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Applying Data Science and Big Data; Tips from the Experts - 1 day seminar

Date:
Wednesday 18th November 2015
 
Time:
9am to 5pm
 
Venue:
Dublin City Centre
 
Cost:
Complimentary
 
Event Code:
SS15-99
 
Book now


This one day seminar on data science is designed to give a high level overview of the field of Big Data – what it is, why we need it and why now, along with its various toolkits and processes. 

 
Understand how you can use data science to unlock potential, improve efficiencies and drive innovation within your organisation.

This seminar is suitable for entry level data scientists and business people who want to get an idea at what data science can bring to their organisations and what are the best tools for your business.

No coding or hands on mathematics is required for this seminar.

 

Introduction to Data Science 

Data Science – what it is, scope, data science process, what a data scientist does and the main skills that are required.

 

Business Matters & Privacy

Why does data science matter and what can it do for your business? Identify and understand the issues of privacy in big data.

 

Data sets & Data Cleaning

Public, private and government. Understand the various aspects of data cleaning, identify the various types of “messy” data,  and look at various techniques for dealing with these. 

 

Hadoop & MapReduce

Apache Hadoop ecosystem, the family of open source packages for analyzing massive data sets. Gain an understanding of MapReduce, distributing data analysis over compute clusters.

 

Streaming & Spark

Gain an understanding of the various open source data streaming tools being developed and used in data science today, including Apache Spark.

 

Databases - SQL & NoSQL

The different types of databases in use in industry today. Relational (SQL) databases, when they are used, and the proprietary and open source versions available. Become familiar with the various types of NoSQL databases and their use cases.

 

Statistics

The theory and practice of some basic statistics that is relevant to data science. This includes probability distributions and types of analysis.

 

R, Python, Julia

The most popular programming languages being used in data science today.

This includes the statistical package R, an increasingly common and useful open source tool for analysing data; Python, along with its various analytics packages; and the newest data science language, Julia.

 

Machine Learning

Gain a familiarity with machine learning theory, algorithms and applications as they are being used today in data science, including ML packages, deep learning and neural networks. 

 

AI

How to use AI in your business to gain sustainable competitive advantage.

 

NLP

Understand the principles and practices underlying natural language processing, what it is, and how it can help to unlock productivity and innovation in your business.

 

Visualization

The various visualization practices, tools and packages, understand why it is a vital part of any Data Scientist’s repertoire, and how it is important to your business.

 

Internet of Things

The Internet of Things (IoT), its development, the technologies that are enabling it, where it’s going, how fast we will get there, as well as exploring some business use cases.