Algorithmic Toolbox from Coursera

What's inside

Syllabus

Programming Challenges

Welcome to the first module of Data Structures and Algorithms! Here we will provide an overview of where algorithms and data structures are used (hint: everywhere) and walk you through a few sample programming challenges. The programming challenges represent an important (and often the most difficult!) part of this specialization because the only way to fully understand an algorithm is to implement it. Writing correct and efficient programs is hard; please don’t be surprised if they don’t work as you planned—our first programs did not work either! We will help you on your journey through the specialization by showing how to implement your first programming challenges. We will also introduce testing techniques that will help increase your chances of passing assignments on your first attempt. In case your program does not work as intended, we will show how to fix it, even if you don’t yet know which test your implementation is failing on.

Algorithmic Warm-up

In this module you will learn that programs based on efficient algorithms can solve the same problem billions of times faster than programs based on naïve algorithms. You will learn how to estimate the running time and memory of an algorithm without even implementing it. Armed with this knowledge, you will be able to compare various algorithms, select the most efficient ones, and finally implement them as our programming challenges!

Greedy Algorithms

In this module you will learn about seemingly naïve yet powerful class of algorithms called greedy algorithms. After you will learn the key idea behind the greedy algorithms, you may feel that they represent the algorithmic Swiss army knife that can be applied to solve nearly all programming challenges in this course. But be warned: with a few exceptions that we will cover, this intuitive idea rarely works in practice! For this reason, it is important to prove that a greedy algorithm always produces an optimal solution before using this algorithm. In the end of this module, we will test your intuition and taste for greedy algorithms by offering several programming challenges.

Divide-and-Conquer

In this module you will learn about a powerful algorithmic technique called Divide and Conquer. Based on this technique, you will see how to search huge databases millions of times faster than using naïve linear search. You will even learn that the standard way to multiply numbers (that you learned in the grade school) is far from the being the fastest! We will then apply the divide-and-conquer technique to design two efficient algorithms (merge sort and quick sort) for sorting huge lists, a problem that finds many applications in practice. Finally, we will show that these two algorithms are optimal, that is, no algorithm can sort faster!

Dynamic Programming 1

In this final module of the course you will learn about the powerful algorithmic technique for solving many optimization problems called Dynamic Programming. It turned out that dynamic programming can solve many problems that evade all attempts to solve them using greedy or divide-and-conquer strategy. There are countless applications of dynamic programming in practice: from maximizing the advertisement revenue of a TV station, to search for similar Internet pages, to gene finding (the problem where biologists need to find the minimum number of mutations to transform one gene into another). You will learn how the same idea helps to automatically make spelling corrections and to show the differences between two versions of the same text.

Dynamic Programming 2

In this module, we continue practicing implementing dynamic programming solutions.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by Pavel Pevzner, Alexander S. Kulikov, Daniel M Kane, Neil Rhodes, and Michael Levin, all of whom are recognized in the field of computer algorithms and data structures

Develops essential algorithms and data structures skills, which are core for computer science

Examines algorithmic techniques that are highly relevant to industry, including sorting, searching, divide and conquer, greedy algorithms, and dynamic programming

Explores algorithmic techniques that are essential for solving problems in genomic studies

Emphasizes hands-on learning through programming challenges to reinforce understanding and build practical skills

Covers a comprehensive range of topics, including programming, algorithmic warm-up, greedy algorithms, divide-and-conquer, and dynamic programming

Reviews summary

Essential algorithm course

Learners say this essential algorithm course is best suited for experienced coders who want to enhance their algorithm expertise who want to enhance their algorithm expertise. It offers engaging assignments, includes constant in-video quizzes, along with challenging, well documented programming exercises to help you learn. The instructors clearly explain even difficult concepts, making this a great choice for non-computer science students with some coding experience who are ready to dive deeper into algorithms.

Learners should have some programming experience before taking this course.

"So if you want to fare easily in this course, you should have basic ideas of programming in C++ Python Java."

"You already need to know how to code and to handle input and output."

"The course was okay, but it is not an introductory course, since it presupposes programming and mathematical knowledge."

Instructors are knowledgeable and explain concepts well.

"Even I was able to understand it, although I have very poor mathematical and programming background."

"Lecturers explain difficult things in the simplest terms."

"I've been programming professionally for 15 years, but I had a significant gap in my knowledge when it came to data structures and algorithms. This course helped me complete my skill set and regain a competitive advantage in the field."

Well-structured course with engaging content.

"I am unhappily surprised by the fact that some people rate this course low because it is allegedly poor explained."

"it is probably the clearest, best explained and best structured course among all algorithmic courses I've ever taken."

"Constant in-video quizzes to check understanding of the current lecture"

Programming assignments are well-documented, and offer a good learning experience.

"Programming assignments are challenging and fun to solve."

"Challenges are the parts from which you can learn a lot."

"Nice and relevant, not too hard programming assignments, with one or two optional advanced problems each week"

Some learners find it challenging.

"The level of difficulty and level of explanation vary greatly throughout the course."

"I really hate that I paid for this course, and would not recommend it to anyone."

"I would not recommend this course to anyone. I found the videos to be poorly put together and not very educational."

Limited support is available.

"There is a reason why this course is not free and you have to pay upfront to take it."

"there is pretty much no support(QA) from faculty or mentor, when you get stuck in a problem your only hope is someone might have ask a slimier question online - it could take you hours to figure out something"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Algorithmic Toolbox with these activities:

Refresher on Mathematical Concepts

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Ensure a solid foundation for understanding the mathematical concepts behind algorithms.

Browse courses on Mathematics

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Review basic mathematical concepts such as sets, functions, and relations.
Practice solving mathematical problems involving logic, algebra, and geometry.

Compilation of Algorithm Resources

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Organize and expand your understanding of algorithms by collecting relevant resources.

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Identify different sources of information on algorithms, such as websites, books, and online forums.
Create a central repository or document to store and organize your findings.
Include summaries and excerpts from the resources you find, along with your own notes and insights.

Mastering Merge Sort

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Enhance your knowledge about divide-and-conquer algorithms and sorting techniques by following through this tutorial.

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Follow the steps explained in the tutorial
Implement the merge sort algorithm in your preferred programming language
Analyze the time and space complexity of your implementation

Four other activities

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Study Group on Dynamic Programming

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Enhance your understanding of dynamic programming by collaborating with peers.

Browse courses on Dynamic programming

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Form a study group with 2-3 other classmates.
Choose a specific dynamic programming topic to focus on.
Discuss different approaches to solving problems related to the topic.
Work together to solve practice problems.

Practice Dynamic Programming Challenges

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Help yourself improve your understanding and skills with dynamic programming by practicing algorithmic challenges.

Browse courses on Greedy Algorithms

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Solve a challenge related to the topic in leetcode
Go over the solution and think how to come up with it on your own
Apply the same algorithm to a similar problem with your own data

Debug Your Code

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Become more proficient in debugging your code and identifying errors.

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intentionally introduce errors into your code
Use a debugger to step through your code and identify the source of the error
Fix the error and test your code again

Design Your Own Algorithm

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Challenge yourself and showcase your understanding of algorithms by creating your own.

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Identify a problem and define the specific goal of your algorithm.
Research existing algorithms that solve similar problems.
Design and implement your algorithm.
Test your algorithm on a variety of inputs and analyze its performance.
Present your algorithm to your classmates or online community.

Career center

Learners who complete Algorithmic Toolbox will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use a variety of mathematical skills to analyze and interpret data. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Data Scientists. This course will also teach you how to implement efficient algorithms, which is a key skill for Data Scientists who need to process large amounts of data quickly.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, and maintain software systems. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Software Engineers. This course will also teach you how to implement efficient algorithms, which is a key skill for Software Engineers who need to develop software that runs quickly and efficiently.

See salaries and explore the career path for Software Engineer

Computer Scientist

Computer Scientists conduct research on new algorithms and data structures. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which is essential for Computer Scientists. This course will also teach you how to implement efficient algorithms, which is a key skill for Computer Scientists who need to develop new algorithms and data structures.

See salaries and explore the career path for Computer Scientist

Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze financial data. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Quantitative Analysts. This course will also teach you how to implement efficient algorithms, which is a key skill for Quantitative Analysts who need to process large amounts of financial data quickly.

See salaries and explore the career path for Quantitative Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and statistical techniques to solve problems in business and industry. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Operations Research Analysts. This course will also teach you how to implement efficient algorithms, which is a key skill for Operations Research Analysts who need to solve problems quickly and efficiently.

See salaries and explore the career path for Operations Research Analyst

Financial Analyst

Financial Analysts use mathematical and statistical techniques to analyze financial data. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Financial Analysts. This course will also teach you how to implement efficient algorithms, which is a key skill for Financial Analysts who need to process large amounts of financial data quickly.

See salaries and explore the career path for Financial Analyst

Business Analyst

Business Analysts use analytical techniques to solve business problems. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Business Analysts. This course will also teach you how to implement efficient algorithms, which is a key skill for Business Analysts who need to solve problems quickly and efficiently.

See salaries and explore the career path for Business Analyst

Data Analyst

Data Analysts use analytical techniques to analyze data. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Data Analysts. This course will also teach you how to implement efficient algorithms, which is a key skill for Data Analysts who need to process large amounts of data quickly.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians use mathematical and statistical techniques to analyze data. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Statisticians. This course will also teach you how to implement efficient algorithms, which is a key skill for Statisticians who need to process large amounts of data quickly.

See salaries and explore the career path for Statistician

Artificial Intelligence Engineer

Artificial Intelligence Engineers design and develop artificial intelligence systems. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Artificial Intelligence Engineers. This course will also teach you how to implement efficient algorithms, which is a key skill for Artificial Intelligence Engineers who need to develop systems that run quickly and efficiently.

See salaries and explore the career path for Artificial Intelligence Engineer

Machine Learning Engineer

Machine Learning Engineers design and develop machine learning models. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Machine Learning Engineers. This course will also teach you how to implement efficient algorithms, which is a key skill for Machine Learning Engineers who need to develop models that run quickly and efficiently.

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Web Developer

Web Developers design and develop websites. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Web Developers. This course will also teach you how to implement efficient algorithms, which is a key skill for Web Developers who need to develop websites that run quickly and efficiently.

See salaries and explore the career path for Web Developer

Software Developer

Software Developers design, develop, and maintain software applications. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Software Developers. This course will also teach you how to implement efficient algorithms, which is a key skill for Software Developers who need to develop applications that run quickly and efficiently.

See salaries and explore the career path for Software Developer

Systems Analyst

Systems Analysts design and develop computer systems. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Systems Analysts. This course will also teach you how to implement efficient algorithms, which is a key skill for Systems Analysts who need to design and develop systems that run quickly and efficiently.

See salaries and explore the career path for Systems Analyst

Database Administrator

Database Administrators manage and maintain databases. Algorithmic Toolbox can help you build a foundation in algorithms and data structures, which are essential skills for Database Administrators. This course will also teach you how to implement efficient algorithms, which is a key skill for Database Administrators who need to manage and maintain databases quickly and efficiently.

See salaries and explore the career path for Database Administrator