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Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).

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What's inside

Syllabus

Week 1

Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim's MST algorithm.

Week 2

Kruskal's MST algorithm and applications to clustering; advanced union-find (optional).

Week 3

Huffman codes; introduction to dynamic programming.

Week 4

Advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides a solid foundation in greedy algorithms and dynamic programming

Taught by Tim Roughgarden, a recognized expert in algorithm design and analysis

Covers fundamental concepts used in computer science and software engineering

Requires a strong understanding of mathematics and programming

May require additional background reading or external resources for a deeper understanding of advanced topics

Students with no prior experience in algorithm design may find the pace challenging

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Reviews summary

Advanced algorithms course

Learners say that this course is a challenging but rewarding experience perfect for improving their intuition about algorithms. They particularly enjoy the smaller videos and programming assignments. Students are appreciative of the pacing and Professor Roughgarden's teaching style. Overall, those that reviewed this course found it to be positive and helpful for deepening their understanding of algorithms.

The course pace is good.

"The pace is not fast enough to get lost and not so slow to insult your intelligence."

"Great Pace - good examples - always going to the point - clear and providing good information."

"I liked the idea of splitting those 20-30 minutes videos from parts 1 and 2 into smaller ones."

The video lectures are short and helpful.

"I liked the idea of splitting those 20-30 minutes videos from parts 1 and 2 into smaller ones."

"Professor Tim Roughgarden provides an intuitive perspective to Dynamic Programming."

"The instructor makes you understand is really great."

"He's also really motivating."

The programming assignments are difficult but fun.

"Programming assignments were the most challenging but fun part!"

"This course has the most intuitive explanation of dynamic programming that I've ever seen."

"The end of the course (dynamic programming) was harder and kicked my butt a little, but I made it out with a much better grasp of the topics."

"I'm finally able to come up with my own dynamic programming solutions after taking this course, something I've never been able to do before, and it's all thanks to professor TIm Roughgarden's amazing and unique approach!"

Course content is challenging but very rewarding.

"The hurdles were high, but the content was very rewarding."

"This course is very challenging but rewarding."

"One of the most challenging course I've ever taken."

Professor Roughgarden is an amazing instructor.

"Professor Roughgarden provides an intuitive perspective to Dynamic Programming."

"The instructor makes you understand is really great."

"Great course and best computer science instructor I've ever had."

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 Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming with these activities:

Organize course materials

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Improve understanding and retention by organizing course materials systematically.

Browse courses on Greedy Algorithms

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Gather lecture notes, slides, and assignments.
Create a structured system for organizing the materials.

Review 'Introduction to Algorithms' by Cormen, Leiserson, Rivest, and Stein

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Strengthen the theoretical understanding of greedy algorithms and dynamic programming by reviewing a foundational textbook.

View Introduction to Algorithms, fourth edition on Amazon

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Read the relevant chapters on greedy algorithms and dynamic programming.
Solve practice problems from the book.

Participate in peer study sessions

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Enhance understanding and problem-solving abilities by collaborating with peers.

Browse courses on Greedy Algorithms

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Find a group of classmates with similar interests.
Set regular meeting times and discuss course material.
Work together on practice problems or projects.

Three other activities

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Show all six activities

Solve practice problems on algorithmic thinking

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Improve algorithmic thinking and problem-solving skills by solving practice problems related to greedy algorithms and dynamic programming.

Browse courses on Greedy Algorithms

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Identify the main concepts of greedy algorithms and dynamic programming.
Solve problems from online resources or textbooks.
Analyze the solutions and identify patterns.

Explain a greedy algorithm or dynamic programming technique

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Deepen understanding of a greedy algorithm or dynamic programming technique by explaining it to others.

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Choose a specific greedy algorithm or dynamic programming technique.
Research and understand the algorithm thoroughly.
Create a presentation, video, or written explanation.
Share your explanation with others and seek feedback.

Develop a mobile app to solve scheduling problems

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Apply greedy algorithms to a practical problem by developing a mobile app for solving scheduling problems.

Browse courses on Greedy Algorithms

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Identify specific scheduling problems to target.
Design and implement a greedy algorithm for solving the problems.
Develop a mobile app that incorporates the greedy algorithm.
Test and refine the app based on user feedback.

Career center

Learners who complete Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming will develop knowledge and skills that may be useful to these careers:

Operations Research Analyst

An Operations Research Analyst uses mathematical models and algorithms to improve the efficiency of business processes. The course's focus on greedy algorithms and dynamic programming can help an Operations Research Analyst develop the skills needed to solve complex optimization problems.

See salaries and explore the career path for Operations Research Analyst

Data Scientist

A Data Scientist uses data to solve business problems. The course's focus on greedy algorithms and dynamic programming can help a Data Scientist develop the skills needed to analyze data and develop predictive models.

See salaries and explore the career path for Data Scientist

Software Engineer

A Software Engineer designs, develops, and maintains software applications. The course's focus on greedy algorithms and dynamic programming can help a Software Engineer develop the skills needed to design and implement efficient software.

See salaries and explore the career path for Software Engineer

Computer Scientist

A Computer Scientist designs, develops, and implements computer software and systems. The course's focus on greedy algorithms and dynamic programming can help a Computer Scientist develop the skills needed to design and implement efficient algorithms.

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Actuary

An Actuary uses mathematics to assess risk and uncertainty. The course's focus on greedy algorithms and dynamic programming can help an Actuary develop the skills needed to develop and price insurance products.

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Statistician

A Statistician collects, analyzes, and interprets data. The course's focus on greedy algorithms and dynamic programming can help a Statistician develop the skills needed to design and conduct statistical studies.

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Financial Analyst

A Financial Analyst provides financial advice to individuals and organizations. The course's focus on greedy algorithms and dynamic programming can help a Financial Analyst develop the skills needed to make sound investment decisions.

See salaries and explore the career path for Financial Analyst

Management Consultant

A Management Consultant helps organizations improve their performance. The course's focus on greedy algorithms and dynamic programming can help a Management Consultant develop the skills needed to analyze business problems and develop solutions.

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Systems Analyst

A Systems Analyst designs and implements computer systems. The course's focus on greedy algorithms and dynamic programming can help a Systems Analyst develop the skills needed to design and implement efficient systems.

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Project Manager

A Project Manager plans and executes projects. The course's focus on greedy algorithms and dynamic programming can help a Project Manager develop the skills needed to manage projects efficiently.

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Business Analyst

A Business Analyst analyzes business processes and develops solutions to improve efficiency. The course's focus on greedy algorithms and dynamic programming can help a Business Analyst develop the skills needed to identify and solve business problems.

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Database Administrator

A Database Administrator manages and maintains databases. The course's focus on greedy algorithms and dynamic programming can help a Database Administrator develop the skills needed to optimize database performance.

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Network Administrator

A Network Administrator manages and maintains computer networks. The course's focus on greedy algorithms and dynamic programming can help a Network Administrator develop the skills needed to optimize network performance.

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Information Security Analyst

An Information Security Analyst protects computer systems and networks from unauthorized access. The course's focus on greedy algorithms and dynamic programming can help an Information Security Analyst develop the skills needed to design and implement security measures.

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Operations Manager

An Operations Manager plans and directs the operations of an organization. The course's focus on greedy algorithms and dynamic programming can help an Operations Manager develop the skills needed to optimize business processes.

See salaries and explore the career path for Operations Manager

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming.

Introduction to Algorithms, fourth edition

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This classic textbook covers greedy algorithms, minimum spanning trees, and dynamic programming in great detail. It valuable reference for anyone interested in learning more about these topics.

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Advanced algorithms course

Activities

Career center

Reading list

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