The Course: Practical Applications of Machine Learning, Deep Learning and Data Science offers you the opportunity to gain an insight into one of the fastest-growing sectors with the highest demand for skilled workers. These days, the ability to analyse data and extract value from it is essential for making strategic decisions in any sector. This course prepares you to master Python tools and libraries, which are essential for implementing Machine Learning and Deep Learning algorithms. You’ll also learn how to use PowerBI for data analysis and visualisation, essential skills in the field of Data Science. By taking part, you will not only gain cutting-edge technical knowledge, but you will also be ready to develop real-world applications that can transform processes and make an impact in the professional world.
Practical Applications of Machine Learning, Deep Learning and Data Science
AI Academy
40 hours
Introduction
Objectives
- Understand and apply machine learning algorithms using Python and its libraries.
- Implement deep learning models in Python to solve complex problems.
- Analyse and visualise data using PowerBI effectively and professionally.
- Develop practical data science applications for analysing real-world data.
- Identify and use key tools in machine learning and deep learning.
- Integrate machine learning solutions into software development projects.
- Evaluate and optimise machine learning and deep learning models to improve their performance.
Table of Contents
TEACHING UNIT 1. MACHINE LEARNING. IMPLEMENTATION OF ALGORITHMS IN PYTHON AND MACHINE LEARNING TOOLS AND/OR LIBRARIES.
Linear Regression.
Logistic Regression.
Neural Networks.
Clustering.
Principal Component Analysis (PCA).
TEACHING UNIT 2. DEEP LEARNING. IMPLEMENTATION OF ALGORITHMS IN PYTHON AND DEEP LEARNING TOOLS AND/OR LIBRARIES.
Deep neural networks.
Algorithm optimisation.
Convolutional neural networks.
Recurrent neural networks.
NLP. Natural Language Processing.
TEACHING UNIT 3. DATA SCIENCE. DATA ANALYSIS AND VISUALISATION USING THE POWERBI TOOL.
Creating tables and reports.
Data transformation and filtering.
Data visualisation.
Calculation. Relationships between data tables, metrics and indicators.
Dynamic and interactive control panel.
TEACHING UNIT 4. DEVELOPMENT OF REAL-WORLD APPLICATIONS.
Application. Object classification in images.
Application. Object detection in images.
Application. Facial recognition.
Application. Word recognition for voice assistants.
Application. Business Intelligence.
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