About corse
This comprehensive seven-day course explores the critical role of artificial intelligence (AI) and big data in transforming modern organizations. As digital transformation accelerates, businesses increasingly rely on these technologies to improve decision-making, streamline operations, and foster innovation. The program is designed to equip participants with a deep understanding of AI and big data strategies, enabling them to navigate the complexities and challenges associated with implementing these technologies effectively. The curriculum covers a wide range of topics, including data management, machine learning algorithms, predictive analytics, and ethical considerations related to data usage. Attendees will gain both theoretical knowledge and practical skills through interactive case studies, real-world exercises, and expert-led discussions. Industry professionals and thought leaders will share insights and best practices to help participants develop strategic frameworks tailored to their organizational needs. By the end of the course, participants will be capable of designing and executing robust AI and big data strategies that align with their business goals. This training empowers professionals to harness the full potential of AI and big data, fostering innovation, improving efficiency, and gaining a competitive edge in today’s fast-paced digital landscape.The Objectives
- Understand fundamental concepts in machine learning and data science.
- Gain hands-on experience with popular machine learning algorithms.
- Learn data preprocessing and feature engineering techniques.
- Develop skills for model evaluation and selection.
- Explore advanced topics such as deep learning and neural networks.
- Foster collaboration and practical application of learned skills through projects.
Training Methodology
The training will employ a blend of theoretical instruction, interactive discussions, and practical exercises. Participants will engage in case studies, group projects, and individual assignments to reinforce learning. Real-world applications will be emphasized, ensuring that attendees can apply the knowledge gained in their respective fields.WHO SHOULD ATTEND
This course is ideal for data analysts, software developers, business analysts, and professionals from any field seeking to enhance their data science and machine learning capabilities. A basic understanding of programming and statistics will be beneficial for participants to maximize their learning experience.Course Outlines
Day 1: Introduction to Machine Learning- Overview of machine learning and data science
- Types of machine learning: supervised, unsupervised, reinforcement
- Key concepts: features, labels, and models
- Introduction to Python for data science
- Setting up the development environment
- Hands-on exercise: Basic data analysis using Python
- Importance of data quality and cleaning
- Techniques for handling missing values
- Data normalization and standardization methods
- Feature selection and extraction
- Introduction to data visualization techniques
- Overview of classification and regression
- Implementation of linear regression
- Decision trees and random forests
- Support vector machines (SVM)
- Evaluation metrics: accuracy, precision, recall, F1 score
- Hands-on exercise: Building a classification model
- Introduction to clustering and dimensionality reduction
- K-means clustering and hierarchical clustering
- Principal Component Analysis (PCA)
- t-Distributed Stochastic Neighbor Embedding (t-SNE)
- Applications of unsupervised learning in real-world scenarios
- Hands-on exercise: Clustering analysis on a dataset
- Importance of model evaluation and validation
- Techniques: cross-validation and train-test split
- Understanding overfitting and underfitting
- Hyperparameter tuning methods: grid search and random search
- Comparing model performance
- Hands-on exercise: Evaluating and tuning a model
Training Method?
- Pre-assessment
- Live group instruction
- Use of real-world examples, case studies and exercises
- Interactive participation and discussion
- Power point presentation, LCD and flip chart
- Group activities and tests
- Each participant receives a copy of the presentation
- Slides and handouts
Training Method?
The course agenda will be as follows:- Technical Session 30-10.00 am
- Coffee Break 00-10.15 am
- Technical Session 15-12.15 noon
- Coffee Break 15-12.45 pm
- Technical Session 45-02.30 pm
- Course Ends 30 pm
21/05/2025
6600 GBP$
20 hours
Madrid , Spain
21/05/2025
6600 GBP$
20 hours
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