11 Best Algorithms Courses & Certifications Online In 2023
Discover the 11 best algorithms courses and certifications online in 2023, handpicked and curated after analyzing millions of enrolled students, ratings, and reviews, catering to various skill levels and learning goals in the ever-growing field of computer science.
We independently evaluate all recommended online courses. If you click on
links we provide, we may receive compensation. Learn more.
Choosing the right algorithms course can be a daunting task, especially with an overwhelming number of options available online. Fear not; we have meticulously researched 1,289 popular algorithms courses offered by various providers, analyzed a staggering 32,293,083 enrolled students who have left 1,694,797 ratings and reviews, helping you make an informed decision. To bring you the cream of the crop, we considered multiple factors throughout the selection process, such as rating, reviews, enrollments, student satisfaction, valuable and engaging content, comprehensive curriculum, release date, affordability, and our own experiences and expertise in the field.
As a result, we have compiled a list of the top 11 algorithms courses and certifications suitable for learners at distinct levels of expertise, from beginners to advanced programmers. These hand-picked courses cater to various learning goals, encompassing essential topics like optimizing algorithm efficiency, mastering algorithms and data structures, understanding string algorithms, and delving deep into computation theory. This curated list will surely save you time and effort, ultimately guiding you through a systematic and enriching journey to elevate your algorithmic prowess.
This course delves into the critical knowledge every serious programmer should possess regarding algorithms and data structures, with particular focus given to their applications and scientific performance analysis using Java implementations. The first part of the course tackles elementary data structures, sorting, and searching algorithms, while the second part concentrates on graph- and string-processing algorithms.
All the components of this course can be accessed free of charge, providing a thorough and cost-effective learning experience for individuals looking to strengthen their understanding of algorithms and data structures. However, it should be noted that a certificate will not be granted upon completing the course.
Best for:
This course is ideal for those who want to gain a strong foundation in the knowledge of algorithms and data structures, as well as their applications and scientific performance analysis using Java implementations. It offers a comprehensive and accessible learning experience to improve problem-solving skills, efficiency in coding, and understanding of various types of algorithms across different industries.
This comprehensive course delves into fundamental algorithmic techniques and concepts regularly employed in practical applications. The curriculum covers vital topics such as sorting and searching, divide and conquer, greedy algorithms, and dynamic programming. Students will be exposed to a wealth of theoretical knowledge, including data sorting and its benefits in searching, breaking down complex problems into smaller parts for recursive solving, understanding when to opt for greedy approaches, and the application of dynamic programming in genomic studies.
Throughout the course, learners will have ample opportunities to hone their skills in tackling computational problems, devising innovative algorithms, and implementing solutions in an efficient manner, ensuring optimal performance with minimal execution time. This well-rounded education in algorithmic techniques will empower students to excel in various fields and tackle complex real-world challenges with ease and confidence.
Best for:
This course is ideal for those looking to improve their problem-solving skills, enhance their understanding of algorithms used in computer science and software development, and learn how to design and analyze algorithms for efficiency and optimized performance. It covers a wide range of algorithmic techniques and concepts, enabling students to excel in various fields and tackle complex real-world challenges with confidence.
This course delves into the crucial knowledge that every dedicated programmer should possess regarding algorithms and data structures, emphasizing the applications and scientific performance evaluation of Java-based implementations. The first part of the course tackles elementary data structures, sorting, and searching algorithms, while the second part zeroes in on graph- and string-processing algorithms.
All aspects of this course are readily accessible at no cost, providing programmers with an excellent learning opportunity. However, it is important to note that a certificate of completion is not offered upon finishing this course.
Best for:
This course is best for those wanting to gain crucial foundational knowledge of algorithms and data structures, as well as improving problem-solving skills and efficiency in coding. Additionally, it covers essential elements such as graph- and string-processing algorithms, which is helpful for those interested in text processing applications and advanced programming projects.
This comprehensive course focuses on the core principles and applications of algorithms, which are essential components in the world of programming. By employing the most popular and versatile algorithms for tasks such as data searching, sorting, and value counting, learners will deepen their understanding of programming and improve their problem-solving skills. The course covers concepts such as recursion and data structures, and delves into the performance implications of various algorithms. Additionally, students will learn how to evaluate the performance of specific algorithms, further enhancing their skill set in the programming domain.
Presented by author and developer Joe Marini, the course demonstrates each algorithm in practice through the Python programming language. It's important to note, however, that the knowledge gained is applicable to other languages as well, such as C programming. This versatility ensures that the lessons learned can be easily adapted and implemented across multiple programming environments. Whether new to programming or seeking to expand their expertise, this course offers a practical and engaging approach to mastering algorithms, paving the way for success in the ever-evolving field of software development.
Best for:
This course is best for learners seeking to gain foundational knowledge in algorithms and their implementation, as well as improving problem-solving skills and efficiency in coding. It covers concepts such as recursion, data structures, and performance implications, while demonstrating each algorithm using the Python programming language.
This course aims to introduce the broader discipline of computer science to individuals who have a basic understanding of Java programming. It covers the second half of the book Computer Science: An Interdisciplinary Approach and focuses on demystifying computation and building awareness about the substantial intellectual underpinnings and rich history of the field of computer science.
Throughout the course, learners will be introduced to classic algorithms and scientific techniques for evaluating performance in the context of modern applications. The course also discusses classic theoretical models, addressing fundamental questions about computation, such as computability, universality, and intractability. Additionally, topics such as machine architecture, machine-language programming, logic design, and the development of a full CPU design from the ground up will be explored. The course emphasizes the relationships between applications programming, the theory of computation, real computers, and the field's history and evolution, highlighting the contributions of notable figures such as Boole, Shannon, Turing, and von Neumann. All features of this course are available for free, and no certificate will be offered upon completion.
User review:
I've taken this course as one of few useful classes available on Coursera via AT&T continued education program. This course certainly allowed me to refresh memory on many philosophical CS topics and even learn something new.
The idea of teaching programming from the lowest-level possible and the introduction of TOY-8 assembly with !!!cpu schematics!!! is a very good idea. Gradual transition from mathematical concepts to physical hardware is what makes this course unique.
This class is not about programming. This class is not about algorithms. It it a good CS 101 introductory course. It is for somebody who already knows math, logic, basic electronics and basic programming to give a taste on what CS is about. Or for somebody like me to refresh memory on rarely used topics.
For introductory course it is too heavy-weight in my opinion. The goal of covering everything from Turing Machine to actual hardware is too ambitious and requires much more than 10 weeks to cover. [1]... Read More
DENIS K
Best for:
This course is excellent for individuals seeking to delve into classic algorithms, the theory of computation, and machine architecture, while also exploring the rich history and intellectual underpinnings of computer science.
This comprehensive course focuses on advanced learning algorithms, enabling students to build and train neural networks with TensorFlow for multi-class classification. Additionally, the program emphasizes the application of best practices for machine learning development, ensuring that the models created by students are capable of generalizing to real-world data and tasks. Alongside this, the curriculum covers the construction and utilization of decision trees and tree ensemble methods, including random forests and boosted trees, which are crucial to developing powerful AI applications.
Designed as a collaboration between DeepLearning.AI and Stanford Online, this beginner-friendly Machine Learning Specialization is directed by esteemed AI visionary and researcher, Andrew Ng. Providing a broad introduction to modern machine learning techniques, learners will gain mastery over key theoretical concepts and practical skills, enabling them to apply machine learning to tackle complex real-world problems effectively. For those seeking to break into the AI field or build a career in machine learning, this advanced course offers a strong foundation and invaluable insights into the best practices for AI and ML innovation used in Silicon Valley.
Best for:
This course is best for gaining mastery in advanced learning algorithms, such as neural networks, decision trees, and tree ensemble methods, as well as obtaining a comprehensive understanding of best practices for machine learning development and real-world applications.
This online course delves into the world of textual information, exploring the various string algorithms that search engines and personalized medicine use to make sense of vast quantities of data. By learning about key pattern matching concepts such as tries, suffix trees, suffix arrays, and the Burrows-Wheeler transform, students gain valuable insights into the foundational principles that drive efficient search processes and mutation detection in the human genome.
Throughout the course, learners will develop a deeper understanding of the computer science perspective on strings, and how this view can be applied to optimize everyday tasks such as searching for information, reading websites, books, and emails. By mastering these critical algorithms, students will be better equipped to design and implement effective solutions for a wide range of complex problems involving strings and pattern matching.
User review:
This class makes string algorithms a very interesting and enjoyable topic, and if you are interested in improving your algorithmic knowledge, I would highly suggest taking this course.
The first algorithms you will learn are motivated by problems from Bioinformatics (genome sequencing), and new interesting problems arise and get solved on the way.
All the material is very well explained so you can really understand why it works and not only how (there are even some very enjoyable proofs here)! The programming assignments (there are a lot of them) give you a hands-on experience implementing the different algorithms. This greatly improves the understanding and is therefore a crucial aspect of this class. [2]... Read More
Thassilo H
Best for:
This course is ideal for those looking to improve their knowledge of string algorithms and their applications in fields such as search engines and personalized medicine. Through learning pattern matching concepts and data structures, students will develop a deep understanding of the foundational principles essential for efficient search processes and mutation detection in the human genome.
This comprehensive course provides an in-depth understanding of various machine learning algorithms, empowering students to tackle a wide range of data science problems with confidence. Under the expert guidance of instructor Derek Jedamski, participants will learn the fundamentals of popular algorithms such as logistic regression and gradient boosting, and discover how to implement the most appropriate methodology for the task at hand. The aws machine learning platform offers a plethora of benefits, making it the perfect learning environment for those looking to expand their knowledge in this field.
In the second part of the Applied Machine Learning series, students will build upon their foundational knowledge by diving deeper into the inner workings of each algorithm. By focusing on the key drivers, advantages, and limitations of each method, learners will come away equipped with the tools and understanding necessary to choose the most suitable solution for their particular data science challenges. By the end of the course, participants will not only be well-versed in a broad selection of algorithms but also be able to make informed decisions regarding their application in real-world scenarios, giving them a competitive edge in the ever-evolving landscape of machine learning and data science.
Best for:
This course is the best for those who want to gain an in-depth understanding of various machine learning algorithms, tackle a wide range of data science problems with confidence, and make informed decisions regarding their application in real-world scenarios.
This course delves into advanced algorithms and complexity, building upon the fundamental algorithms learned in prior courses. Students will explore more intricate problems and the algorithms used to solve them, such as network flows with applications ranging from optimal matchings and flight scheduling to image segmentation in computer vision. The course then moves on to linear programming, which has applications in various optimization tasks like budget allocation, portfolio optimization, and finding the most cost-effective diet that meets specific requirements. Students will also examine inherently difficult problems that lack exact solutions, and learn how to tackle them in practice. Lastly, the course offers a gentle introduction to streaming algorithms, which are widely used in Big Data processing and designed to process massive datasets without the need for storage.
Instructors of the course use a comprehensive and engaging approach to teach these concepts, ensuring that students gain a deep understanding of advanced algorithms and their practical applications. As a result, students will develop critical problem-solving skills that can be applied in various fields, such as computer science, operations research, and management science. Whether you are a seasoned programmer or a professional in a related field, this course is an excellent opportunity to expand your knowledge and expertise in advanced algorithms and complexity.
User review:
When they say advanced algorithms and complexity, they mean it. I was initially under the presumption that it would be a straight forward video course, without any assignments. But when I had to start with programming assignments that's when the real test started. Amazing set of tutorials. Would have liked if the courses had more varied examples. [3]... Read More
Madhusudan H J
Best for:
This course is perfect for those who desire to learn advanced algorithms and complexities while exploring their practical applications and honing critical problem-solving skills, applicable in computer science, operations research, and management science.
This comprehensive course focuses on the study of algorithms and their potential for predicting large combinatorial structures. Learners will be introduced to generating functions, real asymptotics, and the symbolic method, applied in the context of algorithm analysis and fundamental structures like permutations, trees, strings, words, and maps.
While the course is entirely free, it is important to note that no certificate will be awarded upon completion. Students can still greatly benefit from the content, gaining valuable skills and knowledge that can be applied to a wide range of algorithm-related fields.
User review:
This course offers an extensive coverage of mathematical material like tools and techniques, putting special emphasis on simple principles and never losing its focus on the general perspective of the topic.
Developing insight on analytic functions together with combinatorics and the practical applications of theory into code gives a significant advantage over using naive approaches.
A special appreciation to Prof. Sedgewick's endless efforts for disseminating mathematical knowledge among programmers, over this platform and even outside!
Thank you very much. [4]... Read More
Ivan F
Best for:
This course is ideal for those who want to learn about the algorithms used for predicting large combinatorial structures and gain valuable skills in generating functions, real asymptotics, and the symbolic method.
This comprehensive course delves into the world of algorithms, providing learners with the knowledge and tools to structure and apply them in solving real-life problems. These algorithms are the driving force behind the success of major web companies and startups, and the ability to understand and utilize them is often a focal point of tech interviews. The course focuses on sorting techniques such as quick sort and merge sort as well as searching algorithms, median finding, and order statistics.
As the course progresses, students will explore various types of algorithms, including numerical, string, and geometric algorithms like Polynomial Multiplication, Matrix Operations, GCD, Pattern Matching, Subsequences, Sweep, and Convex Hull. The course concludes with an examination of graph algorithms, such as the shortest path and spanning tree. By the end of the course, students will have a solid grasp of algorithms and their applications across a wide range of problem-solving situations.
Best for:
This course is ideal for those seeking a solid grasp of algorithms and their applications, including numerical, string, and geometric algorithms, as well as graph algorithms. Students gain the tools to structure and apply algorithms in solving real-life problems and enhance their coding efficiency.
7 days free trial Subscription: $33.25/m annually, $59/m monthly
Algorithms Best for comprehensive algorithm knowledge
$149 or free without certificate
How to choose best Algorithms online course
In order to choose the best algorithms course for your goals and requirements, it is essential to consider various factors and align them with your individual learning objectives. Keep the following criteria in mind while selecting a suitable course:
Understand your primary goal, whether it's gaining foundational knowledge, boosting career prospects, or improving problem-solving and coding efficiency.
Consider the extent of your prior knowledge and experience; if you're a beginner, opt for introductory courses, whereas for those with more advanced knowledge, a course on advanced algorithms and complexities might be suitable.
Take into account the specific applicative area of interest, such as machine learning, artificial intelligence, or text processing, and choose a course that covers relevant algorithms.
Assess whether the course delves into the theoretical foundations and practical applications of various algorithms, as this can be crucial in enhancing your understanding.
Evaluate the course's design and structure, ensuring it teaches how to analyze and optimize algorithms for efficiency and performance.
Lastly, choose a course which exposes you to a diverse range of algorithms used in various industries, helping you expand your skillset and adaptability.
In conclusion, carefully considering these factors will guide you in identifying the best algorithms course that aligns with your objectives, existing knowledge, and long-standing career or learning goals.
Conclusion
In conclusion, mastering algorithms is undeniably essential. Whether you seek to establish a strong foundation in algorithms, enhance your problem-solving skills, or even delve into advanced programming projects, the courses listed above cater to all levels of expertise. As the demand for skilled programmers with proficiency in algorithms continues to rise in fields like AI, machine learning, and data science, boosting your career prospects and expanding your skillset has never been more crucial.
Embarking on a journey to learn algorithms through these comprehensive courses will undoubtedly transform your understanding of algorithm theory, practical applications, and design principles. Embrace the opportunity to improve your coding efficiency, optimize performance, and develop a strong grasp on text-processing applications. In doing so, you will undoubtedly increase your value in the ever-evolving world of computer science, setting the stage for professional success and personal fulfillment.
How much does an algorithms course cost?
The cost of an algorithms course varies depending on the platform and subscription model. On Coursera, you can get a 7-day free trial, and then the subscription costs $33.25/m annually or $59/m monthly. LinkedIn Learning offers a 1-month free trial, followed by subscriptions for $19.99/m annually or $39.99/m monthly. On edX, the courses are available for $149 or can be taken for free without a certificate.
How long do algorithms courses take?
The duration of algorithms courses varies depending on the specific course and platform. The courses can range from around 1h 46m to over 60h. The time required to complete a course will depend on your level of dedication and the complexity of the material.
Do any of these courses offer certificates upon completion?
Yes, many of these online algorithms courses provide a certificate upon completion, usually for a fee. For instance, Coursera and edX offer a course completion certificate, while LinkedIn Learning offers a completion badge that can be displayed on your LinkedIn profile.
