What I learnt from giving 120+ Data Science Presentations

What I learnt from giving 120+ Data Science Presentations

6 points to help navigate the world and daily technical practices to become better data communicators. So, here are six points that I think are valuable and some resources I have used when considering presenting my projects.

Reflecting back on the various roles I have had in a Data Science team, it has occurred to me that I am one of the few people who is often asked to present.

From a whole host of meeting invites, to slides in various Teams channels and countless versions of presentations on my laptop, I realised that I had presented more than 120 versions of 18 projects over the last six years — that’s roughly one presentation every three weeks! Through this, I can safely say that I have sat through and given presentations that did not land well with various audiences.

One would argue that this many presentations were unnecessary for technically apt stakeholders in a data literate organisation, but these individuals are few and far between where I work.

Many of my presentations have been time-consuming and cumbersome to prepare, but they have been invaluable in my attempt to become a better Data Science communicator. Regardless, I am thankful of my introspective moments which have led to confidence in my content and communication skills.

To date, being a keynote speaker and attending a panel at Financial Times Energy Summit on ML in the energy industry has been a highlight. Whilst I have so much more to learn, I now know that I can drive an engaging conversation with those who are listening.

So, here are six points that I think are valuable and some resources I have used when considering presenting my projects.

presentations communication data-visualization data-science storytelling

Bootstrap 5 Complete Course with Examples

Bootstrap 5 Tutorial - Bootstrap 5 Crash Course for Beginners

Nest.JS Tutorial for Beginners

Hello Vue 3: A First Look at Vue 3 and the Composition API

Building a simple Applications with Vue 3

Deno Crash Course: Explore Deno and Create a full REST API with Deno

How to Build a Real-time Chat App with Deno and WebSockets

Convert HTML to Markdown Online

HTML entity encoder decoder Online

50 Data Science Jobs That Opened Just Last Week

Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.

Data Visualization in Data Science

How to use graphs effectively while working on Analytical problems. Data visualization is the process of creating interactive visuals to understand trends, variations, and derive meaningful insights from the data. Data visualization is used mainly for data checking and cleaning, exploration and discovery, and communicating results to business stakeholders.

Applications Of Data Science On 3D Imagery Data

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.

Data Science Course in Dallas

Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...

32 Data Sets to Uplift your Skills in Data Science | Data Sets

Need a data set to practice with? Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.