INTRODUCTION TO DATA SCIENCE
Modern businesses are always looking for ways to improve their strategies. "Which webpage attracts more readers?", "Does the new store layout affect sales?" or "What can we do to improve customer satisfaction?" are just a few examples of questions that sit behind decision making in companies.
To answer these questions we need a mix of analytical skills (to manipulate data), business acumen (to apply findings to real-world situations) and statistics (to separate what's essential from what's not).
This is the skillset of the ‘data scientist’, a new job role that has emerged to meet the increased demands and opportunities of the profusion of data generated by the web and modern technology. This course wrests data science back from the data scientist – it teaches the key elements of data science to allow business generalists to solve real business problems themselves. It also provides an accelerated way for those interested in a career in data science.
WHO'S IT FOR?
- No technical, software or analytical knowledge is needed beyond a grounding in basic maths.
This course is suitable to those new to data science who want to understand what data science can do and the skills involved.
It's also suitable for those who want to develop a core toolkit of technical, statistical and analytical techniques that turn data into insight and support business decision making.
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 toolkit consisting of widely available or free software (principally Microsoft Excel and the R programming language), to allow statistical analysis and visualization.
ABOUT THE AUTHORS
Dr Chris Littlewood (Head of Science)
Chris worked as a consultant at strategy boutique Mars & Co after completing degrees in physics and maths at Oxford and Cambridge and conducting research in particle physics at CERN. He has ten years experience in analysis and strategy development, across industries at Mars & Co and then in the rail sector. He leads on the science behind the product, particularly the filtering algorithm. He is a Fellow of the Royal Statistical Society.
Matilde Castanheira (Data Scientist)
Matilde’s role is to analyse all of our data to improve the algorithm that selects which modules each user might need and also to provide useful business improvements. She has a PhD in particle physics where she braved through terabytes of data (that means a lot of data!) to discover the small signal that was of interest to her chosen topic.
"Learning and development had not been created as a continuous activity. Training was often one off interventions with the impact difficult to measure. Filtered has helped us change that in a short period of time. The cultural change it has driven in terms of reinforcing an expectation of continuous learning at all levels is the biggest achievement to me."
"We partnered with Filtered because we liked the idea of learners being able to tailor resources based on their knowledge gaps. The quality of reporting data provided allowed us to calculate an ROI of £1.80 for every £1 invested in a licence."