About this Course
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Advanced Level

Approx. 48 hours to complete

Suggested: 6-10 hours/week...

English

Subtitles: English, Korean

Skills you will gain

Data AnalysisFeature ExtractionFeature EngineeringXgboost

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Advanced Level

Approx. 48 hours to complete

Suggested: 6-10 hours/week...

English

Subtitles: English, Korean

Syllabus - What you will learn from this course

Week
1
6 hours to complete

Introduction & Recap

8 videos (Total 46 min), 7 readings, 6 quizzes
8 videos
Meet your lecturers2m
Course overview7m
Competition Mechanics6m
Kaggle Overview [screencast]7m
Real World Application vs Competitions5m
Recap of main ML algorithms9m
Software/Hardware Requirements5m
7 readings
Welcome!10m
Week 1 overview10m
Disclaimer10m
Explanation for quiz questions10m
Additional Materials and Links10m
Explanation for quiz questions10m
Additional Material and Links10m
5 practice exercises
Practice Quiz8m
Recap8m
Recap12m
Software/Hardware6m
Graded Soft/Hard Quiz8m
2 hours to complete

Feature Preprocessing and Generation with Respect to Models

7 videos (Total 73 min), 4 readings, 4 quizzes
7 videos
Numeric features13m
Categorical and ordinal features10m
Datetime and coordinates8m
Handling missing values10m
Bag of words10m
Word2vec, CNN13m
4 readings
Explanation for quiz questions10m
Additional Material and Links10m
Explanation for quiz questions10m
Additional Material and Links10m
4 practice exercises
Feature preprocessing and generation with respect to models8m
Feature preprocessing and generation with respect to models8m
Feature extraction from text and images8m
Feature extraction from text and images8m
1 hour to complete

Final Project Description

1 video (Total 4 min), 2 readings
2 readings
Final project10m
Final project advice #110m
Week
2
2 hours to complete

Exploratory Data Analysis

8 videos (Total 80 min), 2 readings, 1 quiz
8 videos
Building intuition about the data6m
Exploring anonymized data15m
Visualizations11m
Dataset cleaning and other things to check7m
Springleaf competition EDA I8m
Springleaf competition EDA II16m
Numerai competition EDA6m
2 readings
Week 2 overview10m
Additional material and links10m
1 practice exercise
Exploratory data analysis12m
2 hours to complete

Validation

4 videos (Total 51 min), 3 readings, 2 quizzes
4 videos
Validation strategies7m
Data splitting strategies14m
Problems occurring during validation20m
3 readings
Validation strategies10m
Comments on quiz10m
Additional material and links10m
2 practice exercises
Validation8m
Validation8m
5 hours to complete

Data Leakages

3 videos (Total 26 min), 3 readings, 3 quizzes
3 videos
Leaderboard probing and examples of rare data leaks9m
Expedia challenge9m
3 readings
Comments on quiz10m
Additional material and links10m
Final project advice #210m
1 practice exercise
Data leakages8m
Week
3
3 hours to complete

Metrics Optimization

8 videos (Total 83 min), 3 readings, 2 quizzes
8 videos
Regression metrics review I14m
Regression metrics review II8m
Classification metrics review20m
General approaches for metrics optimization6m
Regression metrics optimization10m
Classification metrics optimization I7m
Classification metrics optimization II6m
3 readings
Week 3 overview10m
Comments on quiz10m
Additional material and links10m
2 practice exercises
Metrics12m
Metrics12m
4 hours to complete

Advanced Feature Engineering I

3 videos (Total 27 min), 2 readings, 2 quizzes
3 videos
Regularization7m
Extensions and generalizations10m
2 readings
Comments on quiz10m
Final project advice #310m
1 practice exercise
Mean encodings8m
Week
4
3 hours to complete

Hyperparameter Optimization

6 videos (Total 86 min), 4 readings, 2 quizzes
6 videos
Hyperparameter tuning II12m
Hyperparameter tuning III13m
Practical guide16m
KazAnova's competition pipeline, part 118m
KazAnova's competition pipeline, part 217m
4 readings
Week 4 overview10m
Comments on quiz10m
Additional material and links10m
Additional materials and links10m
2 practice exercises
Practice quiz6m
Graded quiz8m
4 hours to complete

Advanced feature engineering II

4 videos (Total 22 min), 2 readings, 2 quizzes
4 videos
Matrix factorizations6m
Feature Interactions5m
t-SNE5m
2 readings
Comments on quiz10m
Additional Materials and Links10m
1 practice exercise
Graded Advanced Features II Quiz12m
10 hours to complete

Ensembling

8 videos (Total 92 min), 4 readings, 4 quizzes
8 videos
Bagging9m
Boosting16m
Stacking16m
StackNet14m
Ensembling Tips and Tricks14m
CatBoost 17m
CatBoost 27m
4 readings
Validation schemes for 2-nd level models10m
Comments on quiz10m
Additional materials and links10m
Final project advice #410m
2 practice exercises
Ensembling8m
Ensembling12m
4.7
153 ReviewsChevron Right

14%

started a new career after completing these courses

22%

got a tangible career benefit from this course

20%

got a pay increase or promotion

Top reviews from How to Win a Data Science Competition: Learn from Top Kagglers

By MSMar 29th 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!

By MMNov 10th 2017

This course is fantastic. It's chock full of practical information that is presented clearly and concisely. I would like to thank the team for sharing their knowledge so generously.

Instructors

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Dmitry Ulyanov

Visiting lecturer
HSE Faculty of Computer Science
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Alexander Guschin

Visiting lecturer at HSE, Lecturer at MIPT
HSE Faculty of Computer Science
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Mikhail Trofimov

Visiting lecturer
HSE Faculty of Computer Science
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Dmitry Altukhov

Visiting lecturer
HSE Faculty of Computer Science
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Marios Michailidis

Research Data Scientist
H2O.ai

About National Research University Higher School of Economics

National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more. Learn more on www.hse.ru...

About the Advanced Machine Learning Specialization

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings....
Advanced Machine Learning

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.