The course is divided into 6 weeks, with each week focusing on a specific topic:
Week 1: Union-Find. This week covers the basics of union-find data structures and algorithms, including quick-find, quick-union, and weighted quick-union.
Week 2: Analysis of Algorithms. This week introduces basic concepts of algorithm analysis, including big O notation and empirical analysis. Students will also learn about sorting algorithms such as selection sort, insertion sort, and shellsort.
Week 3: Stacks and Queues. This week covers the use of stacks and queues in solving problems, including applications of the stack data structure to parsing arithmetic expressions and implementing breadth-first search.
Week 4: Elementary Symbol Tables. This week covers the basics of symbol tables, including ordered and unordered arrays and binary search trees.
Week 5: Balanced Search Trees. This week delves into balanced search trees such as red-black trees, 2-3 trees, and B-trees.
Week 6: Hash Tables. This week covers hash tables and their applications, including separate chaining and linear probing.
Throughout the course, students will implement and analyze algorithms using Java, and they will also gain an understanding of the practical applications of the algorithms they learn. The course is aimed at beginners with some programming experience, and it is a useful foundation for further study in computer science and related fields.
The Algorithms, Part I course on Coursera, created by Kevin Wayne, is a 6-week course that covers the fundamental principles of algorithm design and analysis using Java. The course consists of the following topics:
- Week 1: Union-Find
- Introduction to the union-find data structure
- Quick-find algorithm
- Quick-union algorithm
- Weighted quick-union algorithm
- Applications of union-find
- Week 2: Analysis of Algorithms
- Introduction to algorithm analysis
- Big O notation
- Empirical analysis
- Selection sort algorithm
- Insertion sort algorithm
- Shellsort algorithm
- Week 3: Stacks and Queues
- Introduction to stacks and queues
- Applications of stacks and queues
- Stack data structure for parsing arithmetic expressions
- Queue data structure for implementing breadth-first search
- Week 4: Elementary Symbol Tables
- Introduction to symbol tables
- Ordered and unordered arrays
- Binary search trees
- Tree traversal algorithms
- Week 5: Balanced Search Trees
- Introduction to balanced search trees
- Red-black trees
- 2-3 trees
- Week 6: Hash Tables
- Introduction to hash tables
- Separate chaining
- Linear probing
- Applications of hash tables
The course includes lecture videos, quizzes, programming assignments, and a final exam. There are a total of 6 weeks and approximately 30 lectures in the course. The course is designed for beginners with some programming experience, and it provides a solid foundation for further study in computer science and related fields.
As a former student of the Algorithms, Part I course on Coursera created by Kevin Wayne, I can confidently say that it is an outstanding course for anyone looking to learn about algorithms and data structures.
The course is well-organized and presents the material in a clear and concise manner. The video lectures are engaging, and Kevin Wayne is an excellent instructor. He has a talent for explaining complex topics in a way that is easy to understand, and his passion for the subject matter is evident throughout the course.
One of the highlights of the course is the programming assignments. They are challenging but also incredibly rewarding, as they provide a hands-on experience of applying the concepts covered in the lectures. The assignments are thoughtfully designed and require students to think critically about the best approach to implement algorithms and data structures.
Another strength of the course is the emphasis on problem-solving and algorithm design. The course teaches students how to approach problems from a computational perspective and provides a framework for designing efficient algorithms.
Overall, I would highly recommend the Algorithms, Part I course to anyone interested in learning about algorithms and data structures. The course materials are of high quality, and the programming assignments are an excellent way to apply the concepts learned in the course.
At the time, the course has an average rating of 4.9 out of 5 stars based on over 10,252 ratings.
What you'll learn:
After completing the Algorithms, Part I course created by Kevin Wayne on Coursera, students will gain a solid foundation in algorithms and data structures using Java. Specifically, students will develop the following skills:
Understanding of fundamental algorithms and data structures: Students will learn about important algorithms such as union-find, sorting algorithms, and search algorithms, as well as data structures such as stacks, queues, and symbol tables.
Analysis and complexity of algorithms: Students will learn how to analyze and measure the efficiency and complexity of algorithms, using concepts such as big O notation and empirical analysis.
Problem-solving skills: The course emphasizes the practical applications of algorithms and data structures, providing students with the skills to solve problems in a variety of programming contexts.
Java programming skills: Students will develop their Java programming skills through programming assignments and implementation of algorithms and data structures.
Preparation for further study: The course provides a strong foundation for further study in computer science and related fields, building on the skills and concepts learned in the course.
Overall, completing the Algorithms, Part I course will provide students with a strong set of skills and knowledge in algorithms and data structures, which are essential for programming in a variety of contexts.
Kevin Wayne is a computer science professor at Princeton University, where he teaches courses on algorithms, data structures, and computer science fundamentals. He received his Ph.D. in Computer Science from Cornell University and has published numerous research papers on topics such as cryptography, algorithms, and data structures.
In addition to his work at Princeton, Kevin Wayne is also well-known for his contributions to the field of computer science education. He co-authored the popular textbook "Introduction to Programming in Java" and has developed several online courses on topics such as algorithms and data structures, computer science fundamentals, and cryptography.
Kevin Wayne's expertise in algorithms and data structures is widely recognized, and he has received several awards for his contributions to the field. He is a Fellow of the Association for Computing Machinery (ACM) and has received the ACM-SIGACT Outstanding Educator Award, among others.
Overall, Kevin Wayne is a highly respected computer science educator and researcher with significant expertise in algorithms and data structures. His contributions to the field have had a significant impact on computer science education, and his courses and textbooks are widely used and highly regarded by students and educators alike.
The Algorithms, Part I course created by Kevin Wayne on Coursera has several requirements that students must meet in order to fully participate and benefit from the course:
Programming experience: Students should have some prior programming experience in Java, as the course focuses on implementing algorithms and data structures using Java.
Mathematical background: The course requires a basic understanding of mathematics, including algebra and elementary probability theory.
Time commitment: The course consists of several lectures, quizzes, and programming assignments that require a significant time commitment to complete. Students should plan to spend several hours each week on coursework.
Access to a computer: Students will need access to a computer with Java development tools installed to complete the programming assignments.
Coursera subscription: The course is offered through Coursera, so students will need to sign up for a subscription to access the course materials and participate in the assignments and quizzes.
Overall, the Algorithms, Part I course requires students to have some prior programming experience and a basic understanding of mathematics. The course also requires a significant time commitment and access to a computer with Java development tools installed.