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Introduction to Data Science, Big Data and Business Analytics

Altis Global

Monday, 11 September 2017 at 09:00 - Wednesday, 13 September 2017 at 17:00 (BST)

Introduction to Data Science, Big Data and Business...

Ticket Information

Ticket Type Remaining Sales End Price Fee VAT Quantity
Early Bird Rate 6 Tickets 29 Aug 2017 £1,500.00 £49.95 £309.99
Single Rate 6 Tickets 29 Aug 2017 £1,650.00 £52.95 £340.59

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Event Details

Learn the fundamentals of data science and analytics, from problem formulation through to model building and interpretation of results.

Introduction to Data Science, Big Data and Business Analytics is aimed at the professional who wants an introduction to data science with a strong focus on business applications. By the end of the course, participants will be capable of building, tuning and deploying regression and classification models for a variety of business problems. Participants will also gain an understanding of unsupervised learning techniques and big data architecture.

Taught using a variety of open source and cloud technologies, the course teaches techniques for handling, manipulating and analyzing high volume (millions of rows), high dimension (thousands of variables) business data. Real world projects from the DataSeer analytics consulting team are extensively used to illustrate how each model is used in the real world.

Some familiarity with R or Python (in the form of self study or an online MOOC) is recommended prior to starting the course.

Who Should Attend?

This course is suitable for any person who wants to acquire fundamental data science skills


It is recommended that participants have completed an introductory R programming course or MOOC and at least one introductory statistics unit at the university level.

Laptop Required Specs

  • Intel i3 processor, 4GB RAM
  • Either Mac or Windows operating system

Software Requirements

  • Excel 2010 or 2013 or 2016
  • R or RStudio Latest version
  • A free trial or paid subscription to Microsoft Azure ML Studio

Course Objectives

  • Provide participants with an understand of the fundamentals of data science and analytics, from a commercial perspective
  • Provide an overview of the current state of big data and implications for business
  • Introduce machine learning to beginners using applied examples
  • Give participants a framework for selecting the most appropriate data science method for a given use case

Upon successful completion of this course, participants will be able to:

  • Build, tune and deploy basic machine learning models in the cloud
  • Reduce the dimensionality of large datasets using unsupervised learning techniques
  • Use Azure ML Studio and R to analyze and perform predictions on large datasets
  • Understand distributed computing and how it is used by businesses to query large datasets


This course utilizes the following datasets as learning tools:

  • A 750,000 row, 30 variable digital marketing dataset from the insurance sector
  • A 227,000 row, 21 variable airlines dataset

Data Fields

The digital marketing dataset includes information about customer demographics, product category purchased and the digital marketing channel the customer engaged with at each respective online touchpoint.

The airlines dataset includes information on domestic US flights that departed Houston in 2011. The fields include departure time, arrival time, flight number and destination location (alongside 17 other fields).

For more detailed Information:


Isaac Reyes

Isaac is Head of Data Science at Altis Consulting. A passionate data science educator, Isaac has lectured in analytics and statistical theory at the Australian National University, AIM and the University of Canberra.

Isaac shared his vision for Data Science with perhaps the biggest teaching stage of them all – TEDx. “Speaking about the intersection of Data Science and world issues at a TED event was something that I’ve always wanted to do. My TED talk focused on how we can use Data Science to measure how much we really care about the issues that matter.”

In his previous roles, Isaac has worked as a Data Scientist at leading data consulting firms including Datapharm, Quantium and PricewaterhouseCoopers. He holds a Master of Statistics from the Australian National University and has over 3,000 hours of combined teaching experience. A top Kaggler, his vision is to train 1,000 Data Scientists by 2018.

Do you have questions about Introduction to Data Science, Big Data and Business Analytics? Contact Altis Global

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When & Where

Kingsway Hall Hotel
66 Great Queen Street
WC2B 5BX London
United Kingdom

Monday, 11 September 2017 at 09:00 - Wednesday, 13 September 2017 at 17:00 (BST)

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Altis Global

Since 1998, Altis have been deploying our skills in Business Intelligence, Analytics and Data Management to deliver successful outcomes for our clients by helping them maximise business performance.

Much of an organisation’s operational efficiency can be gleaned from accurate and insightful reporting. Altis look to combine and analyse data in new and creative ways, giving customers the power to make better informed decisions and manage their business performance more effectively.

Altis is built on the philosophy that our people make our business and our clients' businesses successful. Our core ethos of ‘Connecting with Courage, Heart, and Insight' means the firm commitment of our team to building lasting relationships with our clients and sharing the responsibility of delivering their outcomes.

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Introduction to Data Science, Big Data and Business Analytics
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