11 Best Coursera Courses for Algorithms And Data Structure In 2020

11 Best Coursera Courses for Algorithms And Data Structure In 2020

If you are actively looking to learn algorithms and data structures, and also looking for the best platform to start this journey, then you are in the right place.

Nowadays, the environment has become very competitive, and you just can’t afford to miss out on this evolution. And I guess that’s why you are here.

To be more proactive with your learning than the past generation was, you need to learn from only the best, courses on Coursera.

Infact, Coursera will give you the best courses for algorithms that will give you critical concepts that you might have never known about before and that will make you a part of the new generation.

In this article, I am going to share with you some of the best Coursera courses for algorithms that will help you in this journey to greatness.

Now, I know maybe you or your friend runs a business and you might need knowledge analyzing your business.

That’s why I also reviewed the best Coursera courses for business analytics, you should check it out.

Now let’s get to the order of the day.

Here are some quick links to help you get to these courses on Coursera…

COURSESSTUDENTS
1. Algorithms, Part I715, 118
2. Bitcoin and Cryptocurrency Technologies433, 039
3. Algorithmic Toolbox303, 840
4. Cryptography I281, 398
5. Algorithms, Part II191, 094
6. Divide and Conquer, Sorting and Searching, and Randomized Algorithms143, 021
7. Algorithms on Graphs73, 232
8. Algorithms on Strings54, 429
9. Advanced Algorithms and Complexity50, 394
10. Analysis of Algorithms47, 649
11. Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming47, 577

Here is a detailed summary of what you’ll learn in each of the algorithm courses on Coursera. 

We’ll look at what each course is about, what you’ll be able to do after the course as well as the requirements and skill level you need to have before starting any of these courses

1. Algorithms, Part I

This course for algorithms on Coursera 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, this part I covers elementary data structures, sorting, and searching algorithms. 

This course provides an excellent illustration of the basic approach to developing and analyzing algorithms by considering the dynamic connectivity problem.

You will also learn about the two fundamental data types for storing collections of objects: the stack and the queue.

And implement each using either a singly-linked list or a resizing array. 

Additionally, the instructors introduce two advanced Java features: generics and iterators. That simplifies client code. 

Finally, you will consider various applications of stacks and queues ranging from parsing arithmetic expressions to simulating queueing systems.

Part II of this course will focus on graph- and string-processing algorithms.

All the features of this course are available for free.  

But it does not offer a certificate upon completion.

Rating: 4.9 stars (7, 652 ratings).

Level: Intermediate.

Students 715, 118.

Duration: 53 hours.

Language: English.

2. Bitcoin and Cryptocurrency Technologies

To really understand what is special about Bitcoin, we need to understand how it works at a technical level

That’s why, the instructors address the important questions about Bitcoin, such as:

  1. How does Bitcoin work? 
  2. What makes Bitcoin different? 
  3. How secure are your Bitcoins? 
  4. How anonymous are Bitcoin users? 
  5. What determines the price of Bitcoins? 
  6. Can cryptocurrencies be regulated? 
  7. What might the future hold?

After this course, you’ll know everything you need to be able to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. 

You’ll have the conceptual foundations you need to engineer and secure a software that interacts with the Bitcoin network.

And you’ll be able to integrate ideas from Bitcoin in your own projects.

All the features of this course are available for free.  

Though this course does not offer a certificate upon completion.

Rating: 4.7 stars (2, 369 ratings).

Level: Beginner.

Students: 433, 039.

Duration: 23 hours.

Language: English.

3. Cryptography I

Cryptography is an indispensable tool for protecting information in computer systems

In this algorithms course on Coursera, you will learn the inner workings of cryptographic systems and how to correctly use them in real-world applications. 

The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic. 

In this course, you will examine many deployed protocols and analyze mistakes in existing systems. 

The second half of the course discusses public-key techniques that let two parties generate a shared secret key. 

Throughout the course you will be exposed to many exciting open problems in the field and work on fun programming projects. 

If you continue to the second course (Crypto II) the instructors will cover more advanced cryptographic tasks such as zero-knowledge, privacy mechanisms, and other forms of encryption.

Rating: 4.8 stars (3,314 ratings).

Level: Beginners.

Students: 281,398.

Duration: 23 hours.

Language: English.

4. Algorithmic Toolbox

This is one of the most comprehensive courses on algorithms that covers basic algorithmic techniques and ideas.

These ideas can be used for computational problems arising frequently in practical applications: 

  • Sorting and searching.
  • Divide and conquer.
  • Greedy algorithms.
  • Dynamic programming. 

You will also 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. 

Additionally, you will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second).

By the end of this best Coursera course for algorithms, you will have covered the ins and outs of the algorithmic toolbox and have enough to go into the real world with.

Rating: 4.6 stars (9,116 ratings).

Level: Intermediate.

Students: 303,840.

Duration: 37 hours.

Language: English.

5. Algorithms, Part II

This is the best data structure and algorithm course I have come across on Coursera.

It covers the essential information that every serious programmer needs to know about algorithms and data structure. 

With emphasis on applications and scientific performance analysis of Java implementations. 

Before you take this course, you should check out part I that covers elementary data structures, sorting, and searching algorithms. 

This part II of the course focuses more on graph- and string-processing algorithms.

All the features of this course are available for free.  

But in case you are looking for a certificate by the end of your learning, I got bad news for you, this course does not offer a certificate upon completion.

Rating: 4.9 stars (1,380 ratings).

Level: 191, 094.

Students: Intermediate.

Duration: 63 hours.

Language: English.

6. Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Honestly speaking, this  is one of the best Coursera courses to learn algorithms.

It is an impressive course to learn data structure and algorithms which I have attended and found very suitable. As it also teaches you more about the core data structures and algorithms used in everyday applications.

The primary topics covered in this part of the specialization are: 

  • Asymptotic (“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).

 I strongly recommend that you go through both pieces (part 1 and 2) to understand both the basic and advanced data structures.

Rating: 4.8 stars (4,144 ratings).

Level: Intermediate.

Students: 143, 021.

Duration: 17 hours.

Language: English.

7. Algorithms on Graphs

If you have ever used a navigation service to find optimal route and estimate time to destination, you’ve used algorithms on graphs.

Graphs arise in various real-world situations as there are road networks, computer networks, and most recently, social networks! 

If you’re looking for the fastest time to get to work, cheapest way to connect a set of computers into a network or an efficient algorithm to automatically find communities…

And opinion leaders on Facebook, you’re going to work with graphs and algorithms on graphs.

In this best algorithms course on Coursera, you will first learn what a graph is and what are some of the most important properties. 

Then you’ll learn several ways to traverse graphs and how you can do useful things while traversing the graph in some order. 

You will also learn about the shortest paths algorithms from the basic ones to those which open doors for 1,000,000 times faster algorithms used in Google Maps and other navigational services. 

Then you will use these algorithms if you choose to work on the Fast Shortest Routes industrial capstone project. 

You will finish with minimum spanning trees which are used to plan road, telephone and computer networks.

Finally, you will also find applications in clustering and approximate algorithms.

Rating: 4.7 stars (1,759 ratings).

Level: Intermediate.

Students: 73, 232.

Duration: 55 hours.

Language: English.

8. Algorithms on Strings

The world and the internet are full of textual information

We search for information using textual queries, we read websites, books, and e-mails. 

All those are strings from the point of view of computer science. 

To make sense of all that information and make search efficient, search engines use many string algorithms

Moreover, the emerging field of personalized medicine uses many search algorithms to find disease-causing mutations in the human genome.

This is a very exciting course, but at the same time, this course is both comprehensive and challenging. And if you are looking for one of the best Coursera courses for algorithms then you should sign up for this course.

You will get a straightforward guide to implement the most up to date algorithms from scratch: algorithms on strings.

Rating: 4.5 stars (878 ratings).

Level: Intermediate.

Students: 54, 429.

Duration: 17 hours.

Language: English.

9. Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

This is the best Coursera course for algorithms that I have come across for learning Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming.

The course covers the techniques you need in the real world to handle and solve difficult algorithms that you might see for the first time.

And if you are a beginner and are having a hard time understanding Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming, then this is the perfect course for you.

Some of the primary topics in this part of the specialization are: 

  1. Greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes). 
  2. Dynamic programming (knapsack, sequence alignment, optimal search trees).

You will also get advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.

Rating: 4.8 stars (1,054 ratings).

Level: Intermediate.

Students: 47, 577.

Duration: 15 hours.

Language: English.

10. Advanced Algorithms and Complexity

You’ve learned the basic algorithms now and are ready to step into the area of more complex problems and algorithms to solve them.

Advanced algorithms build upon basic ones and use new ideas.

You will start with network flows which are used in more typical applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision

You will then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements and many others. 

Next you will discuss inherently hard problems for which no exact good solutions are known (and not likely to be found) and how to solve them in practice. 

You will finish with a soft introduction to streaming algorithms that are heavily used in Big Data processing. 

Such algorithms are usually designed to be able to process huge data sets without being able even to store a dataset.

Rating: 4.6 stars (515 ratings).

Level: Advanced.

Students: 50, 394.

Duration: 27 hours.

Language: English.

11. Analysis of Algorithms

This course for algorithms on Coursera teaches calculus that enables precise quantitative predictions of large combinatorial structures. 

In addition, this course covers generating functions and real asymptotics.

Then introduces you to the symbolic method in the context of applications in the analysis of algorithms and basic structures such as:

  • Permutations.
  • Trees.
  • Strings. 
  • Words.
  • Mappings.

You will not only learn about data structure but also about how you can analyze your code’s time and space complexity.

Finally, you will also learn to consider a scientific approach to developing approximate answers that mathematicians and scientists have used for centuries.

News flash! the features of this course are available for free.  

But it does not offer a certificate upon completion. So if you are looking for a course that does, then this is not the course you are looking for.

Rating: 4.5 stars (100 ratings).

Level: Advanced.

Students: 47, 649.

Duration: 20 hours.

Language: English.

Conclusion

Thats all about some of best Coursera courses for learning data structures and algorithms.

Algorithms and data structures are independent topics, so once you know how a particular data structure or algorithm works, then you can implement them in any programming language.

Here is a summary of what you’ll learn from these algorithms courses:

  • Basic approach to developing and analyzing algorithms by considering the dynamic connectivity problem
  • The inner workings of cryptographic systems and how to correctly use them in real-world applications
  • How to break a large problem into pieces and solve them recursively
  • The essential information that every serious programmer needs to know about algorithms and data structure

I hope these algorithm courses on Coursera help you learn the ins and outs of algorithms and data structure and launch a successful career in this lucrative field.

Have you ever taken any of these best Coursera courses for algorithms before?

If yes, please share your experience in the comments below.

Lerma Gray

Hey, I’m Lerma, a freelance tech writer and blogger. On this blog I write about anything related to technology. Are you looking for a budget freelance writer to produce compelling content for your business blog? Let's talk here.

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