About the Course
This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice. No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we invested over 3000 hours into designing our challenges as an alternative to multiple-choice questions that you usually find in MOOCs.
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 standard shortest path algorithms!) 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.
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
- Data Structures
- Algorithms on Graphs
- Algorithms on Strings
- Advanced Algorithms and Complexity
- Genome Assembly Programming Challenge
- Daniel M Kane, Assistant Professor, Department of Computer Science and Engineering / Department of Mathematics
- Pavel Pevzner, Professor, Department of Computer Science and Engineering
- Alexander S. Kulikov, Visiting Professor, Department of Computer Science and Engineering
- Neil Rhodes, Adjunct Faculty, Computer Science and Engineering
- Michael Levin, Lecturer, Computer Science
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the “Enroll” button on the left. You’ll be prompted to complete an application and will be notified if you are approved. You’ll need to complete this step for each course in the Specialization, including the Capstone Project.
To enroll in this course, click the link below.
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