Train in Data Reviews 

The course is well structured, explanations are clear, and the short, engaging videos enhance the learning experience.

Great explanations and excellent material.

The instructor, Soledad, is very experienced, knowledgeable and very good at explaining theory and also the practical implementation in python.

This is a rare combination of talents!

I have just completed 20% of the Course but still I am learning the nuances and a step-step by approach and each approach's assumptions, advantages, dis-advantages and applications. Great respect to the Guru Soledad Galli for a refined, structured and easy-to-comprehend course

Fantastic course. Knowledgeable instructors with detailed deep dives into new concepts. Thorough coverage of practical aspects and hands on coding examples that can be used in production. Great tests and quizzes to validate progress.

Strongly recommended.
The "Feature engineering for time series forecasting" course provided various worked-out examples in the form of code notebooks that went beyond the basic explanations commonly seen elsewhere. These examples helped me in my project work by providing me with a good, functional starting point from which I could progress with my forecasting tasks.

Thorough yet gentle introduction to important aspects of time-series feature engineering.

Excellent and practical book. Easy to read and very interesting

I really enjoyed the course Feature Engineering for Time Series.
It combines theoretical knowledge with practical implementation using different libraries.

I love feature-engine and its versatility for a number of daily needs.Thanks Sole and Train in Data for getting me to know your library and for developing such great courses and material.I was not able to find such a juice of theory and practice as in your courses. Waiting for the next one :)

I have gone through the courses for feature engineering and selection and they have been a great overview of techniques that they can be used for modeling. The presentation is clear and concise.

I'm a data scientist and have taken the following courses on Udemy from Train in Data [lecturer: Soledad Galli]:
- Feature Selection for Machine Learning
- Machine Learning with Imbalanced Data
- Feature Engineering for Machine Learning

Following an explanation of Why this data preprocessing operation was needed, there is a demonstration of How to do it in Python. Every video has it's documented Python notebook. In addition to the operation itself the code includes EDA/visualization of the data before and after and sometimes even a snippet of ML to show how the data preparation affected the result. I'm retaking the course on Feature Engineering since it has now almost doubled in size. Especially nice are the Python "one liners" which show how to do complex computation on a Pandas data frame elegantly and concisely.

The quality and depth of the lecture materials are unparalleled. The dedication and meticulous effort put into crafting these state-of-the-art resources is evident. My commendations for such an exemplary job.

Great course! A good and correct mix of theory and practice. I believe very complete course on feature engineering for time series. The course materials are also very useful and helpful.

Insightful and relevant content about Machine Learning..

This Data Bites email tips is very useful for begineers like me in Data Science field.

Things like Feature Engineering and Selection.

The most important part of a data science or machine learning project is feature engineering. So I have learnt lot of things from here. It's an amazing experience for me. I hope more things I will explore from here in future.

Trainindata is a leading platform to learn about data science. Soledad will help students to excel. I have no hesitation to recommend trainindata to aspiring data scientists as they will get bang for buck.

The topics are presented in a clear and concise manner, with each section providing helpful examples to illustrate the concepts and help you apply what you are learning.