Coursera Algorithms Courses & Certifications

If you have already learnt about the basics of Algorithms, you are now ready to take the next logical step into more complex algorithms and problem-solving. The idea behind this Advanced Algorithm and Complexity course is to teach you how to build upon the algorithm basics and utilize new ideas. In this course, we will be starting with network flows that are employed in the typical applications like detecting disjoint paths, optimal matching, and flight schedules along with a few other surprising applications like the segmentation of images in computer vision.

In the next segment, we teach linear programming with its application in allotting and optimizing budgets, Portfolio optimization, finding a diet that is cheap and satisfies all the requirements. Further, we discuss the inherent hard problems that have no perfectly good solutions known (and neither are likely to be found) and how you can solve them in practice. The course finishes with a slight introduction to the streaming of algorithms that are used, most heavily in Big Data Processing. These algorithms are mostly designed to process huge data sets without being capable of storing even a single dataset.

Algorithms are an essential part of the computer to process data effectively. Algorithms are used as specifications for performing tasks like automated reasoning, calculation and even for data processing. Algorithms are becoming an important part of our lives even if we don’t notice it. To make a computer do whatever we desire it is important to write a programme for which algorithm plays an important role. With the help of which one can command the computer whatever they want to.

Whatever one thinks of making from a website to an app they need to create a programme in which programming plays a very important part. This course of Algorithms part II is specially designed for the candidate to upgrade their knowledge about algorithms after they have completed the part one course. It will help them to master their skills in programming and make them stand out from the competition that is prevailing in this era.

The Algorithm programme offered by Princeton University has two parts, Part I and Part II. The programme covers critical knowledge about ‘algorithms and data structures while emphasizing on scientific performance analysis and applications of Java implementations. Every serious programmer needs to know this. 

Algorithms, Part I includes elementary algorithms for data structures, sorting, and searching while Part II focuses on algorithms for graph- and string-processing. After the completion of the first part, candidates can enrol for the second part in Coursera.

The Algorithms, Part I programme is a 100 per cent free programme. Enrolment, access to content everything is provided for free. And also there will be no certification after completion of the programme. 

Candidates who are looking for a way to learn algorithms, Java programming, data structures should enrol for this programme. Irrespective of the field, candidates can enrol in the Algorithms, Part I programme if they use computers to solve problems which are large. 

Candidates who are programmers should also enrol for the Algorithms, Part I programme. By completing the programme they will be getting so many advantages in their career. The ones who have already finished the programme are now in better conditions.

The Computer Science: Algorithms, Theory, and Machines Certification Course is a 100% online course that explores the nuances and concepts of computation. The intermediate-level course will deal with classic algorithms, classic theoretical models, and modern applications of computation. The course can be easily accessed on the Coursera online learning platform. 

The Computer Science: Algorithms, Theory, and Machines Training will be provided by the Computer Science faculty of Princeton University. The Computer Science: Algorithms, Theory, and Machines Certification Course by Coursera and Princeton University will be available for free and there will be no certificates awarded to candidates.

The Analysis of Algorithms online course familiarises students with calculating the computational complexity of algorithms. The training also covers function generation, recurrences, telescoping, and more concepts related to the scientific study of algorithm performance. Candidates learn about real asymptotics, symbolic methods, and basic structures like words, permutations, strings, trees, and mappings, through the programme.

The Coursera Analysis of Algorithms programme is 100% online and free course. It consists of pre-recorded video lectures, pop quizzes, readings, assignments, and practical exercises across a nine-week curriculum. Robert Sedgewick, who is currently the William O. Baker Professor of Computer Science at Princeton, will be your instructor. 

The Online Analysis of Algorithms training course is an advanced-level programme offered in collaboration with Princeton University. Candidates will need approximately 20 hours to finish this course. Besides, you will get English subtitles for the video lectures and flexible deadlines to learn at ease. Since this is free training; candidates will not receive a certification.

Optimization technology is used in many industries to make problem-solving easier. The Discrete Optimization course by Coursera focuses on solving complex problems using optimization algorithms and concepts, including local search, constraint programming, and mixed-integer programming. The course gives an introduction to the fundamental concepts of discrete optimization and its uses in the real world. 

The Coursera Discrete Optimization course explores concepts like mixed-integer programming, constraint programming and local search, starting from their foundations to their uses and application for solving practical problems, which includes scheduling, resource allocation, vehicle routing and supply-chain optimization. 

Furthermore, the Coursera Discrete Optimization course is an online, self-paced learning course offered by the University of Melbourne to help students understand the process of solving complex problems through discrete optimization. Coursera also offers a shareable electronic certificate at the end of the course, which can be printed and used along with the student’s resume, and also shared on professional platforms such as LinkedIn. 

The certificate programme on Algorithmic Toolbox by Coursera is an intermediate level course that will cover basic ideas for problems arising in the practical applications of computational problems, algorithmic techniques, greedy algorithms, Sorting and searching, Dynamic programming, and divide and conquer. The course offers a lot of theory and understanding of the burning questions in programming. It helps candidates develop an understanding of how to solve the most commonly arising problem and how they can break it into pieces and solve them recursively, Further how they can sort data and how it can help in searching, when it is ok to proceed greedily and how genomic studies use dynamic programming.

The candidates will be given enough practice in solving the computational problems, implement the solutions efficiently, design new algorithms, and ensure the easy and smooth running of the programs. This course forms a part of specialisation in Data structures and algorithm specialisation, for candidates willing to learn more about the topic and further continue to take the specialization too.

For candidates and professionals willing to learn about the new challenges in programming and better equip themselves for staying relevant in the industry this course on Algorithmic Toolbox will offer a much better understanding of the subject and help them take the next step in their career.

It seems difficult for Java to deal with data in huge quantities. Various data algorithms and frameworks work together when applications exercise vast and real data sets. Data Structures and Performance is a Java course at an intermediate level which is recommended to the candidates who have an experience or familiar with computer science or software development. The programme focuses on establishing code which finishes the work effectively and efficiently by giving accurate results.

In this programme, the candidates would get an opportunity to analyze and utilize data structures that are applied in industry-level applications like hashtables, trees, and lists. The concepts will describe how the data framework makes programmes flexible and efficient. Through this course, the candidates can apply to Professional Certificates programs as well as multiple specializations. This course would be counted towards training in Object-Oriented Java Programming: Data Structures and Beyond Specialization and Object Oriented Programming in Java Specialization.

The Divide and Conquer, Sorting and Searching, and Randomized Algorithms certification is a course that is provided by Coursera in association with Stanford University. This is a very short course that teaches the candidates regarding algorithms which is considered as the mainstream of Computer Science where algorithms can be used in practical applications.

The Divide and Conquer, Sorting and Searching, and Randomized Algorithms certification syllabus tends to cover introductory aspects of algorithms with some amount of programming exercises. This course belongs to course number one on the algorithms specialization which gives the conceptual learning for elementary level of mathematics and its implementation.

Divide and Conquer, Sorting and Searching, and Randomized Algorithms training is an intermediary level course that will help the candidates become strong with their technical skills so that they are able to speak well regarding algorithms with other Computer Programmers confidently.

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Algorithms Certification Courses

The Trees and Graphs: Basics online course is a study of the algorithms and data structures associated with trees and graphs such as tree data structures, binary search trees, self-balancing trees, graph data structures with some fundamental traversal algorithms on graphs. The online program is provided by the online educational platform Coursera and the course curriculum is offered by the University of Colorado Boulder. The course consists of 34 hours of course content that is scheduled for four weeks. The educator for this online training is associate professor Sriram Sankaranarayanan from the University of Colorado Boulder. 

The Trees and Graphs: Basics is part of the ‘Data Science Foundations: Data Structures and Algorithms Specialization’ and the Master of Science in Data Science(MS-DS) degree hence this online course can be taken for the MS-DS degree. This advanced-level program enables the students to utilize flexible deadlines for convenience to complete the course and a shareable course certificate after course completion.

Shortest Paths Revisited, NP-Complete Problems and What To Do About Them is an online programme designed for intermediate-level students. The online course administered by Stanford University will give the students a deep dive into the shortest paths and related aspects. Shortest Paths Revisited, NP-Complete Problems and What To Do About Them Certification Syllabus, prepared by Tim Roughgarden, the Professor of Computer Science, will walk the candidates through various topics of algorithms such asBellman-Ford, Floyd-Warshall, Johnson, etc. 

Shortest Paths Revisited, NP-Complete Problems and What To Do About Them Certification Course, administered by Coursera, is a flexibly developed course and the students can set their deadlines as per their comfort. The students will also be given subtitles in multiple languages. Shortest Paths Revisited, NP-Complete Problems and What To Do About Them Certification by Coursera is the fourth and the last course in the Algorithms Specialization. 

The I/O-efficient algorithms online course is an EIT digital-based course instructed by Dr Mark de Berg through a wholly online platform for learning with Coursera. The entire programme runs for a duration of 9 hours offering a verified certificate. The I/O-efficient algorithms syllabus will progress through three weeks starting with a curriculum starting with an introduction, cache algorithms, replacement policies and efficient sorting.

The course will be taught in the English language with subtitles in English, Spanish, Russian, French and Portuguese. The  I/O-efficient algorithms by Coursera are planned as advanced level coursework with flexible deadlines for completion. The candidates will need to have some basic prerequisite in the area of mathematics and algorithms to be eligible to enrol for the programme.

Traditional algorithmic tools are often inefficient for solving various real-world algorithmic problems. For example, many such problems are NP-hard; hence, these tools can’t solve them correctly. Thus, the Approximation Algorithms certification course will make you fluent with the critical algorithmic techniques and concepts that can deal with these challenges efficiently. You can employ such techniques instead of the optimal solution; you need an approximation close to this optimal solution. 

Curated by EIT Digital, the Approximation Algorithms certification syllabus offers 100% online lessons and covers vital topics to make you an expert. These include PTAS, knapsack problems, vertex-cover problems, linear programming, load balancing, scheduling algorithms, and numerous other learnings. By covering these, you’ll become adept in finding the required approximations of a problem’s optimal solutions for solving it efficiently. 

The Approximation Algorithms online course features a renowned instructor, Professor Dr Mark de Berg. It also provides self-directed deadlines to help you learn comfortably, along with English subtitles for the programme videos. Moreover, you can also purchase the training completion certificate to access the valuable accreditation and graded assessments.

The Automated Reasoning: Symbolic Model Checking certification course offers to learn through online mode. The course talks about the properties of acting systems and programs. The course can be pursued as a free programme in the audit mode, provided the students will not be able to get access to the graded quizzes, assessments, and certification. 

The Automated Reasoning: Symbolic Model Checking certification syllabus includes four weekly modules that can be completed in the time period of 13 hours. Students can also enable English subtitles in the programme. 

There are no restrictions regarding the timings of the sessions or attendance percentage since this is a self-paced programme that lets the user choose their own deadlines. The certification of the Automated Reasoning: Symbolic Model Checking online course is achievable at the end of the course if the participants successfully complete the course after taking the subscription of the programme.

If you want to learn the applications for satisfiability tools, Automated Reasoning: satisfiability course is perfect for you. The programme uses several examples to give you a glimpse into the various scenarios where satisfiability can be applied. These examples include program correctness, scheduling problems, puzzle-solving and fitting rectangles used for printing posters. 

Besides this, Automated Reasoning: satisfiability training also offers the underlying theory of using the resolution as a primary approach to propositional satisfiability, applying simplex methods for solving linear inequalities and using the CDCL framework for scaling up big formulas. You will learn these concepts through a series of video lessons, reading material, practise assignments and graded assignments. However, the course encourages you to use the knowledge you receive and apply SAT/SMT to several other problems, such as the problems presented in the honour’s assignment.

Automated Reasoning: satisfiability certification is an online course that takes about 25 hours to complete. It is an intermediate course taught by Hans Zantema and is offered by EIT Digital. You can either join the course for free or take the Coursera membership and secure a certificate of completion.

Cryptography and Hashing Overview is an online course meant for beginner-level learners to get acquainted with the blockchain, in general, and cryptography in particular. Cryptography and Hashing Overview Certification Syllabus will shed light on the various aspects of blockchain, cryptography, hashing and the like. 

Cryptography and Hashing Overview Certification Course, offered by Coursera, is the second in the 4 courses of Blockchain Specialization. By joining the course by paying the fee, the learners will be provided with unlimited access to the remaining three courses. Cryptography and Hashing Overview Certification by Coursera is provided by the Division of Continuing Education of the University of California, Irvine.

The soul of programming is said to be data structures and algorithms. Data structures aim to hold the data while the algorithms aim to solve the problem using the data. Data structures are the key to the computer algorithms which help the programmers to manage the data efficiently. The perfect selection of data helps to enhance the efficiency of the computer programme.

Computer science in this era is all about sorting and computing from given data. So, it is necessary to have a powerful knowledge about data structure, it will help one deal with different ways of arranging, storing and processing the data. It helps in utilizing maximum space and also decreases the complexity in deletion of data, addition as well as insertion of data.

To be a successful data processor one should acquire all the skills appropriately and should master their skills that will make them stand out of the crowd. Each and every company searches for an employee who has the ability to overcome all the problems and keep up to the needs and the requirements of the company. This is the platform where they can shape their skills for the same.

Algorithms on graphs is a much-used concept in navigation services and has thus found supreme applicability in the current scenario. Whether it be road networks, social networks or computer networks, this domain offers a lot of scope for learning, especially for engineers. To think of the fastest time to commute, people often resort to a connected set of computers which are strewn through an efficient algorithm or a dense network. This also helps in detecting communities and leaders on Facebook.

Algorithms on Graphs course is one another valuable offering by Coursera which delves deep into the insights of graphs and its varied properties. Candidates will learn traversing graphs and orderly traversing of the same to perform meaningful tasks. Discussion on shortest paths algorithms from basic level used to open doors till faster ones used in Google Maps will be conducted. Pursuing this course will also help candidates in pursuing Fast Shortest Routes industrial capstone projects if they wish to.

This course concludes with minimum spanning trees utilised in road planning and telephone and computer networks.

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming is an online programme provided by Stanford University that will help the learners to have a solid understanding of greedy algorithms and dynamic programming.  Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming Certification Syllabus will walk the student through many concepts including scheduling, minimum spanning trees, knapsack, sequence alignment, and the like. 

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming Certification Course, offered by Coursera, is an intermediate course that is the third in the four courses of Algorithms Specialization. Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming Certification by Coursera is structured in a fashion in which the students can decide the deadline on their own and can be completed within about 14 hours.