The Artificial Intelligence course offers you the opportunity to delve into one of the most dynamic and fastest-growing areas in today’s technology sector. Artificial intelligence has become a a key tool for transforming industries, optimising processes and improving decision-making. With demand for such skills on the rise, gaining knowledge in this area will position you as a valuable professional who is well-equipped to tackle the challenges of the future. Throughout the course, you will explore everything from the fundamentals of artificial intelligence to the different types that exist, as well as a An Introduction to Machine Learning Algorithms. Finally, you will put what you have learnt into practice through a turnkey project, consolidating your technical and strategic skills. Our online course allows you to access this knowledge in a flexible way, tailored to your needs and learning pace. Don’t miss out on the chance to be part of the technological revolution!
Artificial Intelligence
AI Development
40 hours
Introduction
Objectives
- To understand the basics of artificial intelligence.
- Identify and classify the different types of artificial intelligence.
- Analyse machine learning algorithms and how they work.
- Apply theoretical knowledge to artificial intelligence projects.
- To assess real-world applications of artificial intelligence across various sectors.
- Develop the critical skills needed to interpret AI results.
- To explore current trends and developments in artificial intelligence.
Table of Contents
TEACHING UNIT 1. INTRODUCTION TO ARTIFICIAL INTELLIGENCE
The state of the art in artificial intelligence
Philosophy of Artificial Intelligence
The future of artificial intelligence
Project development processes using artificial intelligence
Data: your greatest asset
TEACHING UNIT 2. TYPES OF ARTIFICIAL INTELLIGENCE
Machine learning
Deep learning
Transformers
Generation of synthetic data
Hyperparameters in artificial intelligence models
TEACHING UNIT 3. INTRODUCTION TO MACHINE LEARNING ALGORITHMS
Linear regression
Non-linear regression and Support Vector Machines (SVM)
Decision trees and random forests
Fuzzy logic and gradient descent
Recommendation systems
TEACHING UNIT 4. TURNKEY PROJECT USING ARTIFICIAL INTELLIGENCE
Setting up the development environment: Anaconda, Visual Studio Code and Python
Input dataset and data processing
TensorHub, TensorFlow and Keras
Image processing
Generation of artificial intelligence models
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