AllWomen

AllWomen Logo Small
AllWomen Logo horizontal

Next class starts Jan 18 2021Apply Now

Machine Learning Part Time

Learn how to understand data through the means of predictive modeling.

Download Syllabus
Apply Now
Download Syllabus

Overview

Curious about the field of Machine Learning?

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. By learning data analysis, machine learning tasks, and pipelines, you will acquire the abilities to create a human-centric Data solution as your personal project.

Course Computer Icon

100 hours course

Course Calendar

10 weeks part-time

Course Books

100% hands-on experience

Course Pencil

Flexible Learning Environment

Course Graphics

Career Development

Course Hands

Women-only environment

Course Computer Icon

100 hours course

Course Calendar

10 weeks part-time

Course Books

100% hands-on experience

Course Pencil

Flexible Learning Environment

Course Graphics

Career Development

Course Hands

Women-only environment

Flexible Learning Environment

We offer a Flexible Learning Environment

Our Flexible Learning Environment is adaptable to your best way of working, giving you the opportunity to choose to be on campus or learn remotely based on your schedule and location.

Remote Learning makes more sense than ever with the number of global tech companies that very often work with delocalized teams in order to access the best talent. Learning remotely is a very valuable experience and good practice for the new remote status quo, which is why we give you the option to study with us this way.

We use a mix of agile methodologies and remote tools. Download the syllabus to learn more about our approach.

Who is this for

Looking to shift or boost your career?

This course is suitable for you if you are a:

Career Booster: Women who are established in their STEM professional career and want to take it 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 by 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 woman with a professional profile that deals with STEM. This will complement your work if you already manage data and you want to level up your current job with data science knowledge.

Skill Building

Hard Skills you will develop:

  • Program in Python from a Data Scientist’s 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 drawing conclusions based on your analysis

Soft Skills you will develop:

Creativity

Skepticism

05 Teamwork

Collaboration

04 Public Speaking

Public Speaking

Course Structure

Learn Machine Learning in record time

Pre-work - 10 hours:

Pandas
Basics

Data Analysis
and Visualization

Descriptive
Statistics

Course Structure - 100 hours:

Units 1 & 2Python for Data Science & Storytelling with Data
Unit 3ML supervised methods – Regression
Unit 4ML supervised methods – Classification 
Unit 5ML supervised methods – Unsupervised
Unit 6Build your own final and personal project

Download the syllabus for a comprehensive overview of our curriculum.

Lead Instructor

Learn from female industry experts

0 (14)

Idoia Martí Aluja
Lead Instructor
Data Scientist and Machine Learning Expert

Each course has 5 different instructors on average. They all have senior experience in different industry sectors and work at companies like Typeform, Everis, & Adevinta, among others. Our goal is that you benefit from their diverse experience.

A Typical Week

We’re about learning by doing

70% practical. 30% theory. Each unit covers a different aspect of Machine Learning, concluding in a project presentation of the learnings at the end of the course.

This is what a typical week looks like:

Tue & Thur from 6:30pm to 9:30pm

6:30pm - 6:45pm

Review previous class concepts

6:45pm - 7:45pm

Lecture

7:45pm - 8pm

Break

8pm - 9:30pm

Hands-on practice! Now, it’s your turn!

Saturdays from 10am to 2pm

10am – 10:30am

Review previous class concepts

10:30am – 11am

Stand-up meeting

11am - 1.30pm

Project Work + Individual Mentoring

1.30pm - 2pm

Weekly Retrospective

Career Development

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

Our goal 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 Science field and, at the end of your journey, you will have an individual mentorship session with our Data Science oriented career expert.

You will also present your final project at a Demo Day and will have access to the Hiring Day organized every quarter.

Demo & Hiring Day

Career Assessment
in a group and individually

Networking
Opportunities

See our Career Development plan here.

Dates & Schedule

Adaptive scheduling to fit your needs

Part-time courses that enable students to balance other responsibilities such as full-time jobs and families alongside class.

Study Machine Learning with us!

Jan 18 - Mar 26 (2021)

Tuesday & Thursday from 6:30pm to 9:30pm
Saturdays from 10am to 2pm CET

Apply

Apr 19 - Jun 25 (2021)

Tuesday & Thursday from 6:30pm to 9:30pm
Saturdays from 10am to 2pm CET

Apply

Sept 20 - Nov 26 (2021)

Tuesday & Thursday from 6:30pm to 9:30pm
Saturdays from 10am to 2pm CET

Apply

Tuition & Financing

Full Tuition

2.950€

*Paid in installments
(see below)

Payment upfront

2.650€

*Paid upfront

Early inscription

-200€

*Paid upfront or in installments

Installment Plans & Sponsorships

Pay the full tuition in
3 installments

984€

per installment

* 0% interest, 0% commission

Pay the full tuition in
10 installments

265€

per installment

* 0% interest, 3.5% commission fee

Employer
Sponsorship

We can help you get financial support from your company with the help of our financial consultant. Ask us for more information!

Admission Process

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 team.

3 - From there, we schedule a personal interview with you so that we can understand your background and expectations.

4 - Do the technical assessment.

5 - We will review your application.

6 - Congratulations! You’ve been accepted! Next comes the student onboarding process.

7 - Pay the tuition fee and enroll. Financial options are available, ask us for more information.

8 - Access the pre-work and prepare yourself for the course. Submit it before the start date of the course.

9 - Welcome to the first day of changing your life and to our campus!