Introduction to Data Science
Start CourseCOURSE OVERVIEW
This free, self-paced data science course will introduce you to some key ideas in data science.
The course provides you with some valuable insights into the career opportunities in this exciting field. You will be introduced to what data science is, how it works and how it can be applied.
Each lesson will have video tutorials, activities, and further reading to supplement your learning.
The lessons involve coding activities that can be accessed in Python notebooks, a web-based programming environment. No previous coding experience is needed to access the course as all the commands used are given. You will interact with activities by copying, pasting and editing existing code.
6 online study sessions
The course is offered via the MEI website, and all the resources will be accessed via this page. The coding tasks can be accessed via Kaggle, but an alternative version is available on Google Colab.
This course uses the A level Mathematics large data sets for the AQA, Edexcel, MEI and OCR specifications as examples throughout the course, but it doesn’t matter if you haven’t used them before.
Introduction to Data Science
The Lessons
The lessons involve coding activities that can be accessed in Kaggle, a web-based programming environment.
-
Lesson 1
Introduction to Data Science
In this lesson, you will be introduced to using code to analyse data. You will work with Python in a Kaggle notebook to explore some data about the weather.
Introduction to Data Science – lesson 1 -
Lesson 2
Pre-processing Data
In this lesson, you will learn some pre-processing (or ‘data wrangling’) techniques and how to group and filter data.
Introduction to Data Science – lesson 2 -
Lesson 3
Data Presentation and Visualisation
In this lesson, you will meet some more techniques for pre-processing and cleaning data.
Introduction to Data Science – lesson 3 -
Lesson 4
The Data Science Cycle
In this lesson, you will use all the skills you have developed so far to carry out an analysis on one of four data sets.
Introduction to Data Science – lesson 4 -
Lesson 5
Introduction to Machine Learning
In this lesson, you will build machine learning models that predict the values of a target feature from one or more input features.
Introduction to Data Science – lesson 5 -
Lesson 6
Machine learning, AI and bias
In this lesson, you will reflect on what you have learned in the course with reference to a specific example.
Introduction to Data Science – lesson 6
Frequently asked questions
All of our Data science courses and resources are free to all students and teachers.
If you would like to discuss how MEI can support you in your teaching journey, then please contact us:
Email: datascience@mei.org.uk
Phone Number: +44 (0)1225 776776
Recommended Courses
University Mathematics Interview Practice
Interview practice for students from state-funded schools who have been invited for an interview by the University of Oxford or the University of Cambridge.
Audience: Years 13 When: 17 Nov – 5 Dec Format: 30 min session Cost: Free
Year in Industry Course
A course for Year in Industry students covering selected topics from A level Mathematics and Further Mathematics relevant to maths and maths-related subjects in higher education to consolidate and develop maths skills.
Audience: Students When: To be confirmed Format: 7 modules with on-screen tests Cost: £90
Preparing for the MAT (Mathematics Admissions Test) – On Demand
Prepare for the MAT at your own pace, explore key ideas, complete interactive tasks and questions with feedback throughout, covering the most common topics of the tests.
Audience: Years 12 & 13 When: On demand Format: 7 online modules Cost: Free
Preparing for the TMUA (Test of Mathematics for University Admission) – On Demand
Prepare for the TMUA at your own pace, explore key ideas, complete interactive tasks and questions with feedback throughout, covering the most common topics of the tests.
Audience: Years 12 & 13 When: On demand Format: 7 online modules Cost: Free
Preparing for the STEP (Sixth Term Examination Papers)
Online specialist tuition to support student preparing for the STEP. A free course for Year 13 students from state-funded schools, academies and colleges in the lead up to STEP.
Audience: Year 13 When: 9 Feb Format: 10 online sessions Cost: Free
Problem Solving Matters
Prepare students for success in problem solving mathematics examinations (MAT, TMUA & STEP), by developing their mathematical thinking and problem-solving skills.
Audience: Year 12 When: June – Sept Format: 3 in-person days, mentor support, and online sessions Cost: Free
Preparing for the TMUA (Test of Mathematics for University Admission)
Specialist tuition to support students preparing for the TMUA which takes place in the lead up to the tests for students in state-funded schools, academies and colleges.
Audience: Year 13 When: Sept and Nov Format: 7 online sessions Cost: Free
Preparing for the MAT (Mathematics Admission Test)
Specialist tuition to support students preparing for the MAT which takes place in the lead up to the tests for students in state-funded schools, academies and colleges.
Audience: Year 13 When: Sept Format: 7 online sessions Cost: Free
Setting out in Problem Solving
Designed to help students start to build strategies to approach unfamiliar problems in mathematics along with information on what university entrance exams are out there.
Audience: Year 12 When: Nov Format: 1 online sessions Cost: Free