Interactive Course

Winning a Kaggle Competition in Python

Learn how to approach and win competitions on Kaggle.

  • 4 hours
  • 16 Videos
  • 52 Exercises
  • 1,717 Participants
  • 4,200 XP

Loved by learners at thousands of top companies:

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Course Description

Kaggle is the most famous platform for Data Science competitions. Taking part in such competitions allows you to work with real-world datasets, explore various machine learning problems, compete with other participants and, finally, get invaluable hands-on experience. In this course, you will learn how to approach and structure any Data Science competition. You will be able to select the correct local validation scheme and to avoid overfitting. Moreover, you will master advanced feature engineering together with model ensembling approaches. All these techniques will be practiced on Kaggle competitions datasets.

  1. 1

    Kaggle competitions process

    Free

    In this first chapter, you will get exposure to the Kaggle competition process. You will train a model and prepare a csv file ready for submission. You will learn the difference between Public and Private test splits, and how to prevent overfitting.

  2. Dive into the Competition

    Now that you know the basics of Kaggle competitions, you will learn how to study the specific problem at hand. You will practice EDA and get to establish correct local validation strategies. You will also learn about data leakage.

  3. Feature Engineering

    You will now get exposure to different types of features. You will modify existing features and create new ones. Also, you will treat the missing data accordingly.

  4. Modeling

    Time to bring everything together and build some models! In this last chapter, you will build a base model before tuning some hyperparameters and improving your results with ensembles. You will then get some final tips and tricks to help you compete more efficiently.

What do other learners have to say?

Devon

“I've used other sites, but DataCamp's been the one that I've stuck with.”

Devon Edwards Joseph

Lloyd's Banking Group

Louis

“DataCamp is the top resource I recommend for learning data science.”

Louis Maiden

Harvard Business School

Ronbowers

“DataCamp is by far my favorite website to learn from.”

Ronald Bowers

Decision Science Analytics @ USAA

Yauhen Babakhin
Yauhen Babakhin

Kaggle Grandmaster

Yauhen holds a Master’s Degree in Applied Data Analysis and has over 5 years of working experience in Data Science. He worked in Banking, Gaming and eCommerce domains. Yauhen is also the first Kaggle competitions Grandmaster in Belarus having gold medals in both classic Machine Learning and Deep Learning competitions.

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