Get ready for a Masters in Data Science and AI

Get a taste of life as a Data Science and AI Master’s student

On this course, you’ll have the opportunity to explore the disciplines involved in a Master’s degree in Data Science and Artificial Intelligence (AI).

You’ll be asked to work through the fundamentals of coding in Python, and be encouraged to discover other important elements of the field, like mathematics, statistics, and data science thinking.

You’ll be asked to produce your own piece of data science output, get introduced to data ethics, and be taught about the work of data scientists.

This course should help you to assess your understanding of data science and the surrounding topics and should help you to make an informed decision around choosing a Master’s in Data Science and Artificial Intelligence.

Usually courses are 6 hours per week. Based on the results of your self-assessment we advise you to choose the content most appropriate for you. But you are also welcome to complete the whole course which would be a total of 20 hours.

This course is designed for prospective Master’s students looking to enter the Data Science field who would like to learn more about the disciplines involved. This course is also for students who have an interest in Data Science and AI.

The course has been developed by a collaborative partnership of leading Higher Education Institutions led by Coventry University.

We will be using Jupyter Notebook to learn Python. There are many ways to try Jupyter Notebook for free, including Google Colab, Try Jupyter classic notebook or JupyterLab, or install the Anaconda Individual Edition.

This course is designed for prospective Master’s students looking to enter the Data Science field who would like to learn more about the disciplines involved. This course is also for students who have an interest in Data Science and AI.

The course has been developed by a collaborative partnership of leading Higher Education Institutions led by Coventry University.

• Plan and prioritise options for study in order to enter the data science field
• Explore the various elements of data science, including mathematics and Python programming
• Enter further study with confidence
• Produce a data science output