Search result for Types of search algorithms Online Courses & Certifications
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Algorithmic Toolbox
by Alexander S. Kulikov , Michael Levin , Neil Rhodes , Pavel Pevzner , Daniel M Kane- 4.6
Approx. 39 hours to complete
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. Main Ingredients of Greedy Algorithms Review of Greedy Algorithms...
Algorithms: Design and Analysis, Part 2
by Tim Roughgarden- 0.0
6 Weeks
Specific topics in Part 2 include: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes), dynamic programming (knapsack, sequence alignment, optimal search trees, shortest paths), NP-completeness and what it means for the algorithm designer, analysis of heuristics, local search. Learners will practice and master the fundamentals of algorithms through several types of assessments....
$149
Algorithms, Part II
by Robert Sedgewick , Kevin Wayne- 4.9
Approx. 63 hours to complete
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. All the features of this course are available for free. Depth-First Search Breadth-First Search Digraph Search Ternary Search Tries Substring Search Search Problems...
Solving Algorithms for Discrete Optimization
by Prof. Jimmy Ho Man Lee , Prof. Peter James Stuckey- 4.8
Approx. 22 hours to complete
The same technology can schedule planes and their crews, coordinate the production of steel, and organize the transportation of iron ore from the mines to the ports. Welcome to Solving Algorithms for Discrete Optimization 5 Search Start of Course Survey 8 MiniZinc to Local Search Workshop 12: Local Search End of Course Survey...
Delivery Problem
by Alexander S. Kulikov- 4.7
Approx. 14 hours to complete
We still don’t have provably efficient algorithms for this difficult computational problem and this is the essence of the P versus NP problem, the most important open question in Computer Science. Still, we’ll implement several solutions for real world instances of the travelling salesman problem. Brute Force Search Exact Algorithms Approximation Algorithms Approximation Algorithms Local Search...
Algorithmic Thinking (Part 2)
by Luay Nakhleh , Scott Rixner , Joe Warren- 4.7
Approx. 12 hours to complete
As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Efficiency of binary search...
Addressing Large Hadron Collider Challenges by Machine Learning
by Andrei Ustyuzhanin , Mikhail Hushchyn- 4.5
Approx. 24 hours to complete
Just one of the four experiments generates thousands gigabytes per second. Of course we will scrutinize the major stages of the data processing pipelines, and focus on the role of the Machine Learning techniques for such tasks as track pattern recognition, particle identification, online real-time processing (triggers) and search for very rare decays....
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Computational Thinking for Problem Solving
by Susan Davidson- 4.7
Approx. 18 hours to complete
Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course....
Algorithms: Design and Analysis, Part 1
by Tim Roughgarden- 0.0
6 Weeks
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). Randomized algorithms (QuickSort, contraction algorithm for min cuts)...
$149
Algorithms and Data Structures in Python (INTERVIEW Q&A)
by Holczer Balazs- 4.4
18 hours on-demand video
This course is about data structures, algorithms and graphs. I highly recommend typing out these data structures and algorithms several times on your own in order to get a good grasp of it. practical applications of binary search trees Most of the advanced algorithms relies heavily on these topics so it is definitely worth understanding the basics....
$14.99