#IT-04-29 Get ready for a Masters in Data Science and AI
About CourseCoventry University
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.
What Will I Learn?
- 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
Topics for this course
The big question
Welcome to the course00:03:11
Getting the most out of your learning
A day in the life00:03:44
Studying at master’s level
What you will need for this course
Designing a program
Accessing your data
good course but I would probably prefer it to be a bit longer with more python work
The course is thorough in the basic foundations in Data Science which was pleasing to see, I am looking forward towards the content of the Artificial Intelligence they put out.
I enjoyed reading the content, articles and also doing python codes. There were plenty of examples. Nice work
In-depth overview of data science: discoveries of the possibilities of Python, criteria for taking into account data, decision elements on the analysis process.very good course