Data Science Fundamentals Workshop Series | July 12

Explore one of the most promising and in-demand career paths for skilled professionals.

Basic business intelligence was once the gold standard in generating insights to drive important business decisions. In the information age, the amount of data available to businesses is nearly surpassing our ability to store, access, and analyse the results in an efficient manner.

Data Science is emerging as a discipline to help take business intelligence to the next level by making it easier to harness large amounts of data, make accurate and useful predictions, as well as create data-driven recommendations. Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals.

The goal of this workshop is to give you a taste of data science. We will define what data science is and introduce the data scientist’s toolset through examples and case studies. By the end of this session, you will be able to phrase problems in data science terms, approach the solution in a structured and rigorous manner, and understand how data visualisation can help convey uncovered insights.

• Explain the field of data science, defining common roles, benefits, and trends
• Recognise the different types of problems that can be solved by data scientists
• Discuss common machine learning models and their uses
• Define the standard lifecycle of a Data Science project
• Explore popular tools and resources to visualise, analyse, and model data
• Identify key elements of the Data Engineering Technical Stack
• Use Data Visualisation as a tool in Exploratory Data Analysis

Install Anaconda prior to class.

• This class is taken completely online via Zoom.
• We will provide a link to the session 24 hours before & again, on the day of the class, to the email used to purchase a ticket. If you have signed up on behalf of a friend or colleague, please forward along this information.

NOTE: this class will not be recorded, however, slides will be sent within 7 days following the session.

Curiosity and enquiry has helped Jesús (better known as J) follow a winding path that has passed from physics, chemistry, finance, analytics and even data journalism. He obtained a PhD at Imperial College for work on quantum atom optics and has worked in academic and research posts for Imperial College London and the University of Hertfordshire, as well as for organisations such as IBM Data Science Studio, Prudential and Dow Jones. He has published a number of academic papers and is the author of a couple of books including "Data Science and Analytics with Python".

When not working you can find Jesús tuned into sci-fi films (good and bad), watching rugby, trying to improve his running times, or writing bits and pieces for his blog.