Artificial intelligence (AI) is at the core of the industrial revolution 4.0, and its influence in society and economy is every year more pronounced. The availability of large volumes of data and computational resources with affordable costs has made possible, over the last decade, the training of deep neural networks, a powerful tool in machine learning. Multiple companies are already applying this data-driven programming paradigm, while in parallel public administrations are also developing strategic plans to lead the sector. Progress has accelerated in 2023, with systems like GPT-4, Gemini and Claude 3, impressively multimodal. Companies are racing to build AI-based products, and AI is increasingly being used by the general public.
According to the AI Index from Stanford University, in 2023, global corporate investment in AI was over $189B, with a thirteenfold increase over the past decade. Funding for generative AI has surged, nearly octupling from 2022 to reach $25.2 billion. The number of newly funded AI companies in 2023 was 1.812, a 40.6% increase over the previous years. This has resulted in a significant increase of job postings across every sector. In the US, AI-related job postings made 1.6% of all job postings. In Spain, it made 1.4%, while it was 0.4%, in 2018, and the amount of hiring has doubled compared to its average during the 2015-2016 period. These positions require knowledge on natural language processing, computer vision and robotics, applications that have recently experienced great advances thanks to deep learning. Public investment in AI is growing as well. The EU Digital Europe programme will fund AI with a total of €2.1 billion in the 2021-2027 period. This context explains why the job analysis portal glassdoor.com has chosen data scientist and machine learning engineers among the best jobs in the United States during the last years, being the skills in deep learning the most demanded.
The postgraduate course in Artificial Intelligence with Deep Learning aims to satisfy this demand of professionals thanks to an experienced teaching team with world-class reputation in both industry and academia. Course instructors develop deep learning-powered systems for many customers, and also lead ground-breaking research with regular publications in top scientific venues such as the Conference on Neural Information Processing Systems (NeurIPS), the Conference on Computer Vision and Pattern Recognition (CVPR), and the International Conference on Learning Representations (ICLR). With their support, the students in our program become proficient in both the PyTorch software framework for deep learning, and the theoretical basis necessary to understand the opportunities and limitations.
There exist two types of sessions: practical and lecture sessions. Practical sessions are based on a live development and coding of a practical case that students build in synchronization with the instructor, who will address their questions. Lecture sessions are built on top of a recorded talk that students watch previously at their convenience. During the lecture session, the instructors will review the contents of the talk and slides, solve questions from students, and propose exercises to consolidate the learning goals.
All students must have high speed Internet access for accessing the live video-lectures and a computer with a modern web browser.
Núria Sánchez Alumni of the postgraduate course in Artificial Intelligence with Deep Learning
Martí Pomés Technical Lead of Process Robotics Projects in Omya
Júlia Folguera Data Analyst at CatSalut
