StanfordOnline: Algorithms: Design and Analysis, Part 1
|
Welcome to the self paced course, Algorithms: Design and Analysis! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience.
About this course
Welcome to the self paced course, Algorithms: Design and Analysis! Algorithms are the heart of computer science, and the subject has countless practical applications as well as intellectual depth.
This specialization is an introduction to algorithms for learners with at least a little programming experience. The specialization is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. After completing this specialization, you will be well-positioned to ace your technical interviews and speak fluently about algorithms with other programmers and computer scientists.
Specific topics in the course include: “Big-oh” notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), randomized algorithms (QuickSort, contraction algorithm for min cuts), data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of BFS and DFS, connectivity, shortest paths).
Learners will practice and master the fundamentals of algorithms through several types of assessments. There are 6 multiple choice quizzes to test your understanding of the most important concepts. There are also 6 programming assignments, where you implement one of the algorithms covered in lecture in a programming language of your choosing. The course concludes with a multiple-choice final. There are no assignment due dates and you can work through the course materials and assignments at your own pace.
At a Glance:
Institution: StanfordOnline
Subject: Computer Science
Level: Intermediate
Prerequisites:
This specialization is an introduction to algorithms for learners with at least a little programming experience.
This course is not an introduction to programming, and it assumes that you have basic programming skills in a language such as Python, Java, or C. There are several outstanding free online courses that teach basic programming. We also use mathematical analysis as needed to understand how and why algorithms and data structures really work.
Language: English
Video Transcript: English
Associated skills:Computer Science, Matrix Multiplication, Data Structures, Algorithms, Master Theorem, Divide And Conquer, Bloom Filter
User Reviews
Be the first to review “StanfordOnline: Algorithms: Design and Analysis, Part 1”
Related Products
GalileoX: Java Programming Fundamentals
Your career as a program developer starts here. Gain entry-level programing skills in Java language, and prepare yourself to handle any task that is required in any programming job.
GTx: Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms
Delve into Pattern Matching algorithms from KMP to Rabin-Karp. Tackle essential algorithms that traverse the graph data structure like Dijkstra’s Shortest Path. Study algorithms that construct a Minimum Spanning Tree (MST) from a graph. Explore Dynamic Programming algorithms. Use the course visualization tool to understand the algorithms and their performance.
GTx: Computing in Python IV: Objects & Algorithms
Learn about recursion, search and sort algorithms, and object-oriented programming in Python.
HarvardX: Fundamentals of TinyML
Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.
UCSanDiegoX: Machine Learning Fundamentals
Understand machine learning's role in data-driven modeling, prediction, and decision-making.
CS50’s Introduction to Computer Science
An introduction to the intellectual enterprises of computer science and the art of programming.
There are no reviews yet.