Software Development Engineering

Fundamentals of software development, allowing the student to start creating basic desktop programs. We start by installing an Ubuntu distribution on our laptop and learning how to use Ubuntu at user level. Then we follow the official Python Tutorial to learn the basics of programming and finally we face the challenge of solving a practical case for which we will need to make use of what we have just learned.

1. Creation of basic programmes.
2. Variables.
3. Control structures.
4. Basic memory structures.
5. Conditions.
6. Functions.
7. Input/Output.
8. Embedded data structures.

Fundamental programming concepts. Designed to develop skills in the application of basic programming language methods to abstract problems. Topics include basic programming concepts and Python, computational concepts, software engineering, algorithmic techniques, data types and recursion. The laboratory component consists of software design, construction and implementation.

Introduces students to the essential methodologies and tools for articulating and presenting innovative value propositions in the context of software development. It focuses on developing key skills for effectively communicating complex ideas, with an emphasis on structuring and presenting projects through a pitch deck. This subject addresses the growing labour market demand for profiles capable of conceptualising and communicating technology projects clearly and persuasively. It also contributes to students’ all-round development by fostering critical thinking, structured argumentation and leadership skills, all of which are fundamental to their personal and professional progress in a dynamic business environment.

The most common data structures used by developers when creating software. We will face practical challenges that will make it easier to learn how the most common data structures (lists, trees, graphs and hash tables) work. To do this, we will first create our own implementation for these data types and then integrate our libraries into a program that we have created for a previous block.

Elementary discrete mathematics for science and engineering, with special attention to mathematical tools and proof techniques useful in computer science. Topics include logic notation, sets, relations, elementary graph theory, state machines and invariants, induction and proofs by contradiction, recurrences, asymptotic notation, elementary analysis of algorithms, elementary number theory and cryptography, permutations and combinations, counting tools and discrete probability.

The most common algorithms commonly used to solve sorting and searching problems.

We will tackle practical challenges that will make it easier to learn the most widely used algorithms for solving list sorting and list element search problems. To do this, we will first create our own implementation of these algorithms and then integrate our libraries into a program created for a previous block.

Study of computer components and discusses the techniques used by current systems to obtain high performance by exploiting parallelism.

Object-oriented programming paradigm. We will tackle a practical challenge in which we will need to use object-oriented programming to manage scientific data that fit this paradigm. It will involve not only using classes and methods, but also making effective use of the key principles of Object-Oriented Programming: encapsulation, data abstraction, polymorphism and inheritance.

Design project: The main assignment is the design project (DP). This project is where students get to design their own system, which is the main objective of this course.

The DP requires you to develop a detailed system design to solve a real-world problem. This project will span most of the course, and will be done in teams of five students. Real-world systems are not built individually; it is always a team effort. Part of the PD is learning how to work productively and effectively in this environment. We will give you tools to do this in the writing tutorials.

It presents the fundamental principles and techniques of software development: how to write software that is safe from bugs, easy to understand and ready for change. Topics include specifications and invariants; testing, test case generation and coverage; abstract data types and representation independence; design patterns for object-oriented programming; concurrent programming, including message passing and shared memory concurrency, and defending against races and locking; and functional programming with immutable data and higher-order functions. Includes weekly programming exercises and larger group programming projects.

Elementary discrete mathematics for science and engineering, with special attention to mathematical tools and proof techniques useful in computer science. Topics include logic notation, sets, relations, elementary graph theory, state machines and invariants, induction and proofs by contradiction, recurrences, asymptotic notation, elementary analysis of algorithms, elementary number theory and cryptography, permutations and combinations, counting tools and discrete probability.

Basics of client-side web programming. We will face the challenge of creating the client-side part of a business. To do this, we will use HTML to create the web page, CSS for layout and JavaScript for event handling. We will also take care of client-side web security.

Basics of server-side web programming. We will face the challenge of completing our business by implementing its server-side part, making use of a server-side programming language, accessing a database and taking care of server-side web security. All this will be done following the Model-View-Controller design pattern.

We will face the challenge of creating a programme that is capable of managing a company's customer information. This will include performing the corresponding data modelling, defining the Entity-Relationship model, creating databases and tables, and implementing all the functionalities to access the database using SQL. Then, develop a system that makes use of a schema-less database to store, manage and display heterogeneous information from several different sources, each using its own data format. Optionally, students can opt for a distributed solution if they wish.

Basics of Android mobile programming. We will be challenged to create an Android application using Android Studio. This will include managing Android manifests, Graddle build files, activities, snippets and graphical widgets, event handling, layout and styling.

We will face the challenge of creating an advanced Android App that is able to act as a multimedia shop to display/play and record/capture audio, images and video. This App will access a local database to keep track of the information it handles, and will also be able to connect to external servers to exchange complementary information.

Basics of classical software engineering. Students are divided into groups and each group thinks of a project. Then, each group takes the requirements of another group and follows the usual software development life cycle to generate all the corresponding documents (requirements, design, implementation, testing, installation and maintenance). It is not necessary to write source code for the mandatory part. Optionally, students can write the corresponding source code, verify it and then validate it with the client group.

Latest trends and methodologies related to software engineering. Students are separated into groups and each group thinks of a project (which must be different from the previous project in Software Engineering block I). Then, each group will follow the latest trends in software engineering (Lean and Agile methodologies, Kanban method and Scrum methodology) to develop that project. At the same time, students will act as potential clients of the projects they do not belong to.

Cloud computing. We faced the challenge of evaluating and testing how to work in the cloud.

Importance of cybersecurity and its basic principles and techniques.

This module continues the development of entrepreneurial skills, focusing on execution and strategy for creating a new business. It explores the generation and validation of startup ideas in greater depth, and practises the ability to communicate them effectively through an elevator pitch.

The course covers the fundamentals of business strategy, guiding students in the creation of a Go-to-Market model. The culmination of the module is the development of a detailed Business Plan, integrating all the elements studied to shape a viable project. This knowledge prepares students not only to start their own company, but also to work in strategic roles within innovative organisations.

1. Introduction to the world of entrepreneurship
2. Ideas workshop to create a startup
3. Elevator Pitch
4. Introduction to strategy
5. Commercialisation model: Go-to-Market
6. Building a Business Plan

Use of the network and its related protocols. We will face the challenge of creating a client-server solution that allows the users of the client program to share information that will be stored in a program-server that can be accessed by all. This challenge will facilitate learning the client-server paradigm and the basic procedures commonly used to communicate programs over the network.

Fundamentals of Big Data and its ecosystem. We will face the challenge of using Apache Hadoop and Apache Spark to collect and display some KPIs for a hypothetical management team of a company. This company will have a huge customer database with information from various heterogeneous sources (so we will also need to perform ETL actions).

Data science process and techniques.

This module introduces students to the fundamentals of artificial intelligence, focusing on the technologies and tools that power modern applications. It explores neural networks as the cornerstone of deep learning, and looks in depth at advanced architectures such as transformers and diffusers, which are essential for generative and natural language processing models.

The module teaches the practical use of industry-leading tools such as OpenAI and LangChain, enabling students to build and chain language models effectively. The concept of vectors is addressed as the mathematical basis for data representation and similarity. By the end, students will have acquired the essential skills to understand and work with the most innovative AI tools.

1. Transformers
2. Diffusers
3. Neural networks and convolutional networks
4. OpenAI. Lang Chain
5. Vectors

This module delves into the world of artificial intelligence, focusing on the most advanced technologies. It explores Generative AI and LangChain, a key framework for building complex applications using large language models (LLMs). This enables students not only to understand the theory, but also to apply these tools to create innovative solutions.

The course also covers the concept of vectors as the numerical representation of data in a multidimensional space. Students learn how this representation enables machines to understand and compare information efficiently. This knowledge is fundamental to the development of semantic search systems, data classification and any application that depends on advanced information analysis. By the end, students will have acquired a solid foundation for working on the development of AI-based products.

1. Generative AI (formerly OpenAI). LangChain.
2. Vectors

This module introduces students to robotics engineering, combining theory and practice for the design and control of autonomous systems. It covers the fundamentals of dynamic system modelling, enabling students to understand the movement and behaviour of robots.

The course explores feedback control in depth, a key concept that enables robots to interact with their environment and perform tasks accurately. It examines the different sensors and actuators that robots use to perceive their surroundings and execute actions. Finally, it introduces ROS (Robot Operating System), an industry-standard platform for developing robotics applications, facilitating hardware and software integration.

1. Dynamic system modelling
2. Feedback control
3. Sensors
4. Actuators
5. ROS (Robot Operating System)

This module is the culmination of entrepreneurship training, where students apply all the knowledge they have acquired to launch their own project. Building on the foundations of entrepreneurship and the projects developed, the course focuses on real-world practice.

The module focuses on validating hypotheses through the creation of a customer persona, an essential technique for understanding the customer and ensuring product-market fit. Students refine their pitch and explore scalability, learning to design processes and systems that enable business growth. The final presentation before a real audience is the key milestone of the module, where the project’s viability and potential are demonstrated. This module is the final step for students to turn their ideas into concrete business projects ready to be presented to potential investors.

1. Foundations of entrepreneurship
2. Your projects and the pitch
3. Validating hypotheses: Customer Persona
4. Scalability: processes and systems
5. Your final presentation

• Team building.
• Choice of topic for final project.
• Assignment of tutors.
• Development of the project with an assigned tutor.
• Project delivery.

Presentation of the final project before a panel of experts.