Bachelor's Degree in Artificial Intelligence and Data Science

Methodology

The methodology with which you will receive your training at La Salle will be eminently practical based on:

• Training focused on learning by challenge.
• Laboratory work as a key element for the assimilation of concepts.
• Problem solving.
• Development of practical exercises that complement the theoretical foundations.
• Cooperative work to promote teamwork and develop interpersonal skills.
• Project-based learning is one of the most widely used active learning methodologies in the degree.

Credits: 240 ECTS

Year 1

Semester 1

• Thought and creativity I (2)
• Fundamentals of programming I (6)
• Mathematical foundations (6)
• Linear algebra (6)
• Computational logic (6)
• Artificial intelligence and its ethical considerations (4)

Semester 2

• Thought and creativity I (2)
• Fundamentals of programming II (6)
• Probability and statistics (6)
• Computing infrastructures (6)
• Differential and integral calculus (6)
• Design and usability (6)

Year 2

Semester 1

• Thought and creativity II (2)
• Advanced programming and data structure (6)
• Mathematical methods (6)
• Business administration (6)
• Methods for advanced data analysis and visualization (6)
• Knowledge-based systems (6)

Semester 2

• Thought and creativity II (2)
• Artificial Intelligence legislation (4)
• Operating systems (6)
• Object-oriented design and programming (6)
• Machine learning (6)
• Databases (6)

Year 3

Semester 1

• Thought and creativity III (3)
• Optimization (6)
• Programming languages (6)
• Software methodology (3)
• Computing infrastructures for artificial intelligence (6)
• Neural networks and deep learning (6)

Semester 2

• Thought and creativity III (3)
• Artificial intelligence projects (6)
• Autonomous systems and robotics (6)
• Artificial vision (6)
• Natural language processing (6)
• Project management (6)

Year 4

Semester 1

Elective Subjects:

• • Supply chain management (6)
  • AI specialization I (6)
  • Data science applied to biomedicine (6)
  • Digital marketing strategies (6)
  • Medical robotics (6)
  • Audio processing with machine learning (6)
  • Principles of human-machine interaction (6)
  • Time series forecasting (6)
  • AI for business processes (6)
  • AI specialization IV (6)
  • Signal processing and medical images (6)
  • Cybersecurity with machine learning (6)
  • AI specialization II (6)
  • AI specialization III (6)
  • Digital transformation of a health center (6)
  • Advanced robotics (6)
  • Financial analytics (6)
  • AI specialization V (6)

Semester 2

• Final Thesis (15)
• Internship (15)

• To train experts in artificial intelligence: Students will be trained to gain a deep understanding of the theoretical and practical concepts of artificial intelligence and data science, covering areas such as machine learning, deep learning, natural language processing, and computer vision.
• Develop advanced technical skills: Students will be trained to acquire solid technical skills in programming, mathematics, statistics, and algorithms, enabling them to design, implement, and evaluate artificial intelligence algorithms.
• Encourage research and innovation: Research and innovation will be stimulated among students, motivating them to tackle challenging problems and contribute to the constant advancement of the field of artificial intelligence.
• Apply artificial intelligence in various industries: Students will be prepared to apply their knowledge of artificial intelligence in different sectors, such as health, energy, commerce, finance, government and public administration, marketing and advertising, manufacturing, and agriculture, to solve real-world problems in multiple contexts.
• Promoting ethics and responsibility in artificial intelligence: Students will be instilled with a deep understanding of ethics and responsibility in the development and implementation of artificial intelligence systems, encouraging ethical practices and reflections in their related activities.

Artificial Intelligence and Data Science graduates can work in a variety of roles and sectors, due to the growing demand for professionals with expertise in these areas.

Some of the possible career paths include:

Artificial Intelligence Professionals

• Artificial Intelligence Engineer. Design and develop AI systems, including algorithms and models.
• Machine Learning Engineer. Focus on the implementation and optimization of machine learning algorithms.
• AI Research Scientist. Conduct advanced research to improve AI.
• AI Ethicist. Address ethical issues related to AI and ensure its responsible use.
• AI Consultant. Provide expert advice on AI projects and their practical application.

Data Science Professionals

• Data Scientist. Work on creating models to extract valuable information and insights from data.
• Data Analyst. Focus on analyzing data to make informed decisions.
• Data Engineer. Design and maintain data infrastructures to ensure availability and accessibility.

Business Applications Professionals

• Business Artificial Intelligence Analyst. Translate data into relevant information for business decision-making.
• Business Artificial Intelligence Developer. Create and maintain business intelligence systems to facilitate access to key information.
• Business Artificial Intelligence Analyst. Analyse data to generate reports and dashboards to support business strategies.