Machine Learning
part time course

Learn the fundamentals of machine learning together with the key steps in transforming data into answers by means of predictive modeling.

Shaping the futures of women in technology ✊

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What our students say

Course Overview

Meet some of our Hiring Partners

“allWomen has had a profound impact in my personal journey, transitioning into Tech. By giving me a vibrant, and exciting space to learn, and by exposing me to terrific women leaders working in AI. The quality of teaching was outstanding and based on hands-on business real-life problems.”

Giovanna Jaramillo

allWomen Data Science graduate
Epistemologist & Data Scientist

Learning & Professional Objectives

For scientific and/or technical backgrounds with a solid understanding of mathematics, statistics, probability and programing. 


in Python from a Data Scientist point of view.


of the scientific method applied to Machine learning.


data into answers (data exploration, preprocessing, data cleaning and feature engineering).

Career Development

We want to provide you with the necessary support 
to boldly scale up
 the industry with confidence.


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08003. Barcelona. SPAIN.


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Machine Learning. 


critically about data and draw conclusions based on your analysis.





data, data analysis, machine learning and the opportunities it offers.

a personal project using the tools and skills that you will be learning during the course;

your results, findings, and next-steps recommendations in front of an audience.

as an individual to accomplish your personal goals, and share your knowledge by working in a team.

Start your application today! 

Shaping the futures of women in technology.

Inés Cordón, Testimonial Data Science Immersive Course

Machine Learning is just the intelligence to find improvement data and automatic learning. In this course, the fundamentals of machine learning together with the key steps in transforming data into answers by means of predictive modeling will be addressed. 

You will also learn how to create machine learning pipelines to continuously improve the efficiency of a machine learning project. 

In just 10 weeks you will have a solid foundation and knowledge of how to manage data and get the most out of it effectively by means of machine learning modeling. Learning data analysis, machine learning tasks and pipelines. Create a human-centric Data solution as your personal project. 

Sept 21st to Nov 25th
100 hours over 10 weeks

Flexible Learning

Monday & Wednesday 
from 18:30 to 21:30

from 10.00 to 14.00

Demo Day & Hiring Day
Career Assessment

Blanca Cros

allWomen Data Science graduate
Digital MKT Specialist & Data Analyst

“I did the Data Science Program with no technical background, it has been a truly challenging, amazing experience. The content, the labs and the community of women in technology that allWomen is creating, is fantastic! I recommend it to all my friend.”

Download SyllabusApply Now

Demo Day & Hiring Day

Individual & Group 

Female Industry Network

Our goal is to help more women either take the leap into the technology sector or continue to develop a meaningful career in this industry.

Our students come to data science
courses from all kinds of different fields


an understanding of the most commonly used tools in the Industry. 

About our instructors

Learn from a team of tech female leaders and create meaningful professional relationships.

Idoia Martí Aluja

Data Science Lead Instructor at allWomen
Data Scientist & Analyst. PhD in Chemometrics


Each course has a team of 5 instructors on average. They all have senior experience in different industry sectors. We want you to benefit from their diverse experience. 

Our instructors work at Typeform, Adevinta and Everis. 

Flexible Learning Environment

Attend the course on-campus or from your home, co-working, 
or even another city with classes streamed online! 


Slack, Hangouts Meet, 
Google Classroom, Miro 
and recorded classes.


Daily Stand Up Meetings, 
Daily Masterclasses, Group Q&A 
Individual Mentorship.


Students, Instructors 
and Hiring Companies.