mlcourse.ai is one of the largest free machine learning courses run by OpenDataScience, with over 10,000 participants and 3,000 alumni. The course consists of 4 modules covering topics like data analysis, tree-based models, linear models, and other techniques. Each module includes quizzes, assignments applying the concepts, and practice competing in Kaggle competitions to beat baselines.
2. In 4 lines
• One of the largest open & free ML
courses
• Run for ~3 years by ODS.ai team
• >10k participants, ~3k alumni
• Good start for a junior DS position
A podcast about mlcourse.ai
4. Module 1. Data Analysis
The golden rule: in your task, always start
with Exploratory Data Analysis.
Plan:
• 1 assignment
• Dota 2 winner prediction EDA -
Kaggle
5. Module 2. Tree-based models
Random Forest and gradient boosting
are wheelhorses of practical ML
Plan:
• 1 assignment in 2 parts
• 1 quiz
• Beating a baseline in a Kaggle
competition
6. Module 3. Linear models
Linear models are most wide-spread in
whole of ML, econometrics, statistics etc.
Plan:
• 1 quiz
• Beating a baseline in a Kaggle
competition + actually competing
7. Module 4. “The rest”
How to scale to Gbs with simple models (Vowpal
Wabbit), time series, unsupervised learning
Plan:
• 1 quiz (all topics)
• 1 assignment (time series)
• Beating a baseline in a Kaggle competition
with ~10 Gb of data
8. Roadmap
What you can follow:
• #mlcourse_ai_news
• mlcourse.ai/roadmap
• Google calendar