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Digital Marketing - Study Notes:

What is Artificial Intelligence?

Artificial intelligence (AI) can be defined as the theory and development of computer systems that are able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. Effectively, it’s the cognitive processes that machines can use as a way to make key decisions based on key real-time inputs. A very simple example is a bank implementing voice and speech recognition into the internet telephone banking core services. This enables customers to, for example, access a bank balance via a voice recognition system. There are even more complicated and advanced systems being developed.

Catalysts for development of AI

Some catalysts for about the development of artificial intelligence include:

  • Moore’s Law is an observation made by Gordon Moore, a co-founder of Intel, stating that the number of transistors in a dense integrated circuit doubles every two years, or the cost of manufacturing dense integrated circuits halves every two years.
  • The evolution of Big Data is driving artificial intelligence. With Big Data, we can put datasets together and develop predictive analysis.
  • The third aspect is the Internet and the cloud, because they enable us to create networks of connectivity. We will talk about the Internet of Things and how that will start to feature prominently at the forefront of artificial intelligence.
  • Creating new algorithms, or new ways of thinking about things, enables us to create better decision-making processes within our operations.


Some common applications of AI include:

  • Finance: fraud prevention, and avoiding accounting errors
  • Hospitals and medicine: managing patient medical records, treatment design, and medication management
  • Customer services: chat-bots, personalization, customer analytics, and insights
  • Transport: driverless vehicles, traffic management, and airport facial recognition
  • Telecommunications: network optimization, maintenance, and automation

Associated technologies

Some of the technologies associated with AI include:

  • Computer vision
  • Machine learning
  • Natural language processing
  • Robotics
  • Facial or speech recognition
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Jack Preston

Jack Preston is a Data Scientist working within marketing analytics, with a particular focus on strategic customer loyalty. Jack has experience working in both small-scale startups and large corporates, including dunnhumby and Notonthehighstreet. He also holds an MSc in Business Analytics from UCL where he graduated with distinction.


Jack Preston
Skills Expert

This short course covers the principles of analytics and demonstrates techniques and useful tools that you can use to develop and refine your knowledge of data analytics.

You will learn:

  • The fundamentals of data, collecting data, and processing data, including best practices, techniques, and challenges
  • The principles of web analytics, the benefits and limitations of Google Analytics, terminology for reporting, and the legalities around consent and data privacy
  • The concepts of Big Data, the processes around data, including mining, scraping, cleansing, and de-duping, and the various languages and programs for testing your data
  • The importance of AI, Machine Learning, analysis types, the value of testing hypotheses, and forecasting based on the data available
  • How best to report and present data findings to management and the different tools available to you

Approximate learning time: 3 hours