Description:
Improve your marketing insights by learning how to effectively use data and data science techniques. This course will teach you how to gain deeper marketing insights through the power of data science and enable you to become a better digital marketer. Developed by the pioneering Data Science team at the University of Southampton – ranked among the top 100 universities globally – this course will teach you how to effectively use data science techniques to improve your marketing insights, better understand your customers, and manage customer interaction in web-based environments.
The course runs over 6 weeks and is broken down into manageable weekly topics:
Week 1: Introduction to common web analytics tools (Googleverse; How people interact with sites; Setting goals; Basic site design – what Google wants; Google Analytics and search console; Facebook advertising)
Week 2: Analytics for digital marketing (A/B testing; Reporting; Traffic and site journeys; Sources and conversations; Reporting dashboards; Integrating traffic with other business metrics)
Week 3: Social network analysis (The role of social networks; Facebook advertising campaigns; Micro-segmentation; Graph theory; Tools for social media analytics’ Content analysis methods)
Week 4: Machine-learning (Definitions of data science; What is machine learning? Different types of machine learning methods and models for marketers; Decision trees; Cluster analysis; How machine learning can be applied to website data; How to choose training data and evaluate the effectiveness of machine learning)
Week 5: Application of machine learning in marketing (Using machine learning for attention, persuasion and retention; Your strategic role in applying machine learning to your work; Limitations of Artificial Intelligence (AI) and ethical considerations )
Week 6: Big data and future applications (What is big data? Volume, variety, velocity, and veracity dimensions and how they apply to marketing data sources; Cloud computing and distributed computing architectures; Data analysis in the cloud; Novel visualisations and applications; Future technological directions)
After successfully completing the course, you’ll be able to:
- Understand the role data science plays in digital marketing
- Describe tools for web analytics and understand how customer journeys and sources can be tracked using these tools
- Describe different ways in which social network analysis can be used to gain marketing insights
- Apply content analysis methods to gain insights into your customer base
- Explain what machine learning is and what it can be used for
- Understand what big data is and how it applies to your business problems
- Identify what data needs to be collected to ensure your digital marketing process is optimised
Key benefits:
- Tutor-led – University of Southampton academics will guide you through the content and answer your questions, unlike other online courses where you’re left to your own devices
- Continuing Professional Development (CPD) accredited, helping you demonstrate your commitment to upskilling at your next appraisal
- Hands-on – learn how to use data science to better understand your organisation’s customers.
Education provider: Southampton Data Science Academy
Southampton Data Science Academy forms part of the Web Science Institute at the University of Southampton – ranked among the top 100 of universities globally. Developed in partnership with leading global education specialists Cambridge Education Group (CEG), the Academy bridges the data skills gap in today’s increasingly data-driven world through world-class training and education from industry-leading academics and thought leaders in the field of data science.
CEG Digital partners with prestigious, high quality UK universities to deliver online or blended courses to a global market on a part-time, flexible basis. Courses are delivered using cutting-edge, tablet friendly technology and sector leading pedagogy.
Southampton Data Science Academy training is CPD accredited, meaning it has reached the Continuing Professional Development (CPD) standards and benchmarks.
Minimum 25 students.
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