3-week course

Managing Data for Business Insights - student package

Grow your data analysis skillset and become data literate to increase your employment and career progression opportunities with our intensive data course.

Course overview

Managing Data for Business Insights involves three or six weeks of classes with up to two optional project weeks that will give you the skills to manage datasets efficiently and drive value from data. Data literacy is a valuable career building-block and a key skillset that will enable you to understand the information you or an organisation collects and organise it so that it can be used to communicate clear business or research insights.  Available now through virtual learning.

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Module 1: Three weeks in class plus optional project week​

At the end of Managing Data for Business Insights Module 1, you will understand data cleaning and manipulation concepts and principles. You will have practical experience of using R and SQL programming and be able to manage, clean and analyse datasets to inform decision-making. The course introduces best practice in data coding, version control, reproducibility and data ethics. 

 

Week 01: Intro to data programming

  • Unix, Git and Github
  • Intro to R & R Studio (vectors, data structures)
  • Coding best practices
  • Control flow and functions
  • Reproducibility

Week 02: Managing sources of data

  • Reading and loading data
  • Intro to SQL
  • Connecting and writing to PostGres SQL
  • Connecting R to databases
  • Postico, Advanced SQL
  • Table relationships and joins
  • JSON and lists
  • Data management and governance

Week 03: Manipulating data

  • Intro to Tidyverse
  • Manipulating data in R using dplyr
  • Data cleaning
  • Outliers and missing values
  • Strings and regular expressions in R
  • Ethics

Project Week (Week 4): Ethics and Dirty Data

  • Present short presentation on ethics
  • Dirty data project: clean, organise and analyse messy data 

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Module 2: Three weeks in class plus optional project week

Once you have learned how to clean, organise and manipulate data you need to learn how to create powerful visualisations to provide insights and tell a story. In Module 2, you will learn how to choose the right visualisation for your data, and become proficient in data visualisation and communication using R. You will gain a strong foundation in descriptive and inferential statistics, and complete some advanced topics such as time series analysis and spatial analysis. You finish up the module by learning how to design and building interactive dashboards in R Shiny, and be able to complete a half day Tableau workshop. You will then have a chance to apply your skills in a group project which involves building a dashboard in R Shiny to satisfy a client brief. The group project also involves collaborative development using Git and Github, which is a key skill for coding in a team.

illustration showing data visualisation

Week 01: Visualising Data

  • Plotting in R with ggplot2
  • Creating dashboards in Shiny
  • Learn how to choose the right plot for your data
  • How to create effective and engaging plots
Illustration showing statistics and probability

Week 02: Probability and Statistics

  • Probability
  • Descriptive statistics
  • Inferential statistics
illustration showing Data Through Time​

Week 03: Data Through Time

  • Time and spatial analysis
  • Synthetic data
  • Dashboard design
  • Data Storytelling
illustration showing a data dashboard

Project Week (Week 4): Dashboard Project

  • Building a dashboard in R Shiny
  • Collaborative development work with Git and GitHub

Prerequisites

You must have completed the module 1 to continue on to module 2. If you have already completed module 1 and wish to register for module 2, contact Admissions: admissions@codeclan.com

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A typical day

Here’s what your day will look like while you train in our virtual classroom.

CodeClan students participating in a virtual standup using conferencing technology

Daily stand-up

All the students and instructors meet for a daily stand-up, and to do a review of the homework from the previous night.

Classroom Learning

Our Virtual Learning Experience simulates a classroom-based environment. Lessons are interactive, with instructor led live coding and student participation. The live lessons are also recorded and available for review afterwards.

Lunch

A break for lunch so that students can take a breather, socialise and have some food. 

Lessons continue

Lessons continue in the afternoon, with some days involving afternoon lab work and others focusing more on additional teaching time.

Recap 

The day’s recap is completed and students have an opportunity to start their homework.

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Who is this course for?

This course is ideal for people looking for a solid foundation in data skills, and this package is available for:

  • University and college students who want to start their careers with a robust foundation in data skills
  • Researchers and faculty staff who want to consolidate data skills

“It doesn’t matter how much experience you have with a computer, anyone can learn. I’m amazed at what I can do now.” Delphine, Data Analysis graduate

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Instructors

CodeClan instructors have lots of cross-industry experience, and are on-hand throughout the day to answer your questions. 

Meet Del

“Data is one of the most exciting places to be.”

Del has a degree in physics and a PhD in computational chemistry, has worked as a researcher and teacher at The Universities of Cambridge, Glasgow, Warwick and Stony Brook (USA), and as a software developer in Edinburgh.

Meet Steph

“Data is not just boring spreadsheets.”

Steph has a PhD in cognitive neuroscience, has worked as a researcher and data analysis teacher at the University of Glasgow and UC Berkeley, and has spent time working in the pharmaceutical industry in Edinburgh as a lead data analyst.

Meet Aileen

“Now is a great time to get into data.”

Aileen has a degree in mathematics and statistics and a masters in actuarial maths. She qualified as an Associate actuary while working in investments and pensions before moving into analytical consulting. She is passionate about data for social impact and in the third sector.​

Meet Mhairi

Mhairi has a degree in mathematics and a masters in applied statistics and data mining. She has worked as a data scientist in a range of different industries. She now splits her time between teaching and doing freelance data science work.

Meet Mandy

Mandy has a degree in psychology with an emphasis on research methods, statistics and data analysis. She is passionate about the visualisation and communication of data.

Tune into a webinar or try a taster session.

Meet the team, learn about this course or try coding from the comfort of your own home. See dates.

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Start Dates

Our next cohort is open to everyone based in the UK, and we regularly announce new course dates. 

LocationPre-course workClasses start
UK wide*15/06/202029/06/2020

*This cohort will be delivered through CodeClan’s Virtual Interactive Learning Experience and available to complete remotely

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Funding & Costs

Reduced fee for students and faculty staff*

*Please contact our Admissions Team for details: admissions@codeclan.com.

Standard payment

Once you are accepted, we’ll ask you to pay for the course in full to confirm your place.

Funding

Funding for this course is available through Knoma.

Laptop info

Your laptop must be a MacBook Pro with least 8GB RAM and comfortably run the latest operating system. If your laptop is older than 2014 please check with Admissions to see if it is suitable to use. If you would like to hire a laptop from CodeClan, there is a rental fee of £150.

Start your application

Your questions answered:

Join us for our next webinar, or get in touch with our admissions team for a chat: admissions@codeclan.com