Zurück zu Advanced Algorithms and Complexity

4.6

Sterne

440 Bewertungen

•

89 Bewertungen

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. We will start with networks 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. We then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements and many others. Next we 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. We 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 datasets without being able even to store a dataset....

Jan 04, 2018

As usual, complex arguments explained in simple terms!\n\nSome problems are really tough! (e.g. there's a problem from Google Code Jam).\n\nThank you for this course!

Aug 26, 2019

Very Very Challenging Course , it test your patience and rewards is extremely satisfying. Lot of learning on a complicated subject of NP-Hard problems.

Filtern nach:

von To P H

•Sep 27, 2018

Very bad course content for some modules

Many abstract concepts and mathematical terms but with severe lack of explanation of the terms and lack of specific, concrete examples to help learners to understand them

For example: in LP module there should be example of how the primal and dual matrix looks. How simplex algorithm is used on a specific example (showing explicit graph). I undertood only 25% of what was discussed about in this module

No motivation to move on after week 2!

Other weeks are slightly better

In summary: Too many abstract concepts with little examples

von Nikhil

•Jan 04, 2017

Loved what I learnt, I also implemented a project using Google MAP API for the organization I'm working at

von Omar M A M

•Apr 15, 2017

Thank you very much for this awesome course, I really enjoyed and learned alot from it.

I really liked the selected topics, they act like an intro to some really interesting fields in the programming.

I've learned about NP multiple times but never found a use to it until now, the problems were really good and informative.

I think the linear programming was pretty rushed, it should've been expanded over two weeks with more in details.

Maybe add a problem or explain the use of duality .

von Eugenio G M

•Jan 04, 2018

As usual, complex arguments explained in simple terms!

Some problems are really tough! (e.g. there's a problem from Google Code Jam).

Thank you for this course!

von Chitrang S

•Aug 26, 2019

Very Very Challenging Course , it test your patience and rewards is extremely satisfying. Lot of learning on a complicated subject of NP-Hard problems.

von Yinchung C

•May 15, 2019

This is a very challenging course in the specialization. I learned a lot form going through the programming assignments!

von Syed H A

•Feb 12, 2020

Really rigorous and fundamental with what scientist and other professionals need to know about programming.

von Surbhi M

•Dec 14, 2019

This course is wonderful.I am really feel like I have all knowledge of adsa

von Addis R S

•Sep 26, 2016

Thank you very much. I learned a lot in this course. I recommend it!

von Anton R

•Mar 02, 2019

Liked this course, at least there are courses for advanced level.

von Priyansh B

•May 31, 2019

Was fun learning advanced stuff and implementing algorithms.

von Tamilarasu S

•Apr 10, 2018

Very well made course with challenging algorithm problems.

von Pablo E M M

•May 20, 2018

Great Courses!. Thanks for this wonderful specialization!

von Joseph G N

•Sep 02, 2018

An incredible course,the exercises were very interesting

von Ahmad B E

•Jan 10, 2018

This is how algorithms should be taught.

von Fernando K I

•Jan 01, 2020

Shout-out to professor Alexander Kulikov that is the only one in the whole specialization who has good didactics skills. He knows how to explain a concept by giving examples and walking through them step by step so the viewer can understand the thought process. Unfortunately, professor Kane's lectures were poorly taught. I understand that his videos are older and maybe the technology wasn't there yet when he recorded the lectures. You'd better off skipping those lectures and going through the assignments directly, learning the material elsewhere.

von Yue S

•Oct 22, 2019

I really dislike Daniel Kane's teaching style!!! His slides are rough and lack of details, the structure of his lectures is loose. Every time I met a Unit taught by Kane, I have to spend much more time on videos and assignments than other Units. This makes me very annoyed -- why can't this teacher be more serious on teaching just like other teachers in this course??? :-(

von Madhusudan H J

•Oct 14, 2018

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.

von Kota M

•Sep 16, 2016

I enjoyed the course a lot. I cannot thank the instructors enough.

It would have been more interesting if we could go deeper on linear programming, such as extension to integer programming. The discussion about the duality was a bit too fast to me.

von Tamas K

•May 05, 2018

Great course again! The problems are considerably more difficult than in the previous courses in this specialization. The only problem is that the forum interaction with TAs is nonexistent, if you stuck with a problem, you have to solve it alone.

von Wong L L

•Oct 14, 2017

This is a tough course compared to the previous courses in this specialization. The cover of NP-complete problems using two weeks time is especially valuable. The course team has also done a fantastic job in designing the programming assignments.

von Madan K

•Oct 09, 2016

Excellent but tough course ,you need to work and it is not simply called advanced Algorithms and Complexity.

You will be forced to test your code properly ,even if you didn't do it properly in the previous specialisation course.

von Dr K S V

•May 18, 2020

Excellent Course. I learnt new things like integer programming and bioinformatics related applications.

I did my Ph.D in bioinformatics datasets. Stream matching algorithms and apllication oriented wonderful examples

von Dmitrii S

•May 22, 2019

I very enjoyed this course! Theoretic informatics - is my favorite field of study. All the professors are the best. Dreaming to enroll in your Ph.D. program. Thank you very much

von Andrii S

•Jun 15, 2018

Another great course in this specialization with challenging and interesting assignments. However, this one is somewhat harder but rewarding.

- KI für alle
- Vorstellung von TensorFlow
- Neuronale Netzwerke und Deep Learning
- Algorithmen, Teil 1
- Algorithmen, Teil 2
- Maschinelles Lernen
- Maschinelles Lernen mit Python
- Maschinelles Lernen mittels Sas Viya
- R-Programmierung
- Einführung in die Programmierung mit Matlab
- Datenanalyse mit Python
- AWS-Grundlagen: Mit der Cloud vertraut werden
- Grundlagen der Google Cloud-Plattform
- Engineering für Site-Funktionssicherheit
- Englisch im Berufsleben
- Die Wissenschaft des Wohlbefindens
- Lernen lernen
- Finanzmärkte
- Hypothesenüberprüfung im öffentlichen Gesundheitswesen
- Grundlagen für Führungsstärke im Alltag

- Deep Learning
- Python für alle
- Data Science
- Angewandte Datenwissenschaft mit Python
- Geschäftsgründungen
- Architektur mit der Google Cloud-Plattform
- Datenengineering in der Google Cloud-Plattform
- Von Excel bis MySQL
- Erweiterte maschinelles Lernen
- Mathematik für maschinelles Lernen
- Selbstfahrende Autos
- Blockchain-Revolution für das Unternehmen
- Unternehmensanalytik
- Excel-Kenntnisse für Beruf
- Digitales Marketing
- Statistische Analyse mit R im öffentlichen Gesundheitswesen
- Grundlagen der Immunologie
- Anatomie
- Innovationsmanagement und Design Thinking
- Grundlagen positiver Psychologie