Intelligence artificielle et données
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Cours, examens, TD, TP et exercices de intelligence artificielle et données. Thèmes couverts : machine learning, apprentissage automatique, big data, data science, fouille de données.
The document provides a step-by-step analysis of MapReduce, a distributed computing framework that abstracts the complexity of multi-node operations. It explains how data traversal and processing are handled using map and reduce functions on Hadoop, offering key-value pair formats for flexible data transformation. The methodology involves parallel processing across nodes, sorting/merging intermediate outputs, and final reduction to yield computed results such as word frequency. It emphasizes the seamless integration of Mapper and Reducer classes in Java, aligning input and output types for...
This document outlines the fundamentals of MapReduce, a programming model for processing large data sets across distributed computing environments. It explains the roles of the map() and reduce() functions, and illustrates the flow of data in a MapReduce job using an example of word frequency distribution in a text file. The document emphasizes how MapReduce abstracts resource management complexities and simplifies parallel processing of data.
This document introduces MapReduce as a paradigm for distributed computing, focusing on its practical advantages over traditional methods for processing large datasets. It explains the methodology through key concepts such as the map and reduce operations, the division of tasks into smaller fragments, and their parallel execution across machines in a distributed cluster. Several concrete examples, such as word frequency analysis and shared-friend calculation in social networks, illustrate the practical utility of MapReduce. These examples, coupled with systematic pseudo-codes, demonstrate h...
Hadoop is an open-source framework, developed by Doug Cutting in 2004 under Apache, for distributed processing of massive datasets (petabyte scale) using clusters of commodity hardware. It facilitates distributed storage (HDFS) and computation (MapReduce) while being fault-tolerant, scalable, economical, and performance-efficient. Its ecosystem includes tools like Hive for SQL-like querying, Pig for scripting, and Mahout for machine learning. Hadoop ensures data reliability with HDFS by partitioning data into large blocks, replicating them across nodes, and utilizing NameNodes for metadata...
The document provides a step-by-step guide for setting up the Microsoft Business Intelligence environment. It highlights the installation of Microsoft SQL Server 2014 Enterprise Edition, emphasizing compatibility and enabling key components like SSIS, SSAS, and SSRS. Additionally, it instructs the installation of SQL Server Data Tools compatible with the SQL Server version installed. The document includes links to video tutorials for further guidance.
The document outlines homework tasks focused on Artificial Intelligence and Robotics. It encourages students to extend their vocabulary and investigate AI through internet research. Activities include creating a poster, composing articles on robots and AI, and writing a letter to an AI expert. The aim is to engage students in interactive and collaborative learning while expanding their knowledge of AI's societal implications.
This document focuses on Ray Kurzweil’s predictions about artificial intelligence, highlighting his belief that computers will surpass human intelligence by 2029. Kurzweil, the Director of Engineering at Google, emphasizes advancements in AI's ability to learn from experiences, tell stories, and even engage in human-like interactions. He asserts that his views on AI have remained consistent over the years, contrasting with a changing public perspective as AI technologies like Siri and autonomous vehicles become more prevalent. His predictions outline a future with computers billions of time...
The document discusses predictions by Ray Kurzweil, a leading AI expert and Google's Director of Engineering, who believes robots will surpass human intelligence by 2029. Kurzweil suggests computers will acquire human-like traits, such as humor and storytelling, and will eventually become one billion times more powerful than the human brain. Despite initial skepticism towards his views, public perception has shifted due to advancements like Siri and self-driving cars. Kurzweil highlights that his consistent predictions have gained credibility as technology evolves.
The document presents predictions by scientist Ray Kurzweil on the advancement of artificial intelligence, suggesting that robots will surpass human intelligence by 2029. It discusses Kurzweil's consistent views on AI development and how public perception has shifted due to technological advancements such as Siri and self-driving cars.
The document outlines projects for the Master's program in Data Science. It includes a continuous assessment and a supervised assignment focused on distributed systems, specifically blockchain technology and mobile device management. A project involving the development of an online voting application is described, emphasizing voter authentication and vote confidentiality.
This document introduces a video discussion from Google I/O 2018, focusing on AI advancements. It challenges the reader to analyze their opinions regarding the innovative uses of AI, surprising aspects of its application, and personal willingness to engage with it. The text highlights how technology showcased in the conference influences modern AI capabilities through practical implementations.
This document outlines a prompt for viewers to engage with a YouTube video from the Google I/O 2018 conference. It focuses on exploring opinions and insights about AI technology discussed in the video. The discussion consists of personal reflections on AI usage, surprising aspects, and willingness to adopt the technology.
The document provides an in-depth overview of Big Data, its definition, importance, characteristics (5Vs: Volume, Variety, Velocity, Veracity, Value), and applications spanning industries like healthcare, marketing, politics, sports, and public security. It discusses technological frameworks like Hadoop and Spark, the methodologies for data processing, and strategies for handling limitations of traditional systems. The document emphasizes distributed systems, parallel processing, scalability, and cost-efficiency as solutions to manage and analyze extensive datasets effectively.
This document outlines the structure and objectives of the first-year Master’s course in Business Analytics & Data Science, focusing on Decision Support Information Systems. It provides a 14-week program divided into four modules covering key concepts, data modeling, integration, and analytical processing using OLAP cubes. The course includes distance learning complemented by forums for discussion and tutor support via synchronous and asynchronous methods. Deadlines are enforced, and tutor assistance is available with a 24-hour response time to facilitate learning progression.
Ce cours vise à introduire les étudiants aux systèmes d’information décisionnels et à maîtriser leur mise en place. Il est structuré autour de quatre modules couvrant les concepts fondamentaux jusqu'à l'analyse des données. La formation se déroule à distance avec un soutien tutoriel et des séances synchrones.
This document focuses on understanding the fundamentals, history, and applications of Artificial Intelligence (AI). Key questions prompt learners to explore the definition of AI, its origins, and its recent growth drivers. The document emphasizes practical uses and potential societal impacts of AI, including job displacement and ethical concerns. Discussion prompts encourage critical thinking and evaluation of AI's advantages and risks in both present and future contexts.
This document outlines a video-based discussion on artificial intelligence. It includes questions regarding the definition, historical context, growth factors, and current uses of AI. Additionally, it encourages pairs to discuss the impacts and potential concerns of AI technology in the future.
The document explores the fundamental concept of Artificial Intelligence (AI), prompting a comparative analysis between human intelligence and AI across different domains. It encourages interactive dialogue on areas where computers excel compared to humans, like speed and efficiency, versus human strengths in creativity and emotional reasoning. The activity also considers the potential future implications of AI surpassing human intelligence in cognitive or decision-making capabilities. Visual aids are included to stimulate thought and discussion among participants.
This document explores the differences and comparisons between artificial intelligence and human intelligence. It prompts readers to engage with visual content and reflect on the capabilities of both. Critical questions are posed to encourage thought on the future of AI and its potential to surpass human intelligence.
The Business Intelligence (BI) program aims to train graduates capable of designing, configuring, and deploying decision support systems and knowledge management systems. It focuses on equipping learners with data analysis skills to assist decision-makers in companies. The curriculum includes a series of technical and soft skills courses over six semesters.
The thesis explores the development and implementation of a Business Intelligence (BI) decision-making solution tailored for tracking purchases and sales in Anouar Market, a retail company. Leveraging BI methodologies, the solution integrates data mart modeling, ETL processes, and Microsoft Power BI dashboards to analyze and visualize critical business KPIs. Key technologies include dimensional modeling and ETL pipelines for data extraction and transformation, enabling actionable insights through user-friendly dashboards. The findings demonstrate the system's capacity to enhance decision-ma...
The report outlines an internship experience at IDsoft, a software company specializing in real estate applications. The author's main project involved contributing to the development and enhancement of the reporting capabilities of IDsoft's SaaS-based ERP solution, IDimmo. The project incorporated Business Intelligence (BI) tools such as SQL Server Integration Services (SSIS), Analysis Services (SSAS), and Reporting Services (SSRS), which were utilized for efficient data handling and reporting. The work facilitated improved data aggregation, visualization, and decision-making processes for...
This Master’s thesis focuses on designing and implementing a maintenance dashboard for CLC-Délice, using Business Intelligence (BI) principles. The methodology involves analyzing the current system, proposing improvements, and creating a dashboard to streamline maintenance management. The solution integrates multidimensional data models, ETL processes, and OLAP analysis to enhance data access and operational efficiency. The study evaluates the deployed application, showcasing significant advancements in maintenance reporting, decision-making, and cost optimization.
This thesis presents the design and implementation of a decision-making solution for the Arab Tunisian Bank (ATB). The project follows an Agile SCRUM methodology, enabling iterative progress and consistent involvement of stakeholders. The solution integrates tools such as Visual Studio and SQL Server to consolidate data from disparate sources, transforming and loading it into a centralized Data Warehouse. The implementation includes interactive dashboards and dynamic reports for monitoring financial metrics, using technologies like SSIS, SSRS, and MDX scripting.