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What You Need to Know About Data Science

An Overview and Direction for Future Learning

Dr. Philip Winder

The goal of this live training is to give participants a high-level overview of the current state of Data Science. We will investigate case studies to show how Data Science is used today, how to develop and run a successful Data Science project, which tools and technologies are most important and what decisions you need to make to ensure success.

This live training is an introduction to help you chart your Data Science journey. You need to decide which parts of Data Science are important to you. You will learn to acknowledge that Data Science is becoming increasingly important in industrial applications and that the body of knowledge is vast. We will put this into context and optimise your actions according to goals that you will develop.

What you'll learn-and how you can apply it

Participants will be able to: - Draw upon use cases and industry case studies - Describe the differences between common Data Science disciplines (e.g. AI, Big Data, Deep Learning, etc.) - Plan a Data Science project and describe common techniques - Describe the common tools and technologies - Be able to make important strategic decisions

This training course is for you because...

  • You want to learn about Data Science but don’t know where to start
  • You are a Developer and need to establish which tools and technologies to use
  • You are a Manager and want to know the basics about running a Data Science project
  • You want a systematic way of charting your future Data Science development


No prerequisites. Engineering, industrial background expected.

Recommended Follow-up

About your instructor

  • Dr. Philip Winder is a multidisciplinary Engineer who creates data-driven software products. His work incorporates Data Science, Cloud Native and traditional software development using a range of languages and tools.

    Phil is the CEO of Winder, a Data Science consultancy in the UK, which operates throughout Europe delivering training, development and consultancy services. He has Ph.D. and a Masters degree in Electronics from the University of Hull, UK.


The timeframes are only estimates and may vary according to how the class is progressing

Everything You Wanted to Know About Data Science: An Introduction

Length: 60 min - Instructors will provide an introduction by discussing the applications and uses of Data Science through case studies. The difference between all the different disciplines (machine learning, analytics, big data, etc.) will be described in this context. (30 min) - Participants will begin to grasp the size of data science as a subject. They will be challenged to apply data science to a current problem. Selected individuals will get the opportunity present their idea and obtain feedback. Q&A. (25 min) - Assignment: Develop your own data science project. A worksheet and worked example will be provided.

Break: 5 min

Data Science in Industry: How to Build a Data-Driven Product

Length: 60 min - Instructors will describe how data products are developed using an industry standard process. Given the model, we will provide an overview of the common techniques used across data science. (30 min) - Participants will be able to plan their own data project and anticipate the techniques that they will need to apply. They will further develop their project idea with an implementation plan. Selected individuals will get the opportunity present their idea and obtain feedback. Q&A. (25 min) - Assignment: How to plan your data science project. A worksheet and a worked example will be provided.

Break: 5 min

Real World Implementations: Where to Start

Length: 60 min - Instructors will discuss real world industrial concerns. We will increase awareness of common tools and technologies. The most important strategic decisions and pitfalls will be discussed. (30 min) - Participants will further develop their project plan based upon technical and strategic decisions. This will help guide them to discover what they need to focus on next. Using their project plan they will develop key learning objectives and tasks that will help make their project a success. (25 min) - Assignment: What’s next? A worksheet and a practical example will be provided.