Retour à Divide and Conquer, Sorting and Searching, and Randomized Algorithms

4.8

étoiles

3,544 évaluations

•

639 avis

The primary topics 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), and randomized algorithms (QuickSort, contraction algorithm for min cuts)....

Sep 14, 2018

Well researched. Topics covered well, with walkthrough for exam.le cases for each new introduced algorithm. Great experience, learned a lot of important algorithms and algorithmic thinking practices.

Mar 16, 2017

Very good course in algorithms. I bought the book to help me understand but the lectures make it way easier and thus much more fun to understand the analysis. Looking forward to complete the spec

Filtrer par :

par Feiyu L

•Apr 23, 2018

Now I truly understand how to think of algorithm in terms with Recursion applying Divide and Conquer, and how to use Master method to prove an algorithm's complexity. Even though it is more rigorous then what is required for a software interview or engineering project, having the exposure of theory is better than not having it.

par Aditya k

•Jun 19, 2018

This is an amazing course focusing on some of the important fundamentals required to design the right algorithm to a problem statement. Prof. Tim Roughgarden does a fantastic job in explaining the concepts and catching the attention of the students, while not making the course boring. Thanks Courseera for hosting this course.

par Sivaramakrishnan

•Mar 25, 2020

I came here from the stanford Lagunita course with the same material. It's an understatement to say that I had quite a FUN time. Wonderfully laid out course structure and sometimes a bit lightweight (rightly so) course material. Highly recommend for people with non-CS background. Great (evergreen) intro course to Algorithms!

par Rui C

•Oct 22, 2017

Really good course on divide and conquer algorithm design approaches. It's a good introduction to the subject of algorithms. The book written from the course and on sale on amazon is a really good support to the videos. It is a clean up transcript with further additions to the material covered and it's well worth the buying.

par Sangeet M D

•May 31, 2017

I always had my doubt on whether to choose which course on Algorithm in coursera, The Princeton one or the Stanford one. Though I can weight one above the other, but the flow is which the Stanford one proceed is the best for any lower Intermediate level student to wants to learn the upper fundamentals of Algorithm Analysis.

par Dustin Z

•Sep 23, 2019

A very good course. More challenging than the machine learning courses I have taken because there is more math and the programming assignments are less directed, but that was a plus as I grew more in my critical thinking and programming skills because I needed to solve the problems on my own. Very happy with this course.

par Hagen T

•Feb 22, 2018

This is an excellent course on algorithms, that has given me a deeper understanding of the subject.

I am a theoretical physicist using this course as preparation for coding interviews, and the speed, amount of rigor and optional material (the optional theory problems in particular) feel perfect for my learning effort.

par Md. F K

•Sep 27, 2019

At first, the course may look too fast-paced, but after one or two videos, ample explanations would disabuse oneself of that idea. Highly resourceful lectures, challenging quizzes, and optional problems make this course quite an elegant one. One of my favorite courses. Looking forward to completing the specialization.

par Zhao J

•Dec 28, 2017

It's just great! The professor is humorous and fantastic! I really love this course, and it had helped me get started in algorithms and data structures. After finishing this course, I have read some part (part I to part IV) of the CLRS book and learned even more! Believe me, this is a good course and worth your time.

par Limber

•Oct 31, 2017

A really helpful course that help me to dive deep into the algorithms world. The prof is really nice. I thought the book he has wrote is really benefit for my study. I have over 5 years coding experience but it is still hard for me to get that. Some algorithms assignments are really interesting. It's time worthy.

par Masashi M

•Nov 15, 2016

I was very amazed with his really good lectures. Especially proving each algorithm's correctness and performance was very interesting and stimulated my curiosity. I also need to note that optional videos for probability helped me a lot to understand this course. I would like to recommend my friends definitely.

par Damian C

•Feb 02, 2018

Amazing course, just loved it. First there's the ingenuity of the topics covered. Second, Tim makes an awesome job in delivering those lectures. Very clear, and straight to the point. Aside from learning, I enjoyed this a lot. Many thanks to Coursera and its team for making this available, keep the good work :)!

par Li-Pu C

•Mar 24, 2020

the professor talks about the algorithm of the introduction to the algorithm and overall it is very good because it is very uncommon that people can deliver hard knowledge in a easy way. I would recommend all the foreigners to take this course as their first course on Coursera if you're new to computer science.

par Kaan A

•Sep 07, 2019

It was great course from Tim Roughgarden. I like his style and explanations. I enjoyed while doing programming assignments and quizzes and final exams. They were designed well. Difficulty is just right for an online course I guess, not more than courses in universities but more than most of the online courses.

par Paras J

•Apr 04, 2020

The best content and teaching methodology one can find for algorithms. Even the topics that are considered tough were explained in a very smooth and succinct manner. I loved the optional reading material and assignments! Some of the problems were really challenging and fun to solve. Highly recommended!

par Edgar R H P

•Nov 26, 2018

El curso es realmente agradable y permite obtener conocimientos para la optimización de algoritmos, altamente recomendado para aquellos que ya tienen una base ya formada. Parecería apropiado adaptar un curso similar para profesionales capacitados en otras carreras pero con interés en los algoritmos.

par Sonali P

•Aug 10, 2018

An awesome course for learning algorithms in Divide and Conquer Strategy. The lecturer's teaching and lecture content both are world class. The assignments too were worth challenging and confidence boasting. Nice one in case someone needs to grasp at deeper level, the algorithm design and analysis.

par Anton K

•Feb 11, 2018

This is by far the best course I've ever seen on coursera. I actually had a major in discrete mathematics and algorithms at college, so I had though I only needed to refresh. But I was actually able to learn quite a lot new things and realized that some of the concepts I've had wrong all this time!

par Neelabh S

•Apr 02, 2020

Great course! Programming assignments are designed very well. Evaluative components properly judge the learning outcome of the course.

As far as the course is concerned, the explanation of concepts is great. Every topic starts from fundamentals which makes it easy to connect and understand.

par An N

•Feb 26, 2018

It can be difficult for beginners. But you definitely learn alot after if you can make it through the end. There are typed pdf lectures included, but recommend to take notes and have the pdf up when watching the lectures because the instructor's handwriting is not very easy to read.

par Seanita T

•Sep 17, 2019

The ML class was a great prep for this one. I like that this class is taught in Python vs Matlab/Octave. Prof. Ng is excellent as always. Each course solidifies my understanding while also reminding me there is much still to learn. It's challenging but I am thoroughly enjoying it.

par Ke " L

•Jun 09, 2019

I have learned a lot about important concepts about algorithms through this course, to name a few, divide and conquer (recursion), randomized algorithms, and introduction to graph. It took me about 15-20 hours a week to learn the knowledge thoroughly and converted them into codes.

par Libor S

•Apr 24, 2017

Course is brilliant, but at least for me the completion took in average 3 times more effort than expected by authors (4-8 hrs/week). Of course this is mostly due to my low experience with programming, but still, might be relevant for other learners, who don!t have much experience.

par Andy

•Jul 23, 2017

An excellent course for beginners looking to grasp fundamental concepts of algorithms!! Professor Roughgarden was brilliantly lucid in his explanations and the assignments and evaluations were helpful in assimilating the concepts covered. It was pleasure to take this course.

par Rohit S

•Apr 17, 2019

He is the perfect and awesome Guru, who understands how to connect the dots. I found the right place to understand this subject in the right direction and interpretation. It's truth unfolded. Thanks a lot Sir for mentoring and 'illuminating' students around the corner.

- L'IA pour tous
- Introduction à TensorFlow
- Réseau de neurones et deep learning
- Algorithmes, Partie 1
- Algorithmes, Partie 2
- Apprentissage automatique
- Apprentissage automatique avec Python
- Apprentissage automatique à l'aide de SAS Viya
- La programmation en R
- Intro à la programmation avec Matlab
- Analyse des données avec Python
- Principes de base d'AWS : Going Cloud Native
- Bases de Google Cloud Platform
- Ingénierie de la fiabilité du site
- Parler un anglais professionnel
- La science du bien-être
- Apprendre à apprendre
- Marchés financiers
- Tests d'hypothèses dans la santé publique
- Bases du leadership au quotidien

- Deep Learning
- Le Python pour tous
- Science des données
- Science des données appliquée avec Python
- Bases de la gestion d'entreprise
- Architecture avec Google Cloud Platform
- Ingénierie des données sur Google Cloud Platform
- Excel à MySQL
- Apprentissage automatique avancé
- Mathématiques pour l'apprentissage automatique
- Voiture autonome
- Révolutions Blockchains pour l'entreprise
- Business Analytics
- Compétences Excel pour l'entreprise
- Marketing numérique
- Analyse statistique avec R pour la santé publique
- Bases de l'immunologie
- Anatomie
- Gestion de l'innovation et du design thinking
- Bases de la psychologie positive