- Debugging
- Software Testing
- Algorithms
- Data Structure
- Computer Programming
- Dynamic Programming
- Binary Search Tree
- Priority Queue
- Hash Table
- Stack (Abstract Data Type)
- List
- Graph Theory
Data Structures and Algorithms Specialization
Master Algorithmic Programming Techniques. Advance your Software Engineering or Data Science Career by Learning Algorithms through Programming and Puzzle Solving. Ace coding interviews by implementing each algorithmic challenge in this Specialization. Apply the newly-learned algorithmic techniques to real-life problems, such as analyzing a huge social network or sequencing a genome of a deadly pathogen.
Offered By
What you will learn
Play with 50 algorithmic puzzles on your smartphone to develop your algorithmic intuition! Apply algorithmic techniques (greedy algorithms, binary search, dynamic programming, etc.) and data structures (stacks, queues, trees, graphs, etc.) to solve 100 programming challenges that often appear at interviews at high-tech companies. Get an instant feedback on whether your solution is correct.
Apply the newly learned algorithms to solve real-world challenges: navigating in a Big Network or assembling a genome of a deadly pathogen from millions of short substrings of its DNA.
Learn exactly the same material as undergraduate students in “Algorithms 101” at top universities and more! We are excited that students from various parts of the world are now studying our online materials in the Algorithms 101 classes at their universities. Here is a quote from the website of Professor Sauleh Eetemadi from Iran University of Science and Technology: “After examining syllabus and course material from top universities including Stanford, Princeton and MIT we have chosen to follow the Data Structures and Algorithms Specialization from UCSD...due to excellent course material and its practical approach.”
If you decide to venture beyond Algorithms 101, try to solve more complex programming challenges (flows in networks, linear programming, streaming algorithms, etc.) and complete an equivalent of a graduate course in algorithms!
Skills you will gain
About this Specialization
Applied Learning Project
The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco 1000 times faster than the shortest path algorithms you learn in the standard Algorithms 101 course! Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine.
Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.
Basic knowledge of at least one programming language: C++, Java, Python, C, C#, Javascript, Haskell, Kotlin, Ruby, Rust, Scala. Basic knowledge of discrete mathematics: proof by induction, proof by contradiction.
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

There are 6 Courses in this Specialization
Algorithmic Toolbox
This online course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).
Data Structures
A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures.
Algorithms on Graphs
If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. Graphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get to work, cheapest way to connect a set of computers into a network or efficient algorithm to automatically find communities and opinion leaders in Facebook, you're going to work with graphs and algorithms on graphs.
Algorithms on Strings
World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Moreover, the emerging field of personalized medicine uses many search algorithms to find disease-causing mutations in the human genome. In this online course you will learn key pattern matching concepts: tries, suffix trees, suffix arrays and even the Burrows-Wheeler transform.
Offered by

University of California San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.



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