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Kursteilnehmer-Bewertung und -Feedback für How to Win a Data Science Competition: Learn from Top Kagglers von HSE University

1,081 Bewertungen
262 Bewertungen

Über den Kurs

If you want to break into competitive data science, then this course is for you! Participating in predictive modelling competitions can help you gain practical experience, improve and harness your data modelling skills in various domains such as credit, insurance, marketing, natural language processing, sales’ forecasting and computer vision to name a few. At the same time you get to do it in a competitive context against thousands of participants where each one tries to build the most predictive algorithm. Pushing each other to the limit can result in better performance and smaller prediction errors. Being able to achieve high ranks consistently can help you accelerate your career in data science. In this course, you will learn to analyse and solve competitively such predictive modelling tasks. When you finish this class, you will: - Understand how to solve predictive modelling competitions efficiently and learn which of the skills obtained can be applicable to real-world tasks. - Learn how to preprocess the data and generate new features from various sources such as text and images. - Be taught advanced feature engineering techniques like generating mean-encodings, using aggregated statistical measures or finding nearest neighbors as a means to improve your predictions. - Be able to form reliable cross validation methodologies that help you benchmark your solutions and avoid overfitting or underfitting when tested with unobserved (test) data. - Gain experience of analysing and interpreting the data. You will become aware of inconsistencies, high noise levels, errors and other data-related issues such as leakages and you will learn how to overcome them. - Acquire knowledge of different algorithms and learn how to efficiently tune their hyperparameters and achieve top performance. - Master the art of combining different machine learning models and learn how to ensemble. - Get exposed to past (winning) solutions and codes and learn how to read them. Disclaimer : This is not a machine learning course in the general sense. This course will teach you how to get high-rank solutions against thousands of competitors with focus on practical usage of machine learning methods rather than the theoretical underpinnings behind them. Prerequisites: - Python: work with DataFrames in pandas, plot figures in matplotlib, import and train models from scikit-learn, XGBoost, LightGBM. - Machine Learning: basic understanding of linear models, K-NN, random forest, gradient boosting and neural networks. Do you have technical problems? Write to us:


28. März 2018

Top Kagglers gently introduce one to Data Science Competitions. One will have a great chance to learn various tips and tricks and apply them in practice throughout the course. Highly recommended!

18. Feb. 2019

Really excellent. Very practical advice from top competitors. This specialization is much more information-dense than most machine learning MOOCs. You really get your money's worth.

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226 - 250 von 260 Bewertungen für How to Win a Data Science Competition: Learn from Top Kagglers

von Andreas B

19. Feb. 2019

Really great course learned a lot. The only reason that I did not give 5 stars is that the task in some assignments could be explained somewhat clearer (would have saved me a lot of time) and especially also the scope of the final project. In hintsight after reviewing others, i spend way too much time :P

von Roland B

24. Feb. 2020

Bon cours qui permet d'aller plus loin dans son apprentissage du machine learning.

Je regrette qu'il n'y ait pas plus de travaux pratiques sur différents datasets qui nécessiteraient différentes approches (on travaille essentiellement sur le même dataset avec des techniques de plus en plus évoluées).

von Øystein S

7. Jan. 2018

Some of the stuff is really great! I learned a lot. Thanks. On the other hand, there are some bugs in the codes provided, specially in the additional assignment in week 3. Bugs in the online assignment grader and so on... without the bugs I would have rated this 5 stars.

von Sebastián C L

17. Nov. 2020

It's a very challenging course. You need strong basics of Machine Learning and programming in Python. The topics are very useful to learn how to improve your models. Nevertheless, there is no support in the forums from tutors.

von Matt V

30. Juli 2018

Great course. Very challenging. My only real complaint is about the limitations on the frequency of final project submission (even if the submission is ungraded for any reason) which are a little unreasonable.

von Ronak K

14. Jan. 2020

Very good course for intermediate to the advanced level group. It covers various number of models and practical approach which can be used in Competitions in the Kaggle and also in a real-world problem.

von Γεώργιος Κ

7. Juli 2020

The course has many useful topics but needs updating. There are things not well explained while the final assignment is more of a riddle to find how to pass the exam than making an advanced model.

von Divyang S

22. Okt. 2020

Great course, but assignments need a bit more clarity in instructions. I had a really hard time trying to figure out the last programming assignment in this course.

von alessandro s

4. Feb. 2021

Very good course, this is a advance course.

You must integrate with external documentation but this course give a lot of a good points.


27. Mai 2020

This is a really hard course, but the instructors do a big effort to give you many tips to participate in this kind of competitions

von Carlos M

16. Okt. 2020

The content was very useful but sometimes difficult to understand. It's required a lot of previous experience and a high level

von Param K

23. Juni 2020

This course helped me to understand the right way of applying ML algorithms and to build better pipelines in general.

von 林佳佑

26. Jan. 2019

this course is helpful and important for one who become a data science expert, a lot key skill import in dealing data

von Rony A

12. Juni 2020

Very good course if you want to learn the way to broach a data challenge when you're a beginner.

von 藤田典明

1. Mai 2020

Very Useful Cource. I want to be Kaggle master. and I want to do something useful in the world.

von Gustavo A G G

25. Okt. 2020

Materials are really updated and you find a real value with the trainers. thanks

von Vytenis P

28. Jan. 2019

Course has good tips, but should not be in this specialization

von Benjamin F

2. Feb. 2018

The final project is tough, but it's worth it !

von Daya_Jin

13. Juni 2018


von Mahboob A

16. Apr. 2019

my first was week awesome!

von MHD K M

31. März 2020

amazing lecturers

von Anders P

27. Sep. 2018

Learned a lot

von Santiago P G

14. Sep. 2020

Muy exigente


6. Juni 2020

Good course

von Fabián S Á M

30. Sep. 2020