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 the intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience.
See More: https://bit.ly/2GhgSgL
Algorithms design and analysis certificate - edukiteEduKite
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 the intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience.
See More: https://bit.ly/2GhgSgL
What is an Algorithm? It is a set of rules that allows you to solve computational problems in an organized and definite order. You can also use algorithms on a roadmap to reach a destination.
See More: https://bit.ly/2Dib8D4
Algorithms design and analysis diploma - edukiteEduKite
The algorithm is the set of rules that are followed by calculations and processes by computers. Learning how to design and analyze algorithms will put you in an advantage for your professional growth and development.
See More: https://bit.ly/2V1Jl3N
The aim of this course is to provide an introduction to mathematical modeling of computational problems. It is an undergraduate course. It covers topics such as the common algorithms, algorithmic paradigms, and data structures used to solve these problems.
See More: https://bit.ly/30oZS1v
Automata, Computability, And Complexity Training - EdukiteEduKite
This course provides a challenging introduction to the central ideas of theoretical computer science. Beginning in antiquity, it will progress through finite automata, circuits and decision trees, Turing machines and computability and the P versus NP problem. It examines the classes of problems that can and cannot be solved by machines. It tries to explain the key differences between computational models that affect their power.
See More https://bit.ly/30d0B5I
How to build a model from the ground up? Can you understand economics or biology or political science or business or even management by using agent-based modeling? This course will help you to get the answers. You will explore how to use agent-based modeling to understand and examine a disparate set of complex problems.
See More: https://bit.ly/2VyMzsq
Autonomy and Decision Making Diploma - EdukiteEduKite
The Autonomy and Decision Making Diploma course illustrates different types of reasoning, optimization and decision-making strategies for helping you to create highly autonomous systems and decision support aids.
See More: https://bit.ly/2HkSQ6q
The course helps you to master the practical skills for developing a successful user interface. You will learn the techniques of designing modern, intuitive, meaningful, compelling user interfaces for desktop and mobile devices. A strong command over Photoshop and a good understanding of colour theory are must while developing UI design. The course covers these two areas in detail along with the functions and use of Photoshop.
See Details: https://bit.ly/2FWLHdU
Algorithms design and analysis certificate - edukiteEduKite
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 the intellectual depth. This specialization is an introduction to algorithms for learners with at least a little programming experience.
See More: https://bit.ly/2GhgSgL
What is an Algorithm? It is a set of rules that allows you to solve computational problems in an organized and definite order. You can also use algorithms on a roadmap to reach a destination.
See More: https://bit.ly/2Dib8D4
Algorithms design and analysis diploma - edukiteEduKite
The algorithm is the set of rules that are followed by calculations and processes by computers. Learning how to design and analyze algorithms will put you in an advantage for your professional growth and development.
See More: https://bit.ly/2V1Jl3N
The aim of this course is to provide an introduction to mathematical modeling of computational problems. It is an undergraduate course. It covers topics such as the common algorithms, algorithmic paradigms, and data structures used to solve these problems.
See More: https://bit.ly/30oZS1v
Automata, Computability, And Complexity Training - EdukiteEduKite
This course provides a challenging introduction to the central ideas of theoretical computer science. Beginning in antiquity, it will progress through finite automata, circuits and decision trees, Turing machines and computability and the P versus NP problem. It examines the classes of problems that can and cannot be solved by machines. It tries to explain the key differences between computational models that affect their power.
See More https://bit.ly/30d0B5I
How to build a model from the ground up? Can you understand economics or biology or political science or business or even management by using agent-based modeling? This course will help you to get the answers. You will explore how to use agent-based modeling to understand and examine a disparate set of complex problems.
See More: https://bit.ly/2VyMzsq
Autonomy and Decision Making Diploma - EdukiteEduKite
The Autonomy and Decision Making Diploma course illustrates different types of reasoning, optimization and decision-making strategies for helping you to create highly autonomous systems and decision support aids.
See More: https://bit.ly/2HkSQ6q
The course helps you to master the practical skills for developing a successful user interface. You will learn the techniques of designing modern, intuitive, meaningful, compelling user interfaces for desktop and mobile devices. A strong command over Photoshop and a good understanding of colour theory are must while developing UI design. The course covers these two areas in detail along with the functions and use of Photoshop.
See Details: https://bit.ly/2FWLHdU
Basic Principles of Behavior of Algorithms - EdukiteEduKite
This course is a study of Behavior of Algorithms and covers an area of current interest in theoretical computer science. The topics vary from term to term. During this term, we discuss rigorous approaches to explaining the typical performance of algorithms with a focus on the following approaches smoothed analysis. In addition to that, condition numbers/parametric analysis, and subclassing inputs will be discussed.
See More: https://bit.ly/2YCSkdn
This course focus on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning. It covers topics such as classification and linear regression and ending up with more recent topics like boosting hidden Markov models, and Bayesian networks.
See More: https://bit.ly/2VXQnrn
Automata theory is the study of abstract machines and automata, including the computational problems that can be solved using them. The major objective of automata theory is to develop methods by which computer scientists can describe and analyse the dynamic behaviour of discrete systems, in which signals are sampled periodically.
See More: https://bit.ly/2YBuGdR
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See more: https://bit.ly/2n0dwWs
Certificate in Digital System Design - EdukiteEduKite
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See More: https://bit.ly/30fa5Ns
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A first graduate course in algorithms, this Advanced Algorithms Diploma assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design while building a repertory of basic algorithmic solutions to problems in many domains. This course is concerned with the study of algorithms for solving practical problems efficiently, and the theoretical analysis of their behavior.
See More: https://bit.ly/2UaO27r
A first graduate course in algorithms, this Advanced Algorithms Diploma assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design while building a repertory of basic algorithmic solutions to problems in many domains.
See More: https://bit.ly/2UaO27r
The Machine Learning Diploma is designed to teach you about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you’ll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.
See more: https://bit.ly/2K0h8AL
Certificate In Complex Digital Systems - EdukiteEduKite
This course is offered to graduate and is a project-oriented course to teach new methodologies for designing multi-million-gate CMOS VLSI chips using high-level synthesis tools in conjunction with standard commercial EDA tools. The course focus on modular and robust designs, reusable modules, correctness by construction, architectural exploration, and meeting the area.
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Azure Application Deployment and Management Diploma - EdukiteEduKite
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A first graduate course in algorithms, this Advanced Algorithms Diploma assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design while building a repertory of basic algorithmic solutions to problems in many domains. This course is concerned with the study of algorithms for solving practical problems efficiently, and the theoretical analysis of their behavior.
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Algorithms Design and Analysis - Edukite
1. 4/17/2019 Algorithms Design and Analysis Diploma - Edukite
https://edukite.org/course/algorithms-design-and-analysis-diploma/ 1/14
HOME / COURSE / PERSONAL DEVELOPMENT / ALGORITHMS DESIGN AND ANALYSIS DIPLOMA
Algorithms Design and Analysis
Diploma
( 9 REVIEWS ) 477 STUDENTS
The algorithm is the set of rules that are followed by calculations and processes by computers.
Learning how to design …
TAKE THIS COURSE
2. 4/17/2019 Algorithms Design and Analysis Diploma - Edukite
https://edukite.org/course/algorithms-design-and-analysis-diploma/ 2/14
FREE
1 YEAR
LEVEL 3 - DIPLOMA
COURSE BADGE
COURSE CERTIFICATE
96NUMBER OF UNITS
0NUMBER OF QUIZZES
17 HOURS, 8 MINUTES
HOME CURRICULUM REVIEWS
The algorithm is the set of rules that are followed by calculations and processes by computers.
Learning how to design and analyze algorithms will put you in an advantage for your professional
growth and development.
This Algorithms Design and Analysis Diploma will introduce you the teaching techniques focusing
on the design and analysis of ef cient algorithm with emphasis on the methods of application. You
will be provided with information on dynamic programming, complexity, etc. here.
Assessment
This course does not involve any written exams. Students need to answer 5 assignment questions to
complete the course, the answers will be in the form of written work in pdf or word. Students can
write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers
are submitted, the tutor will check and assess the work.
Certification
Edukite courses are free to study. To successfully complete a course you must submit all the
assignment of the course as part of the assessment. Upon successful completion of a course, you can
choose to make your achievement formal by obtaining your Certi cate at a cost of £49.
Having an Of cial Edukite Certi cation is a great way to celebrate and share your success. You can:
Add the certi cate to your CV or resume and brighten up your career
Show it to prove your success
3. 4/17/2019 Algorithms Design and Analysis Diploma - Edukite
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Course Credit: MIT
TWO MOTIVATING APPLICATIONS
Application: Internet Routing 00:11:00
Application: Sequence Alignment 00:09:00
INTRODUCTION TO GREEDY ALGORITHMS
Introduction to Greedy Algorithms 00:13:00
Application: Optimal Caching 00:11:00
A SCHEDULING APPLICATION
Problem De nition 00:06:00
A Greedy Algorithm 00:13:00
Correctness Proof – Part I 00:07:00
Correctness Proof – Part II 00:05:00
Handling Ties [Advanced – Optional] 00:07:00
PRIM'S MINIMUM SPANNING TREE ALGORITHM
MST Problem De nition 00:11:00
Prim’s MST Algorithm 00:07:00
COURSE CURRICULUM
4. 4/17/2019 Algorithms Design and Analysis Diploma - Edukite
https://edukite.org/course/algorithms-design-and-analysis-diploma/ 4/14
Correctness Proof 00:16:00
Correctness Proof II 00:08:00
Proof of Cut Property [Advanced – Optional] 00:12:00
Fast Implementation I 00:15:00
Fast Implementation II 00:10:00
KRUSKAL'S MINIMUM SPANNING TREE ALGORITHM
Kruskal’s MST Algorithm 00:08:00
Correctness of Kruskal’s Algorithm 00:10:00
Implementing Kruskal’s Algorithm via Union-Find 00:10:00
Implementing Kruskal’s Algorithm via Union-Find II 00:14:00
MSTs: State-of-the-Art and Open Questions [Advanced – Optional] 00:09:00
CLUSTERING
Application to Clustering 00:11:00
Correctness of Clustering Algorithm 00:10:00
ADVANCED UNION-FIND
Lazy Unions [Advanced – Optional] 00:10:00
Union-by-Rank [Advanced – Optional] 00:12:00
Analysis of Union-by-Rank [Advanced – Optional] 00:15:00
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Path Compression [Advanced – Optional] 00:15:00
Path Compression: The Hopcroft-Ullman Analysis I [Advanced – Optional] 00:10:00
Path Compression: The Hopcroft-Ullman Analysis II [Advanced – Optional] 00:12:00
The Ackermann Function [Advanced – Optional] 00:16:00
Path Compression: Tarjan’s Analysis I [Advanced – Optional] 00:14:00
Path Compression: Tarjan’s Analysis II [Advanced – Optional] 00:14:00
HUFFMAN CODES
Introduction and Motivation 00:09:00
Problem De nition 00:10:00
A Greedy Algorithm 00:17:00
A More Complex Example 00:04:00
Correctness Proof I 00:10:00
Correctness Proof II 00:13:00
INTRODUCTION TO DYNAMIC PROGRAMMING
Introduction: Weighted Independent Sets in Path Graphs 00:08:00
WIS in Path Graphs: A Linear-Time Algorithm 00:10:00
WIS in Path Graphs: A Reconstruction Algorithm 00:07:00
Principles of Dynamic Programming 00:08:00
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THE KNAPSACK PROBLEM
The Knapsack Problem 00:10:00
A Dynamic Programming Algorithm 00:10:00
Example [Review – Optional] 00:13:00
SEQUENCE ALIGNMENT
Optimal Substructure 00:14:00
A Dynamic Programming Algorithm 00:12:00
OPTIMAL BINARY SEARCH TREES
Problem De nition 00:13:00
Optimal Substructure 00:10:00
Proof of Optimal Substructure 00:07:00
A Dynamic Programming Algorithm 00:10:00
A Dynamic Programming Algorithm II 00:10:00
THE BELLMAN-FORD ALGORITHM
Single-Source Shortest Paths, Revisited 00:11:00
Optimal Substructure 00:11:00
The Basic Algorithm I 00:09:00
The Basic Algorithm II 00:11:00
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Detecting Negative Cycles 00:09:00
A Space Optimization 00:13:00
Internet Routing I [Optional] 00:12:00
Internet Routing II 00:07:00
ALL-PAIRS SHORTEST PATHS
Problem De nition 00:07:00
Optimal Substructure 00:12:00
The Floyd-Warshall Algorithm 00:14:00
A Reweighting Technique 00:14:00
Johnson’s Algorithm 00:11:00
Johnson’s Algorithm II 00:12:00
NP-COMPLETE PROBLEMS
Polynomial-Time Solvable Problems 00:15:00
Reductions and Completeness 00:14:00
De nition and Interpretation of NP-Completeness I 00:11:00
De nition and Interpretation of NP-Completeness II 00:08:00
The P vs. NP Question 00:09:00
Algorithmic Approaches to NP-Complete Problems 00:13:00
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FASTER EXACT ALGORITHMS FOR NP-COMPLETE PROBLEMS
The Vertex Cover Problem 00:09:00
Smarter Search for Vertex I 00:10:00
Smarter Search for Vertex Cover II 00:08:00
The Traveling Salesman Problem 00:15:00
A Dynamic Programming Algorithm for TSP 00:12:00
APPROXIMATION ALGORITHMS FOR NP-COMPLETE PROBLEMS
A Greedy Knapsack Heuristic 00:14:00
Analysis of a Greedy Knapsack Heuristic I 00:07:00
Analysis of a Greedy Knapsack Heuristic II 00:10:00
A Dynamic Programming Heuristic for Knapsack 00:12:00
Knapsack via Dynamic Programming, Revisited 00:11:00
Analysis of Dynamic Programming Heuristic 00:15:00
LOCAL SEARCH ALGORITHMS
The Maximum Cut Problem I 00:09:00
The Maximum Cut Problem II 00:09:00
Principles of Local Search I 00:09:00
Principles of Local Search II 00:11:00
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The 2-SAT Problem 00:15:00
Random Walks on a Line 00:16:00
Analysis of Papadimitriou’s Algorithm 00:15:00
THE WIDER WORLD OF ALGORITHMS
Stable Matching [Optional] 00:15:00
Matchings, Flows, and Braess’s Paradox [Optional] 00:14:00
Linear Programming and Beyond [Optional] 00:12:00
Epilogue 00:01:00
Assessment
Submit Your Assignment 00:00:00
Certi cation 00:00:00
COURSE REVIEWS
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