Ubiqum Code Academy presents the Data Science intensive bootcamp in Barcelona.
This accelerated professional learning program is aimed at absolute beginners who want to enter the Data Science field as a professional. The Ubiqum methodology is unique in that there are no lectures and rather the student takes the central role in an immersive Learning by Doing program. You will finish the intensive onsite course with 4 Real Projects completed as an Analyst, presentable to any future employer.
Talk to our Team
Admissions Team – Nadia Garcia and Victor Gili
Email us: firstname.lastname@example.org
Call us: +34 931 066 929
Visit us: Carrer Bruc 149, Exiample, Barcelona
Office Hours: Mon – Fri 09:15 – 18:30
– 8 hours / day, 5 months (800 hours effective experience)
– Max 12 students per class
– Career support and expert mentoring
– Especially suited to the following academic or work backgrounds (Maths, Science, Engineering & Business)
- – PhDs are a welcome but not mandatory
– This 100% practical Curriculum is designed and maintained by Data Science experts from Northwestern University and has been taught in the University Carnegie Mellon, USA.
11 June 2018
16 July 2018
10 September 2018
15 October 2018
12 November 2018
Women in Tech:
We support Women in Tech which provides a 5% discount to all women at Ubiqum. This applies to all Tuition Payment Types.
Pay 50% upfront and 50% when you get hired. This commitment allows students to split their tuition before and after their new career. In order to check your eligibility go to ubiqum.com/faqs/ or talk directly with our team. Typically students are finding new roles within 45 days of finishing the course.
Those candidates who do not meet the criteria, but who are highly motivated to take our program and start a career in the tech field, are encouraged to still apply to Ubiqum. Please get in touch with our team at email@example.com.
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."