Data Science & Analytics Courses
Want in on the fields revolutionizing modern business? Then check out these data science and analytics courses.
Data science and data analytics are two sides of the same coin. One uses data to understand the present, the other to model the future.
Being familiar with one is good. But using these data science and analytics courses to know both is the best way to ensure future success.
You’ll learn things like industry best practices and the most common tools. Plus, of course, important techniques like machine learning and regression analysis.
Countless organisations rely on this kind of analysis. Start today to begin your journey with big data!
Pairs Trading Analysis with R
Learn pairs trading analysis from basic to expert level through a practical course with R statistical software.
Causal Diagrams: Draw Your Assumptions Before Your Conclusions
Learn simple graphical rules that allow you to use intuitive pictures to improve study design and data analysis for causal inference.
Python Basics for Data Science
This Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you’ll be ready to create your first Python scripts on your own!
MSc Data Analytics and Information Systems Management
This program provides the skills required to utilize big data as an integral part of business strategy, as a means to inform crucial decision-making through expertise in data handling.
Unilever Digital Marketing Analyst Professional Certificate
Unlock your future in digital marketing analytics. Build job-ready skills for an in-demand career as a digital marketing analyst.
Excel for the Real World: Gain the Basic Skills of Microsoft Excel
The first of a 3-part series of Excel short courses, covering everything from basic functions and interface to shortcuts and data visualisation.
Introduction to Data Analysis using Excel
Learn the basics of Excel, one of the most popular data analysis tools, to help visualize and gain insights from your data.