Check out all details on our website thecampus.be.

Overview

This course is intended for everyone with an interest in Big Data and Data Science. What are the differences between the two, what are the most-used tools out there, and how do you integrate these new tools and technologies in your existing workflow.

Course Objectives

Upon completion of this course, participants will understand the following:

• Introduction to Big Data and Data Science. What is it, and what are the differences?
• Possibilities: Big Data and Data Science use cases
• Big Data and Data Science landscape: tools and technologies
• The data science maturity model: the lifecycle of Data Science projects
• Incorporating an innovation workflow into your organization
• Integration within an enterprise architecture and existing BI/DWH stack

Prerequisites

This course covers the absolute basics. A basic understanding of computer technology is required, but we won’t go deep into detail about code. Only concepts and technologies.

Course Content

• Introduction to Big Data and Data Science. What is it, and what are the differences?
• Terminology
• Big Data
• Data Science
• Possibilities: Big Data and Data Science use cases
• Real-life examples of Big Data and Data Science projects
• Big Data and Data Science landscape: tools and technologies
• Big Data Tools
• The Hadoop Ecosystem (Spark, Kafka, …)
• NoSQL Databases
• Graph Databases
• R and R Studio
• Python – Scikit Learn and other Machine Learning Libraries
• Deep Learning and Neural Networks - TensorFlow
• The data science maturity model: the lifecycle of Data Science projects
• Incorporating an innovation workflow into your organization
• Stakeholders within the organisation
• Ideation and roadmap
• Implementing your first case
• Measuring and communicating results
• Integration within an enterprise architecture and existing BI/DWH stack

Meet the trainer

Ben Vermeersch is a technical data architect who has a special interest in traditional sciences, trivial facts and general nerdiness. Throughout the years, he has developed a special appreciation for applied mathematics, especially in the field of statistics and machine learning.

Ben works for InfoFarm, a Data Science company that specializes in Big Data, Data Science implementation and coaching. Ben has experience in building and organizing Big Data and Data Science projects for companies ranging from local startup to multinational and in sectors like marketing, agriculture, fashion, transport, banking, telecom, health and many more.