Data science & AI for decision makers and senior professionals: The complete package

This is the complete package of our flagship workshop “Data science and AI for decision makers”.

This workshop covers everything that is covered by the three other courses:

1. Introduction to data science for decision makers
2. Thinking like a data scientist without being one
3. Hiring and culture: The soft parts of data science

This workshop is offered at 33% discount compared to booking each course individually.

Who is this for?

This is the perfect course of any decision makers who is thinking to work with data science/AI. Whether you are an entrepreneur, a CEO of an SME or a manager in a huge organisation, this course provides the complete package to help you understand and work with any topics related to data science. From data strategy, to building the right culture, to solving problems using data science, this course leaves no stone unturned.

Total duration

~3.5-4 hours

Add-ons

As part of this course, you get unlimited support over email, an 1-hour data science coaching call, and also become part of our community.

Frequently asked questions

What is the difference between data science and machine learning?

Data science is the broader discipline of extracting insights from data, while machine learning is a specific subset focused on building predictive models. A data scientist might clean data and visualise trends, whereas a machine learning engineer designs algorithms that improve automatically with new inputs. Both roles require statistical knowledge, but their daily tasks differ significantly in scope and technical depth.

How much does it cost to hire a data scientist in the UK?

The average annual salary for a data scientist in the UK ranges between £55,000 and £85,000, depending on experience and location. Senior roles in London often command salaries above £100,000. Companies should also budget for recruitment fees, which typically amount to 15 to 20 percent of the first year’s salary, plus ongoing costs for software licences and cloud computing resources.

What skills are essential for a non-technical manager to understand AI?

Managers need a solid grasp of statistical concepts like correlation versus causation, along with an understanding of model limitations. They should be able to interpret key performance metrics such as accuracy and recall without writing code. Familiarity with data ethics and bias detection is also vital, as these factors directly impact business risk and customer trust in automated decision-making systems.

How long does it take to build a data culture in an organisation?

Establishing a genuine data culture typically takes between eighteen and twenty-four months. This period allows time to implement proper data governance, train staff, and align incentives with data-driven outcomes. Quick wins in the first six months help build momentum, but sustained behavioural change requires consistent leadership support and clear communication of how data improves daily operational decisions.

What is the main difference between a data analyst and a data scientist?

A data analyst focuses on describing what happened using historical data, often through dashboards and reports. A data scientist predicts what will happen next by building complex statistical models and machine learning algorithms. While both roles use SQL and Python, data scientists generally require deeper expertise in advanced mathematics, programming, and experimental design to create predictive solutions.