Alejandro Do you dream of becoming a tech entrepreneur? Perhaps you hope to create a global brand recognized by millions of users worldwide. Or maybe you aspire to achieve employment with one of the major global players in the tech industry.
Whether you hope to create a tech giant of the future or work with the likes of Google, Apple, or Microsoft, there are a few things you need to do first. The first thing you need to do is to build your knowledge and skills so that you have the foundations for success.
Knowledge is power, and developing your knowledge and expertise is essential for a career in this industry. If you want a successful future in software engineering, now is the time to take action. Understanding data structures and algorithms is vital for a career in this field.
In this blog, I will help you to master these vital skills using easy tips and tricks to make the learning process as simple and effective as possible for you.
Why it is Essential to Master Data Structures and Algorithms
Data is increasingly important to businesses, and this is set to continue. According to Experian’s 2022 Global Data Management Report, 88% of businesses say that being data-driven helps them stay on top of customer needs and market trends. This can help businesses to enjoy a competitive advantage and increased profits. But, to achieve these benefits, companies need tech experts that can facilitate data organization; this is where you can help.
Having demonstrable knowledge of data structures and algorithms will help you stand out from other candidates when applying for roles. However, knowing how to get better at data structures and algorithms can be challenging.
To help you further your understanding of data structures and algorithms, I have gathered together these top tips and tricks. Mastering these key areas will give you a significant advantage when applying for jobs in the software engineering industry. Read on to learn all you need to know and start developing your knowledge today:
Familiarize Yourself With Common Data Structures
Getting to grips with data structures can seem intimidating. But familiarizing yourself with each of the common data structures is an excellent place to start.
As data structures are fundamental to improving data storage and efficiency, you are likely to be asked a question about them during an interview.
Here are some of the most widely-used data structures to familiarize yourself with:
- Arrays and lists
- Binary trees
- Stacks
- Queues
- Graphs
- Maps
- Linked lists
This isn’t an exhaustive list, so if you want to expand your knowledge further, there are more data structures to learn about.
Understand Algorithm Categories
Algorithms are sets of ordered instructions that facilitate a pre-defined task being completed.
Algorithms can be organized into several different categories. So familiarizing yourself with these and learning all you can about each category is really helpful.
The main algorithm categories are as follows:
- Dynamic programming
- Graph traversing
- Search
- Sorting
- String pattern matching
Focus on the Depth-First Approach
When it comes to mastering coding problems, more is not always better. Many people focus on improving the breadth of their problem-solving. This means that you will often hear people boast that they can solve hundreds of coding problems. However, focusing on depth rather than breadth is more beneficial to your overall understanding of the subject.
Focusing on the depth-first approach will help you to build a strong understanding of coding. Your problem-solving skills will be significantly improved when you choose the depth-first approach, so I always recommend this as an area to focus on.
While having a breadth of knowledge is helpful, the depth-first approach will equip you with the understanding needed to solve problems quickly and easily. This is an essential skill to learn when you are faced with the pressure of an interview situation.
You may be wondering why this depth-first approach matters so much. This is because being able to code fast and efficiently is vital for interviews. Interviews require a deeper level of problem-solving. So, building a strong knowledge base for deep problem-solving will provide a solid foundation for you to work from, making interviews so much easier to handle.
Make a List of Core Questions
Creating a list of core questions that address common problems has many benefits when you are trying to improve the depth of your coding knowledge:
- You will understand how to write clean code effortlessly.
- You can demonstrate correct use of syntax during interviews, showing potential employers that you are efficient and can get it correct the first time.
- You will develop such a strong understanding of data structures that they will each feel familiar to you, allowing you to implement the relevant structure with ease.
- You will have a strong knowledge base that allows you to apply the same familiar code to new problems and solve them fast.
While covering a wide breadth of different questions will enable you to apply your knowledge generally to many areas, it is focusing on depth-first questions that will give you a thorough understanding.
Keep Practicing
Practice is essential when it comes to mastering data structures and algorithms. To excel in interviews, data structure internals need to become second nature to you. Being able to implement these confidently and at speed is vital if you want to impress during interviews.
Keep in mind that one thing that many people overlook before going to interviews is how they will be asked to demonstrate their skills. You may have mastered coding on your computer. But did you know that many companies don’t provide an IDE when you come for your interview?
Practice on Paper
If you are invited along to a face-to-face, in-person interview, you may be asked to demonstrate your skills in a different way. Instead of putting your skills to the test using an IDE, for the technical aspect of your interview, you may be asked to code on paper or on a whiteboard.
So, if you are unsure of the most effective way to practice data structures, I would advise you that the simplest ways are the best. So, grabbing a pen and practicing implementing data structures on paper or on a whiteboard is a great way to cement your knowledge in preparation for interviews.
By continuing to practice on paper, you should soon master the data structure internals. You will also feel more comfortable working on paper or on a whiteboard. This means that being asked to do the same during a technical interview should be far less intimidating.
Identify Patterns
As you work your way through and keep practicing on both an IDE and on paper, you should notice some patterns along the way. After becoming familiar with solving problems using binary code, you may want to go a step further. Isolating the code and then memorizing it is extremely useful. This allows you to then use it to solve any future problems you come across.
By isolating and memorizing the code, you should find you make progress very quickly.
Test Your Knowledge
Once you feel confident, you may wish to expand your knowledge even further. You can do this by setting yourself increasingly more complicated problems. Choosing to work on non-typical problems is an excellent way to push your skills and knowledge further. Just be sure that you do this gradually so that you can fully master what you are doing. Trying to tackle highly-complex problems before you are ready to do so can become confusing and lead to you feeling frustrated. So, taking things slowly and only approaching more complex, non-typical problems when you are ready is vital.
Avoid Learning Burnout
Learning burnout is a common issue that impacts students. According to the American College Health Association’s National College Health Assessment, 80% of college students feel overwhelmed.
Attempting to do too much all at once is a common reason for learning burnout. Trying to cram for exams or interviews is an example of this. Attempting to learn lots of new information in a short space of time can leave you feeling anxious and overwhelmed. Unfortunately, this can make it harder to retain information.
To avoid learning burnout, it is helpful to take a different approach to mastering data structures and algorithms. Using the spaced repetition technique is especially helpful for this. By learning new information and allowing gaps in time before you revisit it, you should be able to retain your learning more efficiently.
Look for Further Learning Opportunities
There are always opportunities to learn, and continually improving your skills is an excellent way to make you a more attractive candidate to future employers.
To advance your knowledge of data structures and algorithms, it can be helpful to read widely on the subject. But for a more focused learning approach, taking an online course could be the perfect way to fully master the subject.
