Free Algorithms Courses & Certifications

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 Introduction to Graduate Algorithms online programme is offered by Udacity and developed by the Georgia Institute of Technology, US. It features rich learning content related to the analysis and design of computer algorithms. The course is free to enrol in and has an approximate timeline of three months. You will get access to video lectures, interactive quizzes and reading material.

Throughout the Introduction to Graduate Algorithms online course by Udacity, you will explore a wide range of graduate-level algorithm concepts. These include computational intractability, Fast Fourier Transform (FFT), dynamic programming, Rivest-Shamir-Adleman (RSA) cryptosystem, minimum spanning tree, Markov chains, Max-SAT approximation, Fibonacci numbers, divide and conquer, randomised algorithms, etc.

Udacity’s Introduction to Graduate Algorithms online training aims to explain the algorithms for fundamental problems and the methods for algorithm design. During this advanced-level programme, you will also study hashing using graph algorithms, linear programming, bloom filters, max-flow algorithm and non-deterministic polynomial-time (NP) completeness.

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 Computational Complexity Theory program offers a great learning experience in the field of computational complexity theory. Students who pursue this course will come to know different topics every week through this course. Candidates will be informed on topics like hierarchy theorems, types of complexities, limitations, etc. The Computational Complexity Theory online course offers full-time access to the course with no limitations or restrictions related to the timings of the course or attendance. Students are requested to own a stable internet connection and a system through which they can log in to the course.

The Computational Complexity Theory training offers a certificate towards the end of the course only if the candidate agrees to pay the exam fees and qualifies the same fulfilling the minimum eligibility criteria. The course takes 12 weeks of time to complete the Computational Complexity Theory certification syllabus. However, students can choose to take longer than the estimated time since this is a self-paced learning program. The course provides a professional level of training and can be taken up by candidates who are interested in computer science.

The Model Checking certification course is a 12-week elective programme that is entirely online. This course is the responsibility of the Chennai Mathematical Institute professor Srivathsan. Swayam, IIT Madras and NPTEL have jointly taken up responsibility along with the institute to offer a certificate jointly. 

Over the years the use of safety-critical systems including embedded software that is dealt with in regular life has increased. Hence this online Model Checking training course is a great introduction to learning the tools that are required for model-checking. Model checking is nothing but a research field that looks after the challenge of making use of models in controller verification. Ultimately the main aim of the course is to give the students a look at the system which is used mainly for finite-state machine extensions. 

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. 

Design and Analysis of Algorithms program is an undergraduate course in the field of Foundation of computing and Computer Science and Engineering. It is a free MOOC that will be held on the online learning platform Swayam. Swayam is a learning portal and an initiative by the Ministry of Education, Government of India.

The syllabus of the Design and Analysis of Algorithms certification has been designed by Chennai Mathematical Institute in association with NPTEL. The program will be taught by professor Madhavan Mukund, the Dean of Studies at Chennai Mathematical Institute. Along with video lectures, candidates will have assignments and a list of books and references to understand the course contents better. 

During the Design and Analysis of Algorithms training, candidates will explore various topics such as Intractability, Design techniques, asymptotic complexity, data structures, algorithm on graphs, sorting, and searching. The course also offers a certification for interested eligible candidates. However, certification is granted only if students pass the final test.

The Programming, Data Structures, and Algorithms Using Python certification course imbibe Python problem-solving and programming fundamentals in its students. A Chennai Mathematical Institute offering, this eight-week curriculum features robust industry recognition amongst programming-oriented companies. Primarily built for undergraduates, this program falls under the following purviews - ‘Foundations of Computing’, ‘Programming’, ‘Artificial Intelligence, ‘Computer Science and Engineering, and ‘Data Science’

The extensive Programming, Data Structures, and Algorithms Using Python certification syllabus cover multiple concepts, including introductory concepts like loops, conditionals, functions, strings, etc. Candidates learn about sorting algorithms, backtracking, using files, exception handling, and more. Regarding data structures, the course also discusses Python dictionaries, objects, and classes to define various data types, including binary search trees and linked lists.

The Programming, Data Structures, and Algorithms Using Python training also offers an optional certificate to help candidates actively seek employment or educational growth. Aspirants can acquire this by clearing the requirements. These include scoring well in the weekly assignments and clearing Swayam’s two examinations.

The Traditional and Non-Traditional Optimization Tools training is designed to explain the optimization process and its principles in depth. You will study traditional optimization tools during this course, including their subgroups, namely - direct search and gradient search methods, steepest descent, random walk method, etc. You will become aware of the significance of optimization to develop the most efficient product at the lowest cost.

The Traditional and Non-Traditional Optimization Tools online program also provides insights into non-traditional tools of optimization such as the genetic algorithm (GA), particle swarm optimization, simulated annealing, etc. It is an eight-week-long course with 20 hours of video lectures, where these methods will be explained along with relevant numerical examples.

The Traditional and Non-Traditional Optimization Tools certification course teaches working principles of multi-objective optimization. These include goal programming, distance-based Pareto-GA, weighted sum approach, and more. You will also understand techniques to handle constraints, benefits, and drawbacks of GA. This elective course also provides a completion certificate when you fulfill certain criteria. 

The Algorithms: Design and Analysis, Part 2 online course by edX, is aimed at learners who have at least some experience in programming. It is a self-paced intermediate-level programme with a rigorous curriculum that focuses more on conceptual understanding and the bigger picture than mathematical details and low-level implementation.

The topics covered under the Algorithms: Design and Analysis, Part 2 certification syllabus include Greedy Algorithms (Clustering, Scheduling, Huffman Codes, Minimum Spanning Trees), Dynamic Programming (Sequence Alignment, Shortest Paths, Optimal Search Trees, Knapsack), NP-Completeness, Local Search, and Analysis of Heuristics.

The Algorithms: Design and Analysis, Part 2 training programme by edX includes various assessments through which learners can practice and master Algorithms. These include six multiple-choice problem sets, six programming assignments, and a final multiple-choice exam. 

Moreover, there is no due date for these assignments, allowing learners to work through the course at their own pace. But to complete the course comfortably within six weeks, they must study two to four hours a week. Edx has 2 tracks namely the verified track and the audit track which allows the students to finish off the course. During the verified track, the candidates will get unlimited but paid access to the course materials. In the audit track, the candidates will be getting limited but free access to the course materials.

Algorithms: Design and Analysis, Part 1 online course will explore the heart of computer science - algorithms. Candidates will learn, practice, and master the fundamentals of algorithms using a combination of video lectures, programming assignments, and multiple-choice quizzes to help them evaluate their progress.

Algorithms: Design and Analysis certification syllabus will provide information on various topics such as sorting and searching, data structures, graph primitives, randomized algorithms, and the 'Big-Oh' notation. This is an intermediate curriculum and requires some experience on the part of candidates in programming languages. These can include C, Java, or Python languages.

Algorithms: Design and Analysis by edX is a six-week, online certification course that features faculty members from Stanford University.  Students will have to devote two to four hours every week to this course and give a multiple-choice final at the end. It is a self-paced course that provides English transcripts of all the lectures for better understanding. Learners can get enrolled in the course for free or by paying a small amount. If they want to learn the course without paying anything they may opt for the audit track where limited access is given. On the other hand, if they want unlimited course access they may opt for admission using the verified track for which they may have to pay a small amount.

Computing in Python III: Data Structures training will allow the students to learn about the complex ways that are included in files, data, dictionaries and lists for building and structuring programmes. The five-week programme will deal with - loops, conditionals, and functions by learning the basics of Python programming. After Computing in Python III: Data Structures comes to an end the candidates will be able to solve strong and complex programme statements. The programme comprises several parts that will be delivered with the help of short video lectures. 

The Computing in Python III: Data Structures certification by edX has included the listed topics like- lists, strings, output and inputs in its curriculum. The programme will allow the applicants to work on real-world problems. The students will be able to grade applications that will be tracked and upgrade the average score of an individual over time. The students will also be solving multiple-choice questions in the Computing in Python III: Data Structures certification course. The candidates can learn the course in a self-paced mode both during the audit or verified tracks. There are two main differences between the two tracks. The candidates will be getting unlimited time to learn the course with some money during the verified track. In the audit mode, the candidates will only have limited access to the course material free of cost without the chance to secure a certification.

Computing in Python IV: Objects and Algorithms certification offered by the platform of edx gives opportunity to all students who want to learn a python programming language and are interested to pursue this career professionally. Students have to attend the Computer in Python IV: Objects and Algorithms course in 100 per cent online mode. Participants need to spend at least 5 weeks studying for Computing in Python IV: Objects and Algorithms certification syllabus. Learners should invest 9-10 works per week to complete the course. 

Computing in Python IV: Objects and Algorithms training is created in association with Georgia Tech for this course. Students will learn about the subjects such as computer science for learning through this Computing in Python IV: Objects and Algorithms certification course. Candidates who will be able to complete the course can gain verified certification for this programme. Students need to pay the quoted amount by the platform for availing of the certificate. Students can avail the course at zero cost as well. The programme is an introductory level programme.

Participants who are interested to learn through this programme have the freedom to learn the subjects according to their schedules as this course is a self-paced learning programme. Though the course can be learned depending on one's schedule the candidates will have only limited access to the course during the audit track but unlimited time to complete the course in the verified track.

The Algorithm Design and Analysis Training Course is a self-paced intermediate level course constituting the Computer Science Essentials for Software Development Professional Certificate program. The online course delivered through expert course materials will discuss the design and analysis of algorithms and related topics.

The Algorithm Design and Analysis Live Course can be opted by anyone interested in learning about problem-solving skills using computational methods. The 4 week-long course requires learners to have basic knowledge of discrete mathematics, probability, and Java programming language.

After successful completion of the Algorithm Design and Analysis Certification Course on the edX platform, learners will receive a valid course certificate. The course will be taught by Sampath Kannan, faculty of Computer and Information Science at the University of Pennsylvania.

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.