Data Analytics & Machine Learning

In the 3 months (480 hours) of the Data Analytics & Machine Learning course, you'll acquire the most sought after skills in data analytics and gain access to one of the most in-demand professions in the market.

Take it on-campus in Barcelona or online from anywhere in the world.

Talk to our team Apply now

Program schedule

480 intensive hours.
you can take full-time or Part-time

Upcoming bootcamps

3 of April 2023
22nd of May 2023
3rd of July 2023
11th of September 2023
16th of October 2023
20th of November 2023

Languages

English
Spanish



Program description

Acquire the complex skills of a 21st-century business strategist by working through a series of realistic projects. In the Data Analytics & Machine Learning program, you will learn how to apply methods of data analytics to clean and prepare a data set, learn about data mining using R and Python, and learn and use the most common Machine Learning algorithms to model complex business problems. You will also build and deliver convincing presentations to recommend your ideas.

You will have a personal mentor

"During the Data Analytics Course we see how many students, at one point, begin to understand that what we teach them and everything we do at Ubiqum is aimed at training them to think like a professional data analyst."

Our Methodology

What You’ll Learn

When I found Ubiqum and saw that the Data Analytics Course was based around real life projects I knew this was the right course for me

Python, SQL & R

The Python, SQL and R programming languages are the most straightforward languages in use by data scientists and the best languages to learn to develop good data models. They remain essential for almost all jobs in data analysis and data science.

At Ubiqum, you will become fluent in both and will be prepared to work in teams from the two main schools of data science: those who prefer R and those who prefer Python.

Both R and Python have tools that will help you in the pre-processing phases of a project — cleansing and completing data — and they will provide the most commonly used Machine Learning algorithms in classification, regression, visualization and time series analysis. These tools are essential to reach the position of data analyst you aspire to.

logo-python Created with Sketch. Python
logo-r Created with Sketch. R
logo-dplyr Created with Sketch. dplyr
logo-ggplot2 Created with Sketch. ggplot2
logo-amazonwebs Created with Sketch. Amazon Web Services
logo-statistics Created with Sketch. Statistics
logo-machinelearning Created with Sketch. Machine Learning
logo-datamining Created with Sketch. Data Mining
logo-algorithms Created with Sketch. Algorithms
logo-agile Created with Sketch. Agile

Project 1

Develop regression and classification algorithms with Python to analyze customer behaviour and predict future profitability of Blackwell Electronics, a fictional electronics retailer. Collect your findings in a presentation and deliver it to a mock team of non-technical executives.

Predicting Profitability

Data Analytics & Machine Learning

Aurore Paligot

“In just one week in the Data Analytics Course, I've learned how to apply machine learning techniques in RapidMiner and received great advice from my mentor about how to present my data in an effective way. I can't wait to see what's next!”

Project 2

As a member of an Internet of Things startup, you have two problems to solve for two fictional clients:

1) Uncovering patterns of energy usage for cleaner energy design
2) Using wifi fingerprinting to determine indoor locationing with GPS. You'll use R to create complex visualisations, descriptive statistics, and predictive models for both problems.

Deep Analytics and Visualisation

Data Analytics & Machine Learning

Carles Castillejo

"I found this task quite challenging because of the following:

- Data wrangling (loading and cleaning)
- Dataset dimensions

But I got there in the end!"

Project 3

As an analyst for a major data analytics firm, your client, Helios, needs to understand how mobile devices are used by aid workers in developing countries. You will crawl large amounts of smartphone data from AWS to construct a predictive model for aid workers' device usage. You will visualize your model and present it.

Web Mining

Data Analytics & Machine Learning

Pau Pardo

"In this project, I got an idea of how Amazon Web Services (AWS) can be utilised in order to work with a huge amount of data (Big Data)."

Project 4

In the final month of the Data Analytics Course, you will work with the Program Owner to design your own project, for example learning Python to predict and visualise global economic patterns in financial markets.

Design Your Own Analysis

Data Analytics & Machine Learning

Juan Manuel

"I’m very interested in exploring how analysing data could help improve living conditions in cities, so I decided to look into how safe the streets of Barcelona are for pedestrians."

Fill in the form to receive the full syllabus

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A Day in Ubiqum

A TYPICAL DAY IN THE LIFE OF AN UBIQUM DATA ANALYST MIGHT LOOK SOMETHING LIKE THIS:

9:00

Plan your day's tasks in Trello

9.30

"Scrum" standup meeting

10:00

Analyze data in R and Python

Data Analytics & Machine Learning
12:30

Review your insights with a mentor

Data Analytics & Machine Learning
13:00

Extract conclusion and recommendations

Data Analytics & Machine Learning
14:00

Lunch

16:00

Prepare compelling visualisations

Machine Learning
17:30

Present your findings to the group

Data Analytics & Machine Learning
The skills that you learn at Ubiqum are very relevant in the current job market.

Miquel Zelich
Business Analyst for MEDIAURBAN

Fees & Payment Options

We are flexible. You start when you decide.

We will assign you to a personal mentor who will guide and accompany you along all your learning process.

Fees

The full cost of the core course, on-campus, is €6.500

480 hours modules 1,2 and 3. You have some electives if you want to go further in your training. Request and check the syllabus.

Payment Plans

We don’t want financing to be an obstacle:

Check out our payment options.

Apply Now

Can’t wait to start your program?

Start your application today!

FAQs

What is the completion rate and student satisfaction?

Our experience and data have shown:
– Completion rate above 90%
– Employment rate above 92% (within two months of completing the course with full-time competitive salaries).

– Student Satisfaction. You can read our students’ testimonials for a better idea of Ubiqum’s results. Everything we do is to help you start your professional life as a Data Analyst, Web Developer, or Mobile Developer. If you put in your best effort, we will do the rest.

We are confident in our methods and content, demonstrated in the fact that we offer an employment commitment formula (Income Share Agreement) which allows those students who qualify to pay only once they’ve successfully secured employment.

What is Ubiqum Code Academy’s learning methodology?

Ubiqum uses an immersive project-based curriculum developed by experts in Learning and Cognitive Sciences. Our learning methodology focuses 100% on “learn by doing”. You will work on projects similar to those you’ll find on the job and complete them using the same tools used by professionals currently in Data Science positions. A mentor will be available at all times to provide help and evaluate your work. We offer you a supportive and engaging work environment, where you can feel free to make mistakes and learn from your experiences. This will fully prepare you to think like a coder.

How much access do students have to the mentors?

Mentors are full-time Ubiqum staff who are onsite every day. Typically, a student will have one 15-minute personal session a day, and this is complemented by "scrum", the daily stand up, and group code reviews facilitated by the mentors. They also lead guided discussions, or "spikes", around shared topics, such as complex problems that multiple students are working on. You will learn how to work autonomously but you'll never feel lost.

If you would like to speak to any of our mentors, they would be more than happy to discuss the course with you. Please speak with our Admissions Team to organise a video teleconference or visit.