Master in Artificial Intelligence
with guaranteed employment
Includes preparation for certifications ISMS + TOEIC + AWS + AZURE
Master in Artificial Intelligence
He Master in Artificial Intelligence It will prepare you to occupy positions of responsibility in one of the booming areas of today's business world: Artificial Intelligence.
Aimed at graduates in computer science, mathematics, physics or other related qualifications.
1700 hours – 68 ECTS.
100% online mode.
With access to the certifications most valued by companies: [ISMS + TOEIC + AWS + MICROSOFT CERTIFIED: AZURE].
Employability 100%.
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Description general
Artificial Intelligence (AI) AI is a powerful, versatile and transformative technology that is revolutionizing multiple sectors. It is characterized by its ability to learn and make decisions from large volumes of data, making it a key tool in the digital age. AI is accessible and flexible, which makes it easy to integrate into various applications and processes, from task automation to predictive analysis.
Its applicability extends to sectors such as health, education, finance and entertainment, where it is generating significant innovations.
Thanks to its growing adoption and its ability to improve efficiency and decision-making, artificial intelligence is one of the most in-demand technologies in today's job market.
Plan of studies
1. INTRODUCTION TO ARTIFICIAL INTELLIGENCE
In this module, you will understand the concept, scope, and history of Artificial Intelligence. You will become familiar with real-world applications and use cases that are transforming various industries, and understand how AI has evolved and where it is headed in the future.
- Definition and scope of AI.
- History of AI.
- AI applications and use cases. In real life.
- Evolution of AI.
2. DATA AS A BASE
You will develop effective strategies and establish strong data governance. You will gain in-depth knowledge of Big Data technologies and data lakes, as well as the ability to apply advanced data mining techniques.
- Data strategy and governance.
- Data Mining.
- Big Data and data lakes.
3. FUNDAMENTALS OF ARTIFICIAL INTELLIGENCE
You will understand the basic concepts of AI, such as agents, environments, and search problems. You will learn how to represent knowledge and apply logical reasoning, while mastering search algorithms, both informed and uninformed. In addition, we will train in programming with key AI languages and tools such as Python, R, TensorFlow, PyTorch, and Scikit-learn.
- AI Basics: Agents, Environments, Search Problems
- Representation of knowledge and reasoning.
- Propositional and first-order logic.
- Search algorithms: uninformed and informed search.
- Programming and AI Tools: Python, R, TensorFlow, PyTorch, Scikit-learn.
4. MACHINE LEARNING
You will understand the essential principles and techniques of machine learning. You will gain knowledge about the different types of learning, whether supervised, unsupervised or reinforcement. You will develop and evaluate supervised learning models for regression and classification tasks, skill
fundamental, as well as understanding key concepts such as generalization, overfitting, and cross-validation.
- Introduction to machine learning.
- Types of learning: supervised, unsupervised and reinforcement.
- Supervised learning models: regression and classification.
- Evaluating machine learning models.
- Basic concepts of generalization, overfitting and cross-validation.
5. NEURAL NETWORKS AND DEEP LEARNING
You will understand the fundamentals of artificial neural networks and become familiar with basic architectures such as the perceptron and feedforward networks. You will learn how to train neural networks using the backpropagation algorithm, and you will acquire the ability to apply neural networks
(CNN) in computer vision and recurrent neural networks (RNN) in natural language processing. In addition, you will understand the concept and applications of Generative Adversarial Networks (GANs).
- Introduction to artificial neural networks.
- Training neural networks: backpropagation algorithm.
- Basic architectures of neural networks: perceptron, feedforward networks.
- Convolutional neural networks (CNN) and their application in computer vision.
- Recurrent neural networks (RNN) and their application in natural language processing. GANs.
6. NATURAL LANGUAGE PROCESSING AND OTHER ADVANCED AI APPLICATIONS
You will develop the ability to create Natural Language Processing applications, such as sentiment analysis, chatbots, machine translation, and text generation. You will also be able to implement Computer Vision techniques, such as image recognition and
object detection. In addition, you will gain knowledge about AI applications in Robotics, including autonomous systems and human-robot interaction, and we will use cloud AI services from providers such as AWS, Azure and Google Cloud.
- Natural Language Processing: Sentiment analysis, chatbots, machine translation, text generation.
- Computer Vision: Image recognition, object detection.
- Robotics and AI: Autonomous systems, human-robot interaction.
- AI in the Cloud: AWS, Azure, Google Cloud. AI Services.
7. ETHICS AND REGULATION IN AI
You will understand key ethical principles in AI, such as fairness, transparency, and accountability. You will be familiar with global AI regulatory frameworks, such as the AI ACT, GDPR, and regulations in the US, China, and the EU. You will develop the ability to identify and mitigate bias in AI systems.
will be crucial, as will understanding approaches and techniques to ensure data privacy and security in AI.
- Ethical Principles in AI: Fairness, transparency, responsibility.
- Global AI Regulation: AI ACT, GDPR, regulations in US, China, EU.
- Biases in AI: Identification, mitigation, social impact.
- Privacy and Data Security: Approaches, techniques, legislation.
8. CYBERSECURITY AND AI RISK MANAGEMENT
You will be able to identify, analyse and manage risks in AI projects. You will learn the techniques required to secure AI systems and understand the crucial role that AI will play in secure digital transformation.
- Risks and Mitigation in AI Projects: Identification, analysis, management.
- Cybersecurity and AI.
- How to secure AI.
- AI and secure digital transformation.
9. AI STRATEGY IN THE COMPANY
You will learn case studies and conduct industry analysis on the adoption of AI in business. You will develop AI products from idea to market and acquire the ability to lead and manage AI teams. In addition, you will be able to evaluate the impact of AI in terms of ROI, success metrics and scalability.
- AI Adoption in Business: Case Studies, Sector Analysis.
- Leadership and Management of AI Teams: Training, talent management.
- AI Impact Assessment: ROI, Success Metrics, Scalability.
- AI Product Development: From idea to market, MVP, iterations.
10. AI PROJECT MANAGEMENT
You will learn project management methodologies in AI, such as Agile, Scrum and Lean. You will learn how to manage the complete life cycle of AI projects, from start to finish, including planning, execution and monitoring. You will also use project management tools such as
JIRA, Asana and Trello.
- Project Methodologies in AI: Agile, Scrum, Lean.
- Project Life Cycle Management
- AI: Initiation, planning, execution,
- monitoring, closure.
- Project Management Tools: JIRA, Asana, Trello.
11. MASTER'S FINAL PROJECT
You will be able to propose, develop and defend a complete AI project. You will apply the knowledge and skills acquired throughout the master's degree to a real-world challenge or research area, and prepare for the transition to professional roles in the field of AI.
- Ability to propose, develop and defend a complete AI project.
- Ability to apply the knowledge and skills acquired throughout the master's degree to a real-world challenge or area of research.
- Preparing for the transition to professional roles in the field of AI.
With the Master in Artificial Intelligence, you can get:
TOEIC
EIP MASTER'S DEGREE
QUALIFICATION EUNEIZ
HARVARD CERTIFICATION
ISMS FORUM CAIP
AWS CERTIFIED MACHINE LEARNING
MICROSOFT CERTIFIED: AZURE
Works at Artificial intelligence
After completing the training of Master AI, you can occupy any of the following positions of responsibility:
Machine Learning Engineer/Scientist
Deep Learning Engineer
Data Scientist
NLP Engineer
Computer Vision Expert
Ethical and Legal AI Specialist
AI Project Manager
AI Researcher
Our Teachers
Active sector professionals from large companies and firms.
Companies that hire our Talent
OPINIONS OF
Our student body
Gari Hiroshi Cotrina.
★★★★★
"It was an excellent experience to have completed the master's degree in Cybersecurity Management, Ethical Hacking and Offensive Security at the EIP. I would like to thank the teacher."
and to the tutors for being up to the task of this training. Thank you very much.»»
Juanma Rodriguez.
★★★★★
«Great team of professionals and teachers! In my case, I have taken the master's degree in cybersecurity management and the content is up to date and very well presented. They adapt and listen to the students.»
Cristina Polo.
★★★★★
«I have taken the Full Stack New Digital Economy Professionals course with them, the content of this was very interesting and I have learned
lot."
Jacob Ruiz.
★★★★★
«The course material, the teacher and the coordinators were fantastic, I learned a lot. I also wanted to mention the EIP for its work and involvement in training and job placement.»»
