This course runs over 3 weeks and is delivered in two parts:
The first part introduces broader data science methods essential for empirical research. It covers data processing and cleaning, effective data visualisation for communication and exploration. Students will also be introduced to the fundamentals of machine learning, including supervised and unsupervised learning, model evaluation, and the use of algorithms for prediction and pattern discovery. The second part focuses on text-as-data methods, explaining how to represent and analyse textual information systematically. Students will learn dictionary-based approaches, sentiment analysis, tokenization, vector representations of text (including TF-IDF), topic modelling, and word embeddings. These tools will be applied to real-world datasets such as sales record, political speeches, economic policy documents, and social media posts.
The programme will be taught through interactive lectures and coding sessions in R. Prior experience in any programming language is strongly recommended; the programme will provide guided practice to help students develop and strengthen their computational skills.
By the end of the module, participants will have a hands-on understanding of how to collect, process, visualise, and analyse both structured and unstructured data. They will gain practical skills to draw meaningful insights and causal conclusions from complex datasets, preparing them to apply these methods in academic and policy-oriented research.
How to Apply
Why study this course?
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Hands-on coding: Learn R for data analysis in interactive seminars.
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Modern methods: Explore data processing, visualisation, and predictive modelling.
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Text-as-data: Apply sentiment analysis, topic modelling, and word embeddings to business and economic texts.
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Real-world datasets: Work with sales records, policy documents, and social media data.
What You’ll Gain
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Practical coding skills for business and economic data analysis.
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Ability to process, visualise, and interpret structured and unstructured data.
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Insights into machine learning and text analytics for real-world applications.
This programme is part of the Birmingham International Summer School (BISS), and is designed for international students seeking an introduction to UK academic life. Beyond the classroom, participants will enjoy a vibrant social programme, including cultural visits and networking events, creating an unforgettable experience of studying in Birmingham.