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Data Analytics Remote Part Time

Boost your career by learning Data Analytics

Overview

Curious about the field of Data Analytics?

In just 12 weeks we will address the fundamentals of data analysis alongside with the key steps in transforming data into answers. You will have a solid foundation and knowledge of how to manage data and effectively get the most out of it. You will learn about programming, data mining, data analysis, and the powerful visualization of data to create a human-centric Data solution as your personal project.

Course Computer Icon

144 hours course

Course Calendar

12 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

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.

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

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 professional career and want to acquire the skills to level up by adding Data understanding and Data design to their resume in a more efficient way.

Suitable for: Any woman with a professional profile that deals with data, such as: business, marketing, logistics…If you manage data, this course is an ideal way to complement your work by adding a tech layer to your current job to become more efficient and robust.

Skill Building

Hard Skills you will develop:

Soft Skills you will develop:

Creativity

Skepticism

05 Teamwork

Collaboration

04 Public Speaking

Public Speaking

Course Structure

Learn Data Analytics in record time

Pre-work - 10 hours:

Python
basics

Python
data types

Basic data visualization
with Python

Course Structure - 144 hours:

Units 1 – 3Programming with Python I, Exploratory Data Analysis
Units 4 – 6Programming with Python II
Unit 7SQL. Concepts, hands-on practise.
Units 8 – 9Unsupervised Machine Learning algorithms
Units 10 – 12Build your final personal project

Download the syllabus for a comprehensive overview of our curriculum.

Lead Instructor

Learn from female industry experts

Idoia Martí Aluja
Lead Instructor
Data Scientist and Machine Learning Expert

Each course has 3 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 Data Analytics, concluding in a project presentation of the learnings at the end of the course.

This is what a typical week looks like:

Tue & Thu 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 9am to 3pm

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

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 Data Analytics with us!

Sep 20 - Dec 11 (2021)

Tuesday & Thursday from 6:30pm to 9:30pm
Saturdays from 9am to 3pm CET

Jan 18 - Apr 9 (2022)

Tuesday & Thursday from 6:30pm to 9:30pm
Saturdays from 9am to 3pm CET

May - July (2022)

Tuesday & Thursday from 6:30pm to 9:30pm
Saturdays from 9am to 3pm CET

Tuition & Financing

We care about your finances!

We carefully revise your profile to provide you with the most suitable financing plan for your current situation.

Book a call with our Admissions Team to find yours!

Full Tuition

3.475€

One-time Payment

3.225€

* Save 250€ when paid in full

Early Registration

2.975€

* Save 500€ when paid in full

Pay in installments

We have several options. Find yours.

Employer
Sponsorship

Your company can fund your studies. Let us help you.

Referral
Program

Bring a friend and both of you will get a 100€ disccount.

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 - Complete 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!