Diploma in Artificial Intelligence – Seventh Edition

Online: Tuesdays and Thursdays from 18:30 pm to 21:30 pm.

Graduates from various fields, students, project managers, entrepreneurs, business managers, team leaders, and independent professionals.

Director:

Dr. Claudio Enrique Righetti

Outstanding professional with a PhD in Computer Science from the University of Buenos AiresHe has held important positions such as Chief Scientist at Telecom Argentina y Chief Scientist at Cablevisión – FibertelFurthermore, he has extensive academic experience as a professor and director in the Universidad Austral and the University of Buenos Aires, where He has supervised more than 35 undergraduate and postgraduate thesesHe received the award International Engineering Professional Award 2018 for their contribution to to promote the adoption and development of AI and ML tools in the telecommunications industry (SCTE). Es member of the AI ​​Working Group of TM Forum.

Academic coordinator:

Mag. Diego Adrián Castro

Master's Degree in Data Mining and Knowledge Management of the Universidad AustralHe currently holds the position of Data & Analytics Manager at Nación Servicios (SUBE Card)In academia, he has worked as a professor at the Faculty of Exact and Natural Sciences of the University of Buenos Aires and at UADE. He has been a member of the committee of the Argentine Symposium on Artificial Intelligence and Data Science (ASAID-JAIIO) since 2021. He is a speaker at events related to Artificial Intelligence and its applications, including in the field of football.

Professors:

Mag. Juan Pablo Sokil

Master's degree in Data Mining and Knowledge Discovery from the University of Buenos AiresMaster's candidate in Statistics from FCEN UBA. Artificial Intelligence and Machine Learning Specialist at Allied Group. She has held prominent roles such as, Lead Data Scientist and AI-ML Engineer at Telecom Argentina, and Data Scientist at the Organization of Ibero-American StatesIn addition, he has experience as Data Mining Analyst at Banco Credicoop and Statistical Analyst at CEOP Market ResearchIn the academic field, he works as Professor of Applied Statistics at the National Defense University.

Eng. Horacio G. Arrigo

Professional with a solid academic background, including a Master (candidate) in Data Exploitation and Knowledge Discovery from UBAHe has held prominent roles in companies such as Telecom-Argentina, where he served as Data Science Manager/Tech Scientistrespectively. Currently Director of Data Science Latin America – MetLife ArgentinaIn addition, he has academic experience as a Data Science professor at CoderHouse and as a teaching assistant at the Faculty of Engineering of the University of Buenos Aires.

Mag. Pablo Galiana

Master's degree in Data Exploitation and Knowledge Management Universidad Austral In the academic field, he works as Professor of Artificial Intelligence, Algorithms and Data Structures, and Databases at the Universidad AustralRegarding his work experience, he has worked as software engineer in companies like MuleSoft (Salesforce Argentina), TekGenesis and Datamex Paraguay, all of them dedicated to software development and IT services.

Mag. Adriana Baravalle

Expert in Data Science and Knowledge Management, with Specialization in Strategic Planning, Foresight, Business Intelligence and CryptologyHe has held prominent positions such as Director of Data Science at Eclypsium Inc. and Chief Data Officer at Zentricx SRLHe has also worked as independent consultant in Data Strategy across various industries. In academia, he has been Director of Academic Quality and Postgraduate Operations at the Faculty of Engineering of the Universidad Austral, and Professor on topics like Data Mining and Cybersecurity in various institutionsHe is a member of several international organizations related to technology and has received prestigious awards in international cybersecurity and AI competitions.

Mag. Ignacio Berdiñas

Master of Business Administration – MBA – Magna Cum Laude (IAE Business School). Furthermore, it is Computer Engineer (Universidad Austral), and performed the Professional Program in Artificial Intelligence (Stanford University). Regarding his professional experience, he is MultiplAI Health: Lead ML Engineerwhere he is developing models for genetic sequencing processing focused on non-invasive disease diagnosis.

Module 1 – Fundamentals of Artificial Intelligence and Machine Learning (15 Hours)

1. Defining Discriminative and Generative AI. Introduction to Exploratory Data Analysis. Applications of Artificial Intelligence
2. Introduction to Machine Learning. Types of learning: supervised, unsupervised, and reinforcement learning. Semi-supervised learning.
3. Supervised learning: regression, classification, and model evaluation.
4. Unsupervised learning: clustering, dimensionality reduction, and anomaly detection.
5. Introduction to Reinforcement Learning: Applications and Case Studies.
6. Data preprocessing techniques and feature selection. Evaluation of the efficiency of a machine learning model.

Module 2 – Deep Learning and Advanced Applications (15 hours)

1. Introduction to Artificial Neural Networks. Image processing using Deep Learning. Text processing and applications.
2. Transfer Learning (Transfer Learning) Ensemble Learning.
3. Deep neural networks: architectures (CNNs, RNNs, and GANs), training, and optimization. Model training and optimization. Indicators of model quality.
4. AI Tools and Frameworks: Popular libraries (TensorFlow, PyTorch, etc.), notebooks, and development environments. Online resources: open-source models and datasets

MODULE 3 – Artificial Vision (20 Hours)

1. Fundamentals of computer vision. Image processing. Object detection and classification. Object detection algorithms. Object classification using machine learning techniques.
2. Deep learning for computer vision: CNNs, ViT, and applications. Object detection and classification. Semantic segmentation. Facial and pattern recognition.

MODULE 4 – Natural Language Processing (22 Hours)

1. Fundamentals of NLP: Text preprocessing. Language modeling and word representation. Word embeddings. Language models
2. Use of Recurrent Neural Networks. Transformers and generative models.
3. NLP applications: sentiment analysis, machine translation, text generation, etc.

MODULE 5: Generative Artificial Intelligence (Part 1) (12 Hours)

1. Introduction to Generative Artificial Intelligence (GenAI): Definition and basic concepts. Differences with other AI approaches.
2. Foundational Models. Applications and Use Cases. Generative Language Models. BERT, GPT, DeepSeek, Gemini, etc.
3. Pre-training and fine-tuning. Text generation. Distillation, model compression.
4. Benchmarks for generative models. State of the art.

Module 5: Generative Artificial Intelligence (Part 2) (16 hours)

1. Generative Models of Computer Vision. Generative Adversarial Networks (GANs). Diffusion Models. VAEs Models. Image Generation and Art.
2. Multimodal Models. Augmented Recovery Generation (RAG). Vector Databases. Intelligent Agent Development. Multi-Agents.
3. Biases in Generative AI. Algorithmic bias and fairness. Perplexity. Hallucinations.

Module 6: Ethical Challenges, General Artificial Intelligence and Perspectives (5 hours)

1. Impacts of Artificial Intelligence on Society
2. Ethical challenges in the development and application of AI
3. Artificial General Intelligence: concepts and possibilities. Future perspectives of AI.

Module 7: Final Group Project (20 hours)

Dedicated to carrying out a practical project in groups, applying the knowledge acquired in the previous modules.

TOTAL: 125 hours

Group project chosen by the students.

The Faculty of Engineering of the Universidad Austral They will extend the Academic Certificate of approval of the “Diploma in Artificial Intelligence” to those who comply with the promotion regime.

DISCOUNTS AND BENEFITS

• UA undergraduate graduates:
  • 25% off all UA postgraduate academic offerings (master's degrees, diplomas and programs).
  • 20% off master's degrees IAE and 10% in targeted programs of IAE.
• UA Postgraduate Graduates:
  • 20% on the academic offer of UA diplomas and programs.
• Former students (non-graduates):
  • 15% on the academic offer of UA diplomas and programs.

 Important: Discounts are not cumulative and are subject to availability.

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