Introduction to Data Science Course - Award Winning Learning Platform
Skillsology
Summary
Overview
The course teaches the analytical and statistical skills to allow students to turn data into actionable insights.
It also covers how to use an analytical tool kit consisting of widely available or free software (principally Microsoft Excel and the R programming language), to allow statistical analysis and visualization.
Do you ever find yourself asking any of the following questions when at work:
• Which of two versions of a web page will attract more readers?
• What's our likely web traffic next year?
• Where should we position our new warehouse?
• Which of our customers might sell more to?
• What can we do that will most improve customer satisfaction?
If you do, but you don't know the answers then you may need data science. This course teaches the key elements of data science, allowing business generalists to solve real business problems. It is an accelerated way for those interested in data science to improve their abilities.
CPD
Description
Highlights
Discover the skill set of a Data Scientist, a new role meeting the increased demands and opportunities of the web and modern technology:
• Use your analytical skills to manipulate data
• Develop business acumen, so findings are applicable in the real world
• Master statistics, to separate vital signals from irrelevant noise
Syllabus
Section 1: Introduction
Unit 1.1 - Introduction
An introduction to the course providing you with an understanding of what data science can do and the skills involved.
Section 2: Software Tools
Unit 2.1 - Software Tools Overview And Setup
The rationale for using Excel and R and how to set up so you are ready to work with them.
Unit 2.2 - Basics of Excel
Discover using Excel as a toolkit for the data scientist.
Unit 2.3 - Basics of R
Discover using R as a toolkit for the data scientist.
Unit 2.4 - Section Summary
A section review on the key elements of Excel and R that will enable you to manipulate and analyse data to develop insight.
Section 3: Understanding Data
Unit 3.1 - Initial Appraisal of a Data Set
How to get to grips with a new data set.
Unit 3.2 - Handling Big Data
Use R to examine a big data file in order to understand it, clean it and retrieve the information you are looking.
Unit 3.3 - Characterising a Data Set
How to characterise / summarise a new data set.
Unit 3.4 - Probability
The basics of probability, and how to calculate and combine probabilities.
Unit 3.5 - Section Summary
A section review on how we can understand, describe and interpret a data set.
Section 4: Inferences from Data
Unit 4.1 - Visualisation
How to understand a whole population by looking at sample data from it.
Unit 4.2 - Making Predictions
How to present data visually in order to allow for a greater understanding and insight.
Unit 4.3 - Decision Making
How to use data to inform decision making.
Terms
You will receive 12 months 24/7 access to your chosen course
Your course subscription will automatically renew after 12 months unless cancelled by the user. You may cancel the renewal at any time
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This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.
