How can you choose the right difficulty and category for algorithm challenges?

1 Why difficulty matters

The difficulty level of an algorithm challenge determines how hard it is to solve, how much time and effort it requires, and how many points or prizes you can earn. It also affects how much you can learn from the challenge and how confident you can feel about your solution. Generally, you want to choose a difficulty that is slightly above your comfort zone, but not too frustrating or overwhelming. This way, you can challenge yourself, improve your skills, and enjoy the process.

2 How to assess your level

Before you choose a difficulty level, you need to have a realistic idea of your current skills and knowledge. One way to do this is to take some online assessments or quizzes that measure your proficiency in algorithms, data structures, and programming languages. Another way is to look at your past performance and feedback on similar challenges or platforms. You can also compare your solutions with other programmers' solutions and see how they differ in terms of efficiency, elegance, and readability.

3 How to choose a category

The category of an algorithm challenge refers to the type of problem or domain it belongs to. For example, some common categories are sorting, searching, graph theory, dynamic programming, cryptography, and machine learning. Choosing a category depends on your interests, goals, and background. You might want to choose a category that aligns with your field of study, work, or hobby, or that exposes you to new and exciting topics. You might also want to choose a category that complements or strengthens your existing skills or that fills in your gaps or weaknesses.

4 How to balance variety and focus

While it's good to explore different categories and difficulty levels, it's also important to have some focus and consistency in your algorithm challenges. This means that you should not jump from one category or level to another without mastering the basics or applying what you learned. You should also not stick to one category or level for too long without challenging yourself or expanding your horizons. A good balance is to have a main category or level that you focus on most of the time, but also try some other ones occasionally or as a break.

5 How to use resources and tools

Choosing the right difficulty and category for algorithm challenges is not enough. To solve them, you need to use the right resources and tools, such as online tutorials, courses, books, and blogs that teach you the concepts and techniques behind algorithms and data structures. You can also benefit from online forums, communities, and mentors that offer guidance, feedback, and support. Additionally, online editors, compilers, debuggers, and testers can help you write, run, and check your code. Finally, online libraries, frameworks, and APIs provide ready-made or reusable code snippets, functions, or modules.

6 How to track your progress and results

Finally, it's important to track your progress and results as you choose and solve algorithm challenges. This will help you measure your improvement, identify strengths and weaknesses, and set goals and plans. You can accomplish this through online platforms, websites, or apps that record scores, rankings, badges, or certificates. Additionally, online portfolios, blogs, or social media can be used to showcase solutions, achievements, or reflections. Online tools, spreadsheets, or journals can be used to log time, effort, or errors. Lastly, online surveys, quizzes, or interviews can be used to test knowledge, skills, or confidence.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?