During this course, you will learn:
- Building and deploying machine learning models using open source R programming language, including data preparation, visualisation, and stringent model validation.
- High-performance ML using the newest version of Microsoft ML Server and SQL Server 2019 with R and RStudio.
- Deployment to production with nanosecond-scale performance.
- Successful data science project formulation and delivery.
Above all, this course will teach you modern R: currently, the most powerful language explicitly designed for advanced analytics, statistical learning, data science, and cutting-edge general-purpose machine learning. While Python is more popular as a universal programming language, also widely used for image and text analysis using deep learning, R is a clear leader in data science. You will learn how to do machine learning in R especially on classical data sets that you often encounter in business use. Even though such data might come from a data lake, typically you will ﬁnd plenty of it in a data warehouse, a relational databases, or you can acquire it from transactional business application ﬁles, or from devices, such as: healthcare equipment, point-of-sales devices, or manufacturing and transportation machinery. Above all, R is great for exploratory analysis of data and it can help you draw meaningful conclusions from real-world experiments, such as A-B marketing tests or product trials. This course will teach you the foundations of hypothesis testing in order to be able to draw such conclusions with a high dose of conﬁdence.
Target audience: Analysts, budding and current data scientists, data engineers, DBAs, BI developers, programmers, power users, predictive modellers, forecasters, consultants, data engineers, anyone interested in using ML for AI, AI engineers.
Prerequisites: General ability to work with data in any form: using spreadsheets, tables, or databases. Prior knowledge of any programming language is helpful, however, if you are prepared to work harder by asking Rafal questions and doing a little additional homework during the week you can use this course to learn R as your very ﬁrst programming language.
This course will teach you machine learning and data science using R and Microsoft technologies: you do not need to know that before attending.
Learning methods: 50% lectures, 30% demos, 20% tutorials.
Assesment methods: Execution of independent work.
Assesment form: Independent practical tasks on relevant topics.
- You can read more about the program here