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      • TID-030/ Data Mining Workshop (R or Python)

      TID-030/ Data Mining Workshop (R or Python)

      User Avatar
      André des Forges
      Diplome et Certifications, MBA, Technologie numérique
      (0 review)
      Free
      • Overview
      Free
      • Overview

      COURSE DESCRIPTION

      With internet’s exponential growth, data and its mining have taken centre stage in most commercial, government as well as international organisations. The increase in access to internet facilities have driven the collection of data in huge numbers, creating new business opportunities, driving sales numbers, providing advanced customer relationship management avenues, in addition to surveillance possibilities. Data mining can serve different purposes in different professional sectors, hence providing a unique and necessary skill to students in the current job milieu. 

      In this interactive course, students will begin to learn the different types of data available to them, its different forms and sources, in addition to building blocks of statistics to ease in. After acquiring basic knowledge of data management, they will develop tactical data analysis skills using the R or Python software under the supervision of their trainer to get get started on their data mining professional journey. They will be introduced to data frames, data sets, as well the syntactical details of the softwares, to be able to use them independently in the future to find meaningful relations and information from data. 

      Learning Objectives:

      • Become familiar with different opportunities of data mining
      • Understand basic concepts of Data and data management 
      • Understand basic concepts of statistics
      • Acquire preliminary skills in using statistical softwares like R or Python
      • Acquire the ability to understand relational analysis, regression 
      • Build an understanding on related issues of Machine learning and Artificial intelligence 

      Prerequisites: minimum TOEIC score of 650, TID 010, TID 020

      DESCRIPTION DU COURS

      Avec la croissance exponentielle d’Internet, les données et leur exploitation ont pris une place centrale dans la plupart des organisations commerciales, gouvernementales et internationales. L’augmentation de l’accès aux installations Internet a entraîné la collecte de données en très grand nombre, créant de nouvelles opportunités commerciales, augmentant les chiffres de vente, offrant des possibilités de gestion avancée de la relation client, en plus des possibilités de surveillance. L’exploration des données peut servir différents objectifs dans différents secteurs professionnels, ce qui confère aux étudiants une compétence unique et nécessaire dans le milieu professionnel actuel. 

      Dans ce cours interactif, les étudiants commenceront à apprendre les différents types de données à leur disposition, leurs différentes formes et sources, ainsi que les éléments de base des statistiques. Après avoir acquis des connaissances de base en matière de gestion des données, ils développeront des compétences tactiques en matière d’analyse de données à l’aide des logiciels R ou Python, sous la supervision de leur formateur, afin de se lancer dans leur parcours professionnel de data mining. Ils seront initiés aux cadres de données, aux ensembles de données, ainsi qu’aux détails syntaxiques des logiciels, afin de pouvoir les utiliser de manière autonome à l’avenir pour trouver des relations et des informations significatives à partir des données. 

      Objectifs:

      • Se familiariser avec les différentes opportunités de data mining
      • Comprendre les concepts de base des données et de la gestion des données 
      • Comprendre les concepts de base des statistiques
      • Acquérir des compétences préliminaires dans l’utilisation de logiciels statistiques comme R ou Python.
      • Acquérir la capacité de comprendre l’analyse relationnelle, la régression. 
      • Acquérir une compréhension des questions liées à l’apprentissage automatique et à l’intelligence artificielle. 

      Prérequis: score minimum de 650 au TOEIC, TID 010, TID 020.

      Links to Resources for presentations and summaries

      Data Mining Definition

      Data Mining: Definitions, 5 Free Tools, and Techniques

      What is Data Mining? Definition of Data Mining, Data Mining Meaning

      How Data Mining Works: A Guide | Tableau

      TOP-10 DATA MINING CASE STUDIES | International Journal of Information Technology & Decision Making

      Download Data Mining Case Studies I

      What are some data mining case studies that use simple data mining algorithms?

      The Age Of Analytics And The Importance Of Data Quality

      The Importance of Data Collection: 10 Reasons Why Data Is So Important

      Read “Going to Extremes: Meeting the Emerging Demand for Durable Polymer Matrix Composites” at NAP.edu

      DATA MINING AND E-COMMERCE: METHODS, APPLICATIONS, AND CHALLENGES DATA MINING AND E-COMMERCE: METHODS, APPLICATIONS, AND CHALLEN

      Data mining in ecommerce

      The Benefits of Data Mining in CRM

      Why Retailers Should Care About Data Mining : Intelligent Enterprise

      Data Analysis with R (Coming Soon!) – BDU

      Big Data Use Cases – Big Data Analytics News

      What Is Data Science, and What Does a Data Scientist Do?

      What is association rules (in data mining)? – Definition from WhatIs.com

      18 Big Data tools you need to know!! – Data Science Central

      Unit Testing in R – DZone Big Data

      How Pokemon Go needed a Kubernetes powered Java cloud

      A Pocket Guide to Data Science

      Data Science and the Imposter Syndrome

      Scalable Software and Big Data Architecture – Software Architectural Patterns and Design Patterns

      The Ultimate Guide to Basic Data Cleaning

      All the Best Big Data Tools and How to Use Them – Import.io

      Navigating the Complexity of Big Data Transformation

      4 Steps to Moving Big Data to the Cloud

      Introductory Data Concepts: Fantastic Video Tutorials from Ronald van Loon

      Big Data Storymap Revisited | Grroups

      5 Steps to Building a Big Data Business Strategy – Data Science Central

      Key tools of Big Data for Transformation: Review & Case Study – Data Science Central

      A Beginner’s Guide to Data Engineering – Part II

       

      Course Features

      • Lectures 0
      • Quizzes 0
      • Duration 14 hours
      • Skill level All levels
      • Language English / French
      • Students 0
      • Assessments Yes

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