‘Machine Learning, Deep Learning and Data Science: Practical Applications’ is your gateway to success in the rapidly evolving field of data-driven technologies. As industries across the globe increasingly rely on data to drive innovation and decision-making, the demand for skilled professionals in machine learning, deep learning and data science has never been higher. This course, delivered entirely online for maximum flexibility, equips you with the essential skills to understand and implement complex algorithms, master data analysis, and apply these techniques to real-world scenarios. By taking part, you’ll position yourself at the forefront of a booming sector, ready to tackle challenges and seize opportunities with confidence. Embrace the future of technology and unlock your potential with this comprehensive and engaging programme.
Practical applications of machine learning, deep learning and data science
AI Development
40 hours
Introduction
Objectives
- To understand fundamental machine learning concepts and their practical applications.
- To explore deep learning techniques and neural network architectures.
- To analyse data using data science tools and methodologies.
- To implement machine learning models for real-world scenarios.
- To evaluate the performance of deep learning algorithms effectively.
- To apply data science principles in case studies.
- To integrate machine learning, deep learning and data science solutions.
Table of Contents
UNIT 1. MACHINE LEARNING
Linear regression
Logistic regression
Basic Neural Network
Clustering
Principal Component Analysis (PCA)
UNIT 2. DEEP LEARNING
Deep learning
Optimisation
Convolutional Neural Network
Recurrent Neural Network
Natural Language Processing (NLP)
UNIT 3. DATA SCIENCE
Creating tables and reports
Data transformation and filtering
Data visualisation
Relationship between data tables
Dashboard
UNIT 4. CASE STUDY APPLICATION
Object detection in images
Object classification in images
Facial recognition
Word detection
Business Intelligence application
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