Data Analytics & Artificial Intelligence Bootcamp

This module focuses on introducing the fundamentals of programming using Python, a widely used and versatile language that is ideal for beginners and professionals alike. Python is used in web applications, data analysis, artificial intelligence, task automation and much more. Its simple and readable syntax makes it easy to learn and develop, providing a solid foundation for the rest of the bootcamp.

• Introduction and Basic Python Features
• Data Types, Variables and Text Manipulation
• Python Data Structures
• Random Data Generation
• Flow Control Structures
• Python functions
• Manipulation of Dates and Times
• Lambda Functions
• Regular Expressions
• Working with JSON Data

This module provides a comprehensive introduction to the world of databases, covering everything from basic modelling principles to practical implementation using SQL. Through this course, students will learn how to define, manipulate and manage data within structured database systems, using SQL as the primary tool. The goal is to equip students with the skills necessary to design efficient databases and perform complex queries to support business decisions.

• General Concepts and Database Modelling
• SQL and NoSQL databases
• Introduction to the SQL Standard: Data Definition Language (DDL) and Data Manipulation Language (DML)
• Advanced SQL Standard: Subqueries and Common Table Expressions (CTEs)
• Scripting in SQL
• PostgreSQL
• MongoDB

This module focuses on data transformation and data modelling, essential techniques for turning raw data into valuable information in business contexts. Through methodologies such as ETL, ELT, and EL, and using modelling standards such as dimensional modelling and Data Vault, students will learn how to create sophisticated data products. In addition, the course will address the use of modern tools for the orchestration of data flows and the creation of applications and APIs that enable the effective exploitation of transformed data.

1. 1. Data Transformation
   • Modelling Techniques
   • ETL/ELT/EL
   • Data Flow Orchestrators
2. Data Exploitation
   • Creating APIs
   • Data Applications

The module is designed to provide students with an in-depth understanding of how to transform complex data into clear, effective and actionable visualisations. This course addresses both the fundamental principles of data visualisation and the advanced techniques needed to create charts and dashboards that support data-driven decision making.

• Introduction to Data Visualisation
• Types of Graphics and Their Applications
• Designing Effective Visualisations
• Visualisation Tools
• Interactive Visualisation and Dashboards
• Advanced Visualisation
• Case Studies and Applied Projects

Advanced data visualisation is essential for turning complex information into clear insights that support strategic decision making in a business environment. In this module, the focus is on using business intelligence tools such as Power BI and Tableau to generate interactive reports and dashboards that present valuable information to decision makers.

• Concept and Relevance of Storytelling in the World of Data
• Key Elements of a Good Data Narrative
• Tools for Effective Dashboard Implementation: Power BI
• Python Integration for Preprocessing and Visualisation

This module sets the starting point for the world of Machine Learning, introducing you to the key concepts and essential techniques of the field. Through hands-on and applied learning, you will discover how models can unravel hidden patterns in data. The goal is to prepare you to handle more sophisticated challenges and dive into more advanced techniques in later modules.

• Introduction to Machine Learning (ML)
• Life Cycle of an ML Project
• Fundamental concepts of ML
• Supervised Learning: Regression
• Supervised Learning: Classification
• Supervised Learning: Decision Tree and Random Forest
• Unsupervised Learning: Clustering
• Dimensionality Reduction