Data Structures and Algorithms are essential in Java to develop more reliable programs to solve real-world problems. Data Science engineers and developers are in huge demand to meet the current need for technology. We have compiled a list of courses to help you kick-start your career in a rising field to achieve your future objectives.
Best Data Structure and Algorithm Courses
1. JavaScript Algorithms and Data Structures Masterclass
This course is well suited for developers and students who are looking to expand their knowledge and grow in the field of technology. It is also highly recommended for those who want to improve their skills in problem solving and analysis.
The course covers topics such as:
- Basics of Big O and timing operations.
- Using Big O and simplifying its expressions.
- Learning about Space Complexity.
- Learning to analyze the performance of Arrays.
- Learning methods of Big O.
- Understanding objects of Big O.
- Learning the methods and fundamentals of problem-solving.
- Understanding patterns in problem-solving and implementing them.
- Analyzing frequency counter patterns and multiple pointer patterns.
- Working with divide and conquer patterns.
- Learning Recursion and its various practices.
- Basics of Search, Binary Search, and Linear Search.
- Working with Binary search solutions.
- Using Linear Search in Big O.
On completing the course, students can apply for jobs in problem-solving. They can also advance their current careers in development or work on independent projects to solve real-world problems.
Prerequisites: A fundamental understanding of Javascript syntax.
Level: Beginner
Rating: 4.7
Duration: 21 hours and 51 minutes
You can sign up here
2. Master the Coding Interview: Data Structures + Algorithms
This ultimate Bootcamp course is designed to prepare candidates for interviews in data structures and algorithms. The course provides a consolidated guide to crack interviews and get the desirable jobs.
The course covers topics such as:
- Creating an attractive resume to attract companies.
- Creating a remarkable portfolio, even if there is less experience to add.
- Guidelines to apply for jobs (how to apply and where).
- Learning the rules of Big O.
- Exercising Big O Calculations to solve problems.
- Learning about Space complexity.
- Learning to solve problems in Coding.
- Fundamentals of Data Structures and their operations.
- Learning the basics of Array.
- Learning the differences between static and dynamic Array.
- Learning about strings and arrays.
- Working on merging arrays.
- Working with Hash Tables in Data Structures.
- Working with linked lists.
- Working with stacks and queues.
- Working with Trees in Data Structures.
On completing the course, students can apply for better job offers. They can also request appraisals and negotiate for better pay structures.
Prerequisites: Understanding of at least one programming language.
Level: Beginner
Rating: 4.7
Duration: 19 hours and 33 minutes
You can sign up here
3. Data Structures and Algorithm Specialization
This course is targeted to acquire the necessary skills to work in data science and development. The course takes an in-depth plunge into understanding and formulating algorithms to solve problems.
The course covers topics such as:
- Learning the basics of algorithms.
- Applying techniques such as binary search, greedy algorithms, dynamic programming, and sorting methods solve problems.
- Learning to apply various data structure methodologies such as hash tables, stacks, queues, graphs, and binary search trees to sort through programming trials.
- Applying techniques of data structures and algorithms to solve real-world problems.
- Using string algorithms with graphs to find shortcuts to sort huge maps and assemble data from various sources.
- Learning to use linear programming.
- Implementing maximum flow and approximate algorithms.
- Learning to test software.
- Learning to debug programs.
- Learning to create priority queues
On completing the course, students can easily apply for jobs in data science and programming. They can also work in quality control. Pay raises can be negotiated based on the new and improved skill set. Students get a hands-on approach to an applied project to strengthen their knowledge on the subject.
Prerequisites: The website does not mention any prerequisites.
Level: Intermediate
Rating: 4.6
Duration: 8 months
You can sign up here
4. Mastering Data Structures and Algorithms using C and C++
This program is based on programming with C and C++. These languages are used in the data structure to analyze patterns and implement solutions. Students learn to use data structure components such as sorting and recursion and apply them to projects to find real-time solutions.
The course covers topics such as:
- Learning the basics of data structure.
- Working with various widely practised parameters in data structure and algorithm.
- Learning the basics of pointers, arrays, structures, and functions.
- Setting up of Dev C++, Code blocks, and their respective settings.
- Debugging software and projects.
- Setting up Visual Studio and Xcode.
- Learning forms of Stacks and Heap Memory and their various functions.
- Learning the concepts of Space and Time Complexity.
- Learning the fundamentals of Recursion and how to use it in Data Science.
- Discussing the various aspects of Recursion such as Head and Tail Recursion, Indirect Recursion, Nested Recursion, etc.
- Performing Factorials using Recursion.
- Learning representation of Arrays, Sparse Matrix, and Polynomials.
- Using Strings and Matrices.
- Learning to use Stacks, Trees Queues, and Heaps in Data Structure.
On completing the course, students can get more comfortable using Data Structures and programming in Data science. They can apply for jobs in analysis and problem-solving. Students can also work as programmers and quality controllers.
Prerequisites: Programming knowledge in C and C++
Level: Beginner
Rating: 4.6
Duration: 56 hours and 30 minutes
You can sign up here
5. Data Structures and Algorithms - The Complete Masterclass
This comprehensive course is aimed at students who want to crack a programming interview and acquire a high-paying job in Data Science. The course discusses various principles of Data Structure and Algorithm, along with tips and tricks to ace an interview.
The course covers topics such as:
- Basics of Data Structures and Algorithms.
- Understanding various complexities of algorithms and why and how they are used to solve problems.
- Using Logarithms.
- Learning the functionalities of Big O.
- Understanding the types of Array, such as 1D Array, 2D Array, etc.
- Creating memory-efficient DLL
- Using Hash Tables and Linked Lists.
- Theories on Stacks, Queues, and Trees in Data Structure
- Visualizing and using graph theories.
- Practising methods to find the shortest paths in Algorithms.
On completing the course, students can compete against fellow data science engineers for promotions. They can easily crack interviews in Data Science and find solutions to problems using their session techniques.
Prerequisites: There are no prerequisites for this course.
Level: Beginner
Rating: 4.6
Duration: 7 hours and 43 minutes
You can sign up here
6. Intro to Data Structures and Algorithms
This course is a minefield of information on cracking interviews. It teaches students the commonly used data structure and algorithm with Python. They help candidates familiarize themselves with interview patterns to navigate their way to the top quickly.
The course covers topics such as:
- Introduction to Data Structures and Algorithms.
- Learning the connotations of Efficiency and practising it first hand
- Learning the fundamentals and applications of lists.
- Learning and implementing arrays
- Working with stacks and queues.
- Learning to manipulate the components of data structures.
- Learning to search and sort.
- Working with binary search and bubble sort.
- Learning to use merge, insertion sort, and quicksort.
- Learning the concepts and implementation of sets, hashing, and maps.
- Practising to work with trees and graphs in data structures.
- Exploring case studies in the algorithm.
- Practising Technical Interview.
On completing the course, students are well-equipped to crack interviews. They can easily negotiate pay raises or changes in roles at their organization. They can also apply in multinational projects for interviews, having practised the skills thoroughly.
Prerequisites: An intermediate understanding of Python and Algebra.
Level: Intermediate
Rating: 4.5
Duration: 4 weeks
You can sign up here
7. Practical Data Structures and Algorithms in Java + HW
This course provides a consolidated source for information on data structures and algorithms. It also prepares students for interviews for jobs in data science. The course will teach students everything they need to know about the subject, so the interview process is relatively easier.
The course covers topics such as:
- Learn to use program flow and constructors.
- Learn how Java impacts programming.
- Practice object-oriented programming.
- Learn how to use data structures and their components.
- Using Abstract data types and stacks in Data structures.
- Learning about Big O notations.
- Programming with linked lists.
- Learning the types of search functions and implementing Binary search, Linear Search, etc.
- Working with Recursion in Java.
- Practising different sorting techniques such as selection sort, insertion sort, merge sort, and quicksort.
- Working with Binary Search Trees.
- Implementing Hash Tables.
- Using Heaps.
- Using a graph to solve problems.
On completing the course, students can easily apply for a career as a software developer. With the complete knowledge of data structures and algorithms, combined with an absolute guide for interviews, students will aptly conquer the interview process.
Prerequisites – Basics of programming, such as loops, if/ else statements in programming, etc.
Level: Beginner
Rating: 4.5
Duration: 11 hours and 39 minutes
You can sign up here
8. Introduction to Data Structures and Algorithms in Java
In this course, instructor Raghavendra Dixit teaches students to implement Java to code various Data structures and Algorithm programs. He takes students through coding basics and explains all the necessary components required to modify coding in data structures.
The course covers topics such as:
- Learning the types of Algorithms used in codings, such as Euclid's Algorithm and Bubble Sort Algorithm.
- Learning how to analyze an algorithm and verify its precision.
- Learning to calculate time complexity.
- Learning the Ram model of computation.
- Practising pseudo code.
- Learning Big O notation and implementing it.
- Using Search and Sort Algorithms.
- Practising the different types of sorting methods such as selection sort, insertion sort, etc.
- Learning to categorize programs for stable and unstable sorts.
- Learning to search elements in various ordered and unordered arrays.
- Learning to insert elements in arrays.
- Working with stacks and queues.
- Implementing linked lists.
- Working on Recursion.
- Using Heaps and Hash Tables.
On completing the course, students can program and code using data structure and algorithms fluently. They can also look for programming jobs in reputable organizations. Students can also design their very own projects from scratch or run quality control in collaboration projects.
Prerequisites: The website does not specify prerequisites for this course.
Level: Beginner to Intermediate.
Rating: 4.5
Duration: The website does not specify the duration of this course.
You can apply here.
9. Data Structures and Algorithms: Deep Dive Using Java
This course provides detailed knowledge of data structures and their vast library of components. It is designed for developers who want to delve into the deep study of data structures and algorithms for a developer's advanced career.
The course covers topics such as:
- Basics of Data Structures and Algorithm.
- Using JDK8 on Windows, Mac, and Linux.
- Using IntelliJ on Windows, Mac, and Linux.
- Learning about Big O.
- Fundamentals of Arrays.
- Practising the different Sort Algorithms such as Insertion, Selection, Shell, Merge, etc.
- Implementing Recursion.
- Using Quick Sort, Counting Sort, and Radix Sort.
- Fundamentals of lists and how to use them.
- Using Vectors to solve problems.
- Using Stacks and Queues in Data Structures.
- Using Search Algorithms to design shorter paths in larger maps.
- Using Hash tables, Trees, and Heaps in Data Structure.
On completing the course, students will be adept at programming at a senior level. They can apply for promotions, appraisals, and other advancements in their respective organizations. They can also look for better opportunities in their new field of study for career developments.
Prerequisites: Experience in working with any object-oriented programming language.
Level: Intermediate
Rating: 4.4
Duration: 16 hours
You can sign up here
10. From 0 to 1: Data Structures and Algorithms in Java
This course takes a unique visualization and animation approach to teach the technical aspects of Java's data structures and algorithms. The course was designed based on the human tendency to absorb information through a visual and spatial aide. It functions as the world's greatest technology that is the imagination of the human mind.
The course covers topics such as:
- Learning the fundamentals of using Data Structures and Algorithms in Java.
- Learning Big O notation.
- Learning complexities such as Time Complexity and Space Complexity.
- Learning to use Stacks and Queues.
- Using Heaps and Trees in Data Structure.
- Programming with various Sorting Algorithms.
- Working with linked lists.
- Using Graphs and Graph Algorithms to solve problems quickly and efficiently.
- Using various Search techniques to sort and analyze data.
On completing the course, students are programmed to visualize their work with their eyes closed and denote the same, using the techniques taught in this course. Their sense of programming will be much more advanced as they can visualize the problems and the outcomes.
Prerequisites: Basic knowledge in programming, preferably in Java
Level: Beginner to Intermediate
Rating: 4.3
Duration: 15 hours
You can apply here.
Conclusion
Data structure and algorithms are considered the foundation of computer science and have changed how man used to operate in development and engineering. This is your chance to grab the opportunity to make yourself invaluable in the workforce by taking up these courses. If you aspire to be in the software industry, then learning algorithms is a must. Later you may want to check Data Structure and Algorithms Interview Questions while looking for a job.
Of course, there are many more valuable data science courses. We found a variety on DataCamp, including some which offer certifications. We also love more general courses. For example, we found this MasterClass course where Terence Tao teaches problem-solving skills with a mathematical mindset.
Do you have questions about choosing the best course from the list? Let us know in the comments below, and our team shall get back to you.
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