Bachelor in Data and Business Analytics - Study Plan

Harness the power of data to transform the world
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A unique Bachelor in Data and Business Analytics

The study plan for the Bachelor in Data and Business Analytics at IE University has been designed with the prestigious academic experience at its core, our academic faculty’s expert knowledge and research in each area, and the linkages between the University and the professional world.

The Bachelor in Data and Business Analytics aims to teach young ambitious individuals to build the proper skill set to become professionals capable of facing real-world challenges.

Through our hands-on teaching methodology, students from the Bachelor in Data and Business Analytics will find the perfect ideal balance between what is studied throughout their degree and the projects that are applied based on real-world scenarios.

This will aid them to develop profiles that are able to adapt to new trends happening now in the 21st century.
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Bachelor in Data and Business Analytics Study Plan

Year 1

1st semester

Courses
Type
ECTS
Syllabus
Learning to Observe, Experiment & Survey
Type Core
ECTS 6
Fundamentals of Social Sciences
Type Mandatory
ECTS 6
Writing skills
Type Core
ECTS 3
Data Insights & Visualization
Type Core
ECTS 3
Introduction to Business Management
Type Core
ECTS 6
Fundamentals of Statistics and Probability
Type Core
ECTS 6

2nd Semester

Courses
Type
ECTS
Syllabus
Technology Trends Today
Type Mandatory
ECTS 3
Fundamentals of Data Analysis
Type Mandatory
ECTS 6
Simulating and Modeling to Understand Change
Type Core
ECTS 6
The Big History of ideas & Innovation
Type Core
ECTS 6
Presentation Skills
Type Core
ECTS 3
Fundamentals of Human Behavior
Type Mandatory
ECTS 6

Year 2

1st semester

Courses
Type
ECTS
Syllabus
Probability & Statistics for Data Analysis & Management
Type Core
ECTS 6
Mathematics for Data Analysis & Management
Type Core
ECTS 6
Algorithms & Data Structures
Type Core
ECTS 6
Programming for Data Analysis & Management
Type Mandatory
ECTS 6
Forecasting and Time Series Analysis
Type Mandatory
ECTS 6

2nd semester

Courses
Type
ECTS
Syllabus
AI - Machine Learning Foundations
Type Mandatory
ECTS 6
Data Structures and Storage
Type Mandatory
ECTS 6
Intro to Business and Social Analytics
Type Mandatory
ECTS 6
Operating Systems & Parallel Computing
Type Mandatory
ECTS 6
Seminar: Global Issues and Debate
Type Mandatory
ECTS 3
Professional Bootcamp: Teamwork
Type Core
ECTS 3

Year 3

1st semester

Courses
Type
ECTS
Analyzing Social Media
Type Mandatory
ECTS 3
Recommendation Engines
Type Mandatory
ECTS 6
AI - Machine Learning & Analytics
Type Mandatory
ECTS 6
Stream Analytics
Type Mandatory
ECTS 6
Big Data Technology
Type Mandatory
ECTS 6
Project Management
Type Mandatory
ECTS 3

2nd semester

Courses
Type
ECTS
NLP, Text Mining, and Semantic Analysis
Type Mandatory
ECTS 6
Designing Artificial Intelligence & Implementing Smart Technologies
Type Mandatory
ECTS 6
Advanced Databases
Type Mandatory
ECTS 6
Data Visualization, Dashboards & Storytelling
Type Mandatory
ECTS 6
Datathon for Social Impact
Type Mandatory
ECTS 3
Professional Bootcamp - Self Management
Type Mandatory
ECTS 3

Year 4

1st semester

Courses
Type
ECTS
Customer and Markets
Type Electives
ECTS 6
Talent and Professional Development
Type Electives
ECTS 6
Healthcare Delivery - Analytics, Financial Services
Type Electives
ECTS 6
Hospitality, Travel & Tourism
Type Electives
ECTS 6
Environment & Sustainability
Type Electives
ECTS 6

2nd semester

Courses
Type
ECTS
Emerging Topics in Data Analysis & Management
Type Mandatory
ECTS 6
Advanced Topic - Connected Industries, Smart Cities & e-Governments
Type Mandatory
ECTS 3
Advanced Topic - Sales & Marketing Analytics
Type Mandatory
ECTS 3
Advanced Topic - Health & Genetics Analytics
Type Mandatory
ECTS 3
Career Preparation & Design
Type Mandatory
ECTS 3
Capstone Project
Type FP
ECTS 12
Components
Credits
Core Courses
60
Obligatory Courses
138
Electives
30
Capstone Project
12
Credits needed to graduate
240

* Our career-focused electives and projects allow you to apply the knowledge and skills gained during your bachelor to a range of industries and job types. These electives will be taken alongside students of other SST Bachelors to develop your ability to work in multidisciplinary teams.
** This study is under review and may be subject to change.

Contact the Admissions Department for details and updates

Course descriptions

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Bachelor in Data and Business Analytics in a Nutshell

YEAR 1

During your first year, you’ll go through an introductory phase focused on the foundations of liberal sciences. You’ll learn about research methods and how they can be applied to solve technology-related problems through data. During this first year you’ll also study the fundamentals of business, statistics, technology and programming that you’ll need to become a successful data scientist.

YEAR 2

In your second year, you’ll study the latest technologies and tools available in the market that can be used to exploit the power of data. You’ll learn about programming, database modeling, machine learning, forecasting time series and big data technology. You’ll also gain the in-depth statistics and mathematics knowledge you’ll need to interpret and analyze data. Finally, you’ll participate in workshops and boot camps that will help you develop teamwork and other soft skills to build a strong professional profile.

YEAR 3

During your third year, you’ll dive into the data analytics technologies needed to harness the power of data. You’ll take hands-on classes in which you’ll learn by applying recommendation engines, advanced machine learning, cloud computing, semantic analysis, artificial intelligence and parallel computing technologies to real-world challenges. In this year you’ll also participate in a datathon: an intensive competition where you’ll have to apply all that you’ve learned up to this point in order to solve a real business problem by using, crunching and analyzing data.

YEAR 4

In your last year, you’ll be exposed to the professional world through specializations oriented toward certain careers. You’ll be able to choose from a range of electives and courses, selecting those that will help you on your own path toward your favored area or industry. During this year you’ll also take the most advanced courses on software development, business analytics and data privacy. Then you’ll deliver a final project (capstone) in which you’ll integrate everything you’ve learned throughout the program in order to solve a problem or challenge of your choice, with the help of a tutor.

COMPETENCES

GENERAL COMPETENCES

  • Identify, contextualize, analyze and formulate solutions to complex problems in multidisciplinary environments using logical methods.
  • Apply systems and processes through their modeling and analysis with the aim of analyzing their dynamics and identifying the keys to their influence and development.
  • Transform large volumes of data into information and formulate contextualized solutions from a social and business management point of view.
  • Understand innovation as a force for positive change and the methods that render it a tool for the identification and implementation of change.
  • Apply the different computer technologies that form the current work ecosystem for the management, analysis and visualization of data.
  • Develop communication techniques to become capable of presenting proposals, projects and the results of analyses coherently and effectively.
  • Use critical and self-critical thinking effectively during the execution of both individual and group tasks.

PROGRAM-SPECIFIC COMPETENCES

  • Critically analyze data and analysis systems identifying the most appropriate storage, processing, modelling and analysis methods according to the study aims.
  • Understand the different types of data, including the diversity of sources, formats, quantity, quality and usefulness in terms of being amenable to analysis.
  • Apply a variety of techniques related to data mining, algorithm-based machine learning, predictive models and the classification and segmentation of data from different sources and formats.
  • Use visualization tools to explore data, reveal patterns and communicate results to others in order to facilitate decision-making.
  • Design, perform and analyze experiments and other forms of data-driven applied research as a way to test ideas and hypotheses and draw conclusions.
  • Acquire competences in the collection, management, cleaning, structuring, storage and consultation of data both manually and through computer programming.
  • Work effectively with data within organizations’ technological ecosystems.
  • Methodically design and carry out analytical projects in multidisciplinary environments.
  • Understand and apply programmatic and algorithmic thinking for the execution of the different phases of business analytics, including knowledge of the main tools used.
  • Incorporate statistical models into technological tools and smart machines dedicated to data analysis.
  • Apply the knowledge and methods of data analytics to functional areas and business sectors in order to improve their performance, identify opportunities and respond to existing and/or emerging problems.
  • Understand the nature of business, its internal structure and its scope of action from a social (society) and individual (consumer, interest groups, etc.) point of view.
  • Know the principles that govern the behavior of individuals and groups as well as the fundamentals of social activity in the business field.

TRANSVERSAL COMPETENCES

  • Identify the main cultural identity traits that characterize today’s world by understanding the main contemporary ideological trends.
  • Behave professionally in accordance with the core principles and ethics of the profession. Manage unforeseen situations by being able to adapt to organizational changes.
    Use knowledge of the discipline to analyze and evaluate current situations.
  • Form a part of interdisciplinary and multicultural teams to achieve shared goals in a diverse environment.
  • Work actively in an international context.

APPLICABLE REGULATIONS OF THE PROGRAM

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