What do we teach?

The workshops start by introducing students to the concept of big data and machine learning through the use of real life datasets. The hands-on project contains a series of simple tutorials that are carefully designed for people with no background in programming. The projects will enable students to write programs in a couple of very popular programming languages: Python and R.

These languages come with a rich set of statistical packages. With proper guidance from our instructors, they can be easily applied to any dataset. Our instructors will go over the basic theories behind these packages, help the students apply them on the project's datasets, and walk them through how to properly interpret and present their findings.

The workshops will also offer career advice and networking sessions that will point the students to online resources, academic programs, and career options that can further develop their data analysis and programming skills. The Coding Hive encourages and actively promotes diversity at the student and instructor level.


Students will walk out of the workshops with a deeper knowledge and understanding in:


Big Data

Each workshop will utilize a dataset about the city of Toronto. Datasets will cover various topics about the city’s health system, transportation, economy, real estate, and technology. Students will learn the basic fundamentals of big data. In addition they will have hands-on exercises in obtaining data, assessing data quality, reducing data features, and drafting an analysis plan to help interpret the data. These exercises will also provide inspiration to future app development ideas that can work as portal to share the knowledge gained from their findings.



Workshops will provide a basic introduction to the concept of programming and provide introductory hands-on tutorials in R and Python. These languages are in high demand in the tech and research fields and are currently used to implement applications at companies such as Google, Dropbox, Yahoo, NASA, IBM, Facebook, Mozilla, Twitter, etc. Students will write programs to import large data sets, visualize data features, and perform basic statistical modelling to explore patterns within data. Students will also be provided with a wide variety of resources that can be used to further develop their programming skills.


Data Analytics

As data generation has increased rapidly, statistical knowledge and machine learning have become critical assets in any career, business, or academic program. The topic of statistics might appear to be intimidating or complex to many; however, the workshops are designed to walk the students through basic statistical concepts step by step, breaking down complex statistical theories to simple terminologies. The workshop, through the hands-on tutorials, will also introduce the students to statistical packages that effectively applies these methods to their datasets and will help them interpret and explain their output. Methods covered in these workshop will include topics such as data summary statistics, correlations, hypothesis testing, data modelling, and machine learning techniques.