Data Science Bootcamp - The ProgramLeverage data science to overcome challenges
UNIQUE IMMERSIVE DATA SCIENCE EXPERIENCE
The Data Science Bootcamp gives you the opportunity to work in the decade's hottest profession: Data Science. Data Scientists acquire, clean, structure, store, manipulate, analyze, and visualize data from diverse sources to answer complex business questions in a plethora of departments.
PREPARATORY WORK: LANDING IN DATA SCIENCE
Before starting the Data Science Bootcamp, you will have some preliminary work to carry out to ensure the program begins as smoothly as possible. Once you have been formally admitted, you will have access to exercises in Python and others in math and statistics. We estimate that it will take an average of 15–20 hours to complete all the exercises, which must be submitted no later than two days before the program’s start date. In this way, we can ensure the faculty and management team is properly prepared to guide you during the program, allowing you to make the most out of this learning experience.
This module is designed to give you an in-depth understanding of Python programming language from its syntaxes to coding tips and techniques for script optimization. You will understand the programming structures as this module provides the core coding foundation for you to excel in the rest of the Bootcamp. You will learn to code from scratch in intensive practice-only sessions using exercises and individual programming assignments.
Math and Statistics for Data Science
This module provides the mathematical foundation for the machine learning module as it covers the mathematical and statistical concepts that support data science and machine learning projects. The sessions in this module provide the theoretical knowledge in quantitative methods and statistical models that will complement the Python machine learning workshops. You will learn the statistical models to extract insights from data and the statistical tests to support your findings.
Machine Learning in Python
This module is designed to enhance an in-depth understanding of the practical knowledge in implementing the quantitative and statistical models that are part of the machine learning landscape in Python.
The machine learning classes will provide you with the hands-on training based on analyzing multiple data sets to take your data science and machine learning output to the next level.
Data Acquisition and Visualization
This module will enable you to complement your data analysis skills with the ability to acquire the data from different sources (from text files to Hadoop files and SQL databases) using Python scripts. Additionally, you will learn how to produce powerful and compelling visualizations using Python packages. Picking the right graph can be the difference between being an agent of change or an irrelevant analysis. You’ll learn how to represent data to highlight your work.
Communication and Data Storytelling
In today’s competitive world, having the technical proficiency to achieve success in the data science industry is not enough to mobilize an organization towards change. Crafting a strong narrative and effectively communicating your analysis is critical to get there. This module aims to complement your technical knowledge with the storytelling and communication skills required to maximize the impact of your data analysis.
LIQUID LEARNING AT IE UNIVERSITY
In this new reality, we understand it’s not always possible to attend class in person. That’s why we developed our Liquid Learning approach, which seamlessly adapts to individual needs and provides equal access to world-class education—whether on campus in Madrid or online wherever you are.Discover more
ONE PROGRAM, TWO FORMATS
OUR IMMERSIVE FULL-TIME PROGRAM INCLUDES:
• 12 weeks of duration
• Intensive and extensive focus for quicker high-impact results
• Possibility to be more present on campus, use more resources and facilities
OUR FLEXIBLE PART-TIME PROGRAM INCLUDES:
• 21 weeks of duration
• Optional Spanish or English edition
• Flexible schedule for work-life balance
• Experience a fully immersive week as in the full-time edition