tim Roughgarden during his stay at Stanford University, the Algorithm Design and Analysis Courses (this part and the next part) will help you work hard to improve your algorithmic thinking and problem-solving skills.
If you have time during interview preparation, I recommend taking this course and the next one. It will be helpful to have a solid foundation from one or more of the previous courses before diving into this algorithms course.
In part 1 of this course on algorithm design and analysis you will learn:
- Big O Notation
- Searching and sorting
- Divide and conquer
- Random algorithms
- Data structures such as hash tables and Bloom filters.
- Algorithms in graphs
Course link: Algorithms: design and analysis, part 1
In this part 2 of the Algorithm Design and Analysis courseYou will learn more advanced concepts including:
- Greedy algorithms
- Dynamic programming
- NP integrity
- Heuristic analysis
- Local search
You can watch the lectures on YouTube or attend the course for free on edX. These courses are also available as a five-course specialization on Coursera. So if you prefer this version, you can audit this Specialization in Algorithms free on Coursera.
Course link: Algorithms: design and analysis, part 2
I hope you found useful resources to help you prepare for your coding interview.
However, before you start preparing for coding interviews, you should brush up on programming concepts and focus on familiarizing yourself with the features of the specific language. This will help you choose the right built-in data structures to design algorithms with the optimal space and runtime complexity.
Good luck with coding interviews and landing your dream position! If you're looking for some practical tips for landing data science jobs, check out 7 Reasons Why You're Struggling to Get a Data Science Job.
Bala Priya C. is a developer and technical writer from India. He enjoys working at the intersection of mathematics, programming, data science, and content creation. His areas of interest and expertise include DevOps, data science, and natural language processing. He likes to read, write, code and drink coffee! Currently, he is working to learn and share his knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more.
