Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
Algorithms are the underlying logic that powers the modern world. They are used in everything from spam filtering to GPS navigation to machine learning. A solid understanding of algorithms is essential for software engineers and other technology professionals. The Introduction to Algorithms and Data Structures certification by Carnegie Mellon University’s School of Computer Science, along with Emeritus, provides you with the knowledge and skills you need to design, analyse, and implement algorithms. This course covers a wide range of topics, including sorting, searching, graphs, and dynamic programming.
With the help of the Introduction to Algorithms and Data Structures certification, you will solve real-world problems by formulating and analysing algorithms. You will also learn how to implement algorithms in a variety of programming languages.
The Introduction to Algorithms and Data Structures online course is designed for students with a basic coding and maths background. By completing this course, you will gain valuable knowledge and skills that will be useful in your academic and professional career.
The Highlights
- 10 week duration
- Offered by Carnegie Mellon University
- Live Office Hours With Learning Facilitator
- Programming Assignments
Programme Offerings
- Certificate of completion
- Online Classes
- Knowledge checks
- Discussion Board Activities
- flexible schedule
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | CMU Pittsburgh |
Eligibility Criteria
The prerequisites for the Introduction to Algorithms and Data Structures certification course are high school algebra, comfort with mathematical arguments, and working knowledge of Python.
Certification Qualifying Details
Upon completing this course and passing all assessments, you will be awarded the Introduction to Algorithms and Data Structures certification by Carnegie Mellon University's School of Computer Science.
What you will learn
After completing the Introduction to Algorithms and Data Structures certification syllabus, you will gain the knowledge and skills you need to design, analyse, and implement algorithms. You will learn about Algorithms, the unseen forces that drive the modern world.
Upon completion of the Introduction to Algorithms and Data Structures training, you will learn how to solve real-world problems by formulating and analysing algorithms. You will gain valuable knowledge and skills that will be useful in your academic and professional career.
Who it is for
Introduction to Algorithms and Data Structures is designed for anyone who wants to learn how to use algorithms and data structures to solve common computational problems. This course can also be beneficial for professionals such as:
Admission Details
Enrol in the Introduction to Algorithms and Data Structures classes by following these steps:
Step 1: Go through the URL below: https://execonline.cs.cmu.edu/algorithms-data-structures
Step 2: Fill out the required details.
Step 3: Download the brochure.
Step 4: Go through the course page and click on ‘Apply Now’.
Step 5: Fill out the application form and pay the course fee.
Application Details
To enrol in the Introduction to Algorithms and Data Structures online course, you have to fill out the online application form on the official provider website.
The Syllabus
- Illustrating the key components of an algorithm and the notations used for time complexity
- Performing recurrence analysis and analyzing the time complexity of merge-sort and quick-select algorithms
- Explaining the concept of concrete models as well as tight upper and lower bounds
- Applying the information-theoretic and adversary techniques to prove upper and lower bounds of computational problems
- Explaining what a greedy algorithm is and how to design such algorithms
- Proving the optimality of greedy algorithms
- Developing and implementing dynamic programming
- Comparing the bottom-up and the top-down approaches to dynamic programming
- Examining the properties of hashing and apply it to the dynamic dictionary problems
- Using hashing to solve problems on data streams
- Finding the maximum flow and minimum cut of a given network
- Designing and implementing network flow algorithms to solve problems
- Exploring LP solutions for the min-cut max-flow and the operations research problems
- Applying LP algorithms, such as the Simplex algorithm
- Proving a problem is NP-complete
- Developing approximation algorithms to solve NP-complete problems
- Using the multiplicative weights framework to solve problems
- Proving the correctness of multiplicative weight algorithms
- Examining the fundamentals of the GD framework and convexity
- Implementing GD algorithms to solve convex optimization problems
Instructors
CMU Pittsburgh Frequently Asked Questions (FAQ's)
It takes ten weeks to complete this course if you work at a pace of 5-10 hours per week.
The course is delivered in an online format. You can attend the classes at home, on your own time.
You can apply for this course by simply filling out the application form on the official provider website.
Carnegie Mellon University's School of Computer Science is partnering with Emeritus, an online education provider, to offer this course.
The course is delivered in an online format. You can attend the classes at home, on your own time.