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 modelling 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 modelling. Learning data analysis, machine learning tasks and pipelines. Create a human-centric Data solution as your personal project.
Remote Learning makes more sense than ever as tech companies are global and very often teams are delocalized in order to have access to the best talent. Learning remotely is a very valuable experience and good practice for the new remote status quo.
We will use a mix of agile methodologies and remote tools. Download the syllabus to learn about our whole approach.
Join us on campus if you want to, whenever you want to! Enjoy our Flexible Learning Environment, online or with us in sunny Barcelona.
This course is suitable for you if you are a:
Career Booster: Women who are established in their STEM professional career and want to jump to the next level by adding Data understanding and Machine Learning to their resume.
PhD STEM Profiles: Women who work or have worked in academia and wish to jump to the corporate sector as well as acquiring the most updated technical skills.
Recent STEM Graduates: Women who have studied STEM disciplines and want to take a deep dive into the world of data science.
Suitable for: any women with a professional profile that deals with STEM. This will be an ideal complement for your work if you manage data and you want to add a data science layer to your current job.
Pre-work. 10 hours of work preparation
Remote Learning Course – 100 hours
Unit 1 – Python for Data Science
Unit 2 – Story telling with Data : exploratory data analysis, data mining , feature engineering.
Unit 3 – ML supervised methods – Regression + Project
Unit 4 – ML supervised methods – Classification + Project
Unit 5 – Pipelines in Machine Learning + Project
Unit 6 – Career Assessment + Final Presentation (Demo Day)
Our students develop a project during the course, as a part of their portfolio. Please, download the syllabus for full understanding of the course content.
Our mission is to bring more women into the tech field, that’s why we are committed to the careers of our graduates.
During the course, you will attend a workshop dedicated to career opportunities within the Data field and, at the end, you will have an individual mentorship session with our Data oriented career expert.
You will also present your final project at a Demo Day and will have access to the Hiring Day of our longer courses organized every quarter.
See Career Development plan in our specific web section.
Idioia Martí i Aluja
Machine Learning Expert
Each course has 3 different 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, Everis, Adevinta, etc.
70% practical. 30% theory. Each unit covers a different aspect of Product Management, concluding in a project presentation of the learnings at the end of the course.
This is what a typical week looks like:
Monday & Wednesday – 18:30 – 21:30 CET
Saturday : 10:00 – 14:00 CET
Here are the steps for completing our admissions process:
Dates & Schedule
Tuition Fee and Payment Conditions