Machine Learning Part Time

Taking advantage of Machine Learning algorithm

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. 

Looking to boost your career in one of the most promising branches of tech?

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.

Technical and Soft Skills of a Machine Learning savvy that you will develop in this course

Technical Skills:

• Program in Python from a Data Scientist point of view
• Usage of the scientific method applied to Machine learning
• The key steps in transforming data into answers
• Hands-on Machine Learning
• Think critically about data and draw conclusions based on your analysis

Soft Skills:

• Leadership and Professional development
• Teamwork and collaboration
• Public Speaking and Oral Communication
• Time Management
• Skepticism Creativity

Learn the fundamentals of Machine Learning

Pre-work. 10 hours of work preparation

• pandas basics,
• data analysis and visualization,
• descriptive statistics

Remote Learning Course – 100 hours

Unit 1 – Python for Data Science
Unit 2 – Storytelling 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. 

Download the course syllabus for full understanding of the curriculum. 

Develop your career in Europe’s leading academy for women in tech  

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. 

• Hiring & Demo Day
• Career Assessment – In group and individual. 
• Networking Opportunities

See Career Development plan in our specific web section.

Learn from female industry experts

Idioia Martí i Aluja
Lead instructor
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.

We are all about learning by doing

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 – Thursday : 18:30 – 21:30 

• 18.30 – 19.00 Refresh of the concepts from the previous class
• 19.00 – 20.00 Lecture 
• 20.00 – 20.15 Break
• 20:15 – 21:30 Hands-on practice! Your turn

Saturday : 10:00 – 14:00

• 10.00 – 10.30 Stand-up meeting
• 10.30 – 14.00 Project Work + Individual Mentoring

Take the next step

Here are the steps for completing our admissions process: 

1. Submit the application form.
2. You will receive an email from us to book a call with our admissions manager. 
3. Attend a personal interview with us. 
4. Pay the tuition fee and sign the contract. Financial options are available, ask us for more information.
5. Access the pre-work and prepare yourself for the course. Submit it before the starting date of class. 
6. If you are still not sure, come to one of our on campus or online informative sessions. You can access the calendar here. 

We are all ears, let us know about your needs.

Dates & Schedule

• Monday & Wednesday from 18.30 to 21.30
• Saturday from 10.00 to 14.00

Tuition Fee and Payment Conditions

• Full price: 2950€ (VAT included) – Pay in 3 installments
• Payment upfront: 2450€ (VAT included)
• Early Inscription: 2250€ (VAT included)

Financial options