Learn Data Structures
2 expert-rated courses covering Data Structures. Compared by rating, price, difficulty, and job relevance so you can pick the right one.
Proficiency in data structures is highly valued across the tech industry, from software engineering and cybersecurity to data analysis and product management. According to Glassdoor, the average salary for a data structures engineer in the US is $117,000, and demand is projected to grow 22% by 2026. Building complementary skills in algorithms, programming languages, and problem-solving can further enhance a data structures specialist's career prospects.
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Key Facts About Data Structures
- 1Data structures are the building blocks of computer programs, defining how data is stored and manipulated.
- 2The most common data structures are arrays, linked lists, stacks, queues, trees, and graphs.
- 3Efficient data structure implementation is crucial for optimizing time and space complexity of algorithms.
- 4Data structures underpin a wide range of applications, from operating systems and databases to AI and machine learning.
- 5Mastering data structures requires a deep understanding of fundamental programming concepts and problem-solving skills.
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Top Data Structures Courses
Data Structures in Python
In this course, you’ll explore data structures in Python, which are methods of storing and organizing data in a computer. You’ll focus on data structures that are among the most useful for data professionals: lists, tuples, dictionaries, sets, and arrays. You’ll also discover how to categorize data using data loading, cleaning, and binning. Lastly, you’ll learn about two of the most widely used and important Python tools for advanced data analysis: NumPy and pandas. By the end of this course, you will be able to: • Explain how to manipulate dataframes using techniques such as selecting and indexing, boolean masking, grouping and aggregating, and merging and joining • Describe the main features and methods of core pandas data structures such as dataframes • Describe the main features and methods of core NumPy data structures such as arrays and series • Define Python tools such as libraries, packages, modules, and global variables • Describe the main features and methods of built-in Python data structures such as lists, tuples, dictionaries, and sets
Programming in Python
Comprehensive introduction to Python programming covering data structures, control flow, functions, and object-oriented programming. Build a strong foundation in one of the most popular programming languages.
Pro Tips for Learning Data Structures
- #1Practice implementing common data structures from scratch to deeply understand their properties and tradeoffs.
- #2Familiarize yourself with common operations (e.g., insertion, deletion, search) and their time complexities.
- #3Supplement your learning with real-world examples and use cases to see data structures in action.
- #4Build a strong foundation in programming concepts like pointers, memory management, and runtime analysis.
Why Learn Data Structures?
- Gain a competitive edge in the tech industry by developing expertise in essential data structures.
- Unlock the ability to design and implement efficient algorithms for complex software applications.
- Enhance your problem-solving skills and logical thinking, valuable for a wide range of tech roles.
- Prepare for technical interviews, where data structures and algorithms are often a focus.