Data Analysis Course

Data Analysis Course with live classes and personalized advice

Learn to analyze data from scratch with a practical approach, guided by industry professionals. This course combines live classes, personalized guidance, and real-world exercises to help you master the most popular tools and techniques on the market.

Upcoming full-time courses

01 Sep – 26 Oct

Spanish

English

Mon. – Fri, 10:00 – 21:00 (CET)

5.000€

Madrid

More info

01 Sep – 26 Oct

Spanish

English

Mon. – Fri, 10:00 – 21:00 (CET)

4.500€

Online

More info

15 Ene – 08 Feb (2024)

Spanish

English

Mon. – Fri, 10:00 – 21:00 (CET)

5.000€

Madrid

More info

15 Ene – 08 Feb (2024)

Spanish

English

Mon. – Fri, 10:00 – 21:00 (CET)

4.500€

Online

More info

What does the Data Analysis Course include?

Learn to program in Python from scratch.

We believe in hands-on learning, so during your training, you’ll carry out real-world projects in Jupyter Notebooks and learn how to perform A/B testing.


You’ll primarily work with the following libraries:

  • Pandas, Numpy, Matplotlib, Poltly y Seaborn

Topics include:

  • Introduction to Python and data cleaning.
  • Exploratory data analysis.
  • A/B Testing.
  • Interact with APIs and web scraping.

Learn to program in SQL.

SQL is the most popular language for database management and, therefore, an essential part of the technology industry.

Topics include:

  • Introduction to data management and cleansing.
  • Exploratory data analysis.
  • Introduction to Jinja Templating.
  • Query optimization.

Tools you will learn:

  • BigQuery, Snowflake, dbt.

Statistics

Descriptive statistics and probability theory are the foundation of data analysis. We’ve developed several methods to help you strengthen your statistical knowledge while practicing SQL and Python.

Topics include:

  • Correlations and distributions.
  • Working with confidence intervals.
  • Apply: Probability functions, Cumulative distribution functions, Probability density functions, Linear least squares.

Machine learning

Take a deep dive into machine learning projects by creating, training, and evaluating models yourself with the Scikit-Learn library.

Topics include:

  • Introduction to prediction models.
  • Types of prediction models.
  • Supervised and unsupervised learning.
  • Regression.
  • Ensemble methods.
  • Hyperparameter tuning and optimization.
  • Validation.

Learn a wide variety of tools

Learn how to work with unstructured data and represent it visually to ensure effective decision-making using industry-leading BI tools like Tableau and Looker.


Learn how to use the terminal and GitHub for version control and project management.
You’ll receive an introduction to DBT so you can intelligently structure your SQL queries. You’ll also learn about a cutting-edge orchestration tool called Apache Airflow.

Customized Career Planning

We offer our own career coaching methodology and personalized professional support.

Application preparation and support

  • Cover letter and CV tailored to the industry
  • Networks
  • The good application process

Interview Preparation

  • Getting to know you and questions about skills
  • Preparation of technical evaluation
  • Negotiation of offer

Admission process

STEP 1

Send us a message

Candidates wishing to enroll in any of the courses must submit the form with their contact information.

STEP 2

We will contact you

Our admissions team will contact you to answer your questions and ensure our courses meet your needs.

STEP 3

Evaluation (20 minutes)

In some cases, the candidate will be invited to complete a short technical test to verify that their profile is appropriate for the course.

STEP 4

Admission

We will contact you to inform you about the status of your application and the next steps.