In 800 hours (5 months), we take beginners with zero experience and turn them into data analysts. There is no pre-course work, which means everyone starts in the same position. This is a full-time, onsite immersive course.
We are proud of our student outcomes, with 98% of our students finding work in their chosen field within 45 days of finishing the program. Check out Switch-Up for independent reviews.
Contact Ubiqum Team
Barcelona Admissions Team
Email Us: firstname.lastname@example.org
Visit Us: Luxa C/Tánger-Badajoz, 08018 Barcelona
Meet Us: Schedule a Video Call
– 8 hours / day, 5 months (800 hours)
- – Develop a portfolio of individual projects
– Max 12 students per class
– Career support
– Designed and maintained by Computer Science experts from Northwestern University and has been taught in the University Carnegie Mellon, USA.
17 September 2018
15 October 2018
12 November 2018
*Cohorts starting every 1-2 months
The full cost of the tuition is 7.900€
- An upfront payment of 2.000 € when you sign up for the course
- A monthly fee of 400 € until the end of the course
- A final payment of 3.900€ is to be made once the student is hired (see Job Hire conditions*).
This payment option awards the candidate with a 5% discount off the overall tuition fees. Candidates entitled to this discount must meet the requirements found here. The upfront price will then be 3.750 €.
Upfront Payment (10 % discount)
An upfront payment of the entire tuition fees. This payment option will award the candidate with a 10% discount off the overall tuition fees, taking the price down to 7.110 €.
We are committed to giving everyone the opportunity to change their careers and get into technology. For this reason, we encourage anyone who does not see the above payment options as feasible to contact us to discuss our special conditions payment plans:
- – Upfront payment of 2.000€
- – The payment of the remaining standard tuition fees should be made upon job hire, plus 10% of the student’s gross salary in their first year of employment. This amount can be paid in 24 instalments with an interest rate of 6%.
Students can expect a lot of career support from us. So far, they have started careers at companies like Hewlett-Packard, Immfly, Netquest, Netcentric and more.
Tech Solutions ProfessionalAlberto Espinosa, Mar 2018
Sentiment & Business AnalystNeus Montserrat, Oct 2017
Data Analyst - A/B Web TestsAna Luisa Basso, Oct 2017
What you will learn
By the end of this course you’ll be able to use a range of data analysis tools to help any company make better business decisions. You will bring valuable skills to your new workplace, such as interpreting significant patterns, applying data mining to business and engineering tasks, and making predictions based on data sets.
A day in class
Plan and Recap
We start each day at 9am sharp with a stand-up meeting led by the course Mentor. The mentor acts like a project manager and will spend 30 mins discussing with you the tasks ahead, the common pitfalls and organise with you personal 1:1 sessions.
Through our online platform, students get a clearly-structured brief, plan of attack, and list of resources to assist them as they begin the work.
Students share their ideas and work together in groups, just as they would in a real work situation. Students are coming from many different technical backgrounds and will provide new insights for you.
Finish at 5pm
At Ubiqum you will have 800hours effective learning. There’s no need to burn out in the first week. Use the evenings to network, go to Meet-Ups and “live” the Data Scientist life.
The course by weeks
Students will be “working” for Blackwell Electronics as data analysts using the Rapid Miner machine learning package. The student’s job is to use data mining and machine-learning techniques to investigate patterns in Blackwell’s sales data and provide insight into customer buying trends and preferences.
You will learn the algorithmic and organizational skills required to scale data analysis to large server farms, computing clouds, and the web, including an understanding of the design and implementation differences between single-computer and cloud-scale programs, analytics, and data processing.
Students will learn to use the R statistical programming language to perform visualizations, then to generate descriptive statistics and predictive models using time series regression techniques and statistical classifiers. Finally, students will present the results to the start-up’s management, explaining strengths and weaknesses of the approaches that were implemented and making suggestions for further improvement.
"It has been an enriching experience on a professional and personal level since you are in contact with people who have very different backgrounds to you. As everyone has the same objective, you can assist each other and contribute unique knowledge. Just as I did, you will learn many things that will properly prepare you to start a long-term successful career."