Top 10 Data Science Videos on Youtube
Learning and the future are the key topics in the recent Youtube videos on Data Science. The main questions revolve around: “how to become a Data Scientist”, “what is a data scientist”, and “where data science is going”. But why there is so little explanation of data science to the masses?
By Marco Nasuto, Data Scientist.
Learning and the future. Looking at top 10 most-watched videos containing the words ‘Data Science’ and/or ‘Data scientist’ in the title, published in the last 2 years, it stands out quite clearly that at the moment the main questions behind the most common queries revolve around: ‘how to become and what a data scientist is’ and ‘where data science is going’.
Screencastings and conferences still rule the style of communication whereas there is an evident lack of documentaries and more entertaining video contents that try to break-trough a non-technical, broader audience. The average length is around 65 minutes whereas the average number of views is 85,732. Even though the number of views may not be the only performance index, as a benchmark, in 2015 the average views per YouTube video of Science&Technology was 6,638, while Educational videos had 4,872 views.
David Langer, Senior Director, BI and Analytics at Microsoft, holds a series of in-depth, hands-in tutorials on data science using R, going through the evergreen of Kaggle’s competitions: Titanic 101. The visuals, from a communication point of view, are simple and effective for the purposes of the video: a classical screencasting with audio narration.
The 3 hours, 10 minutes and 35 seconds tutorial offered by Simplilearn holds the second place of this most-watched top-10. It is quite impressive considering that the average length of the top 50 YouTube videos is roughly 3 minutes. The video is the fourth part of a series of tutorials that offer both a hands-in approach with some explanations on the theory behind predictive modelling. It covers the main types of regression models and some of their applications through some case studies. A slow-paced, screencasting with a narration (that sometimes might result a bit monotone), but perfect for beginners. The full ‘Data Science with R Language Certification Training’ course by Simplilearn is available here.
The third place is hold by another tutorial on Data Science using R, Apache Mahout and Hadoop framework. This first part of the series of tutorials hold by Edureka!, gives mainly a more speculative introduction to Data Science (what Data Science is, the problems it tries to solve and prospects), Hadoop framework, R and machine learning using Mahout, ending with a more hands-in approach. 2 hours, 32 minutes and 55 seconds. Most watched videos on Data Science definitely seem not to follow the typical YouTube golden-rule for length.
“Understanding and innovating with data has the potential to change the way we do anything for the better” – President Obama.
Dr. DJ Patil’s speech at Strata + Hadoop O’Reilly’s conference starts with the special message of President Obama advocating Data Science. This is the first video in the top-ten that delivers a broader picture on Data Science, its culture and possible impacts rather than a “how to” tutorial. The style is definitely engaging, with Dr. DJ Patil highlighting some critical points on how to unleash the full potential of Data Science in business and society. A must-watch if you are interested into “the bigger picture”.
A video lecture in a series about “how to build a modern analytics approaches” for individuals and professionals who don’t have a background in Data Science. The style is simple and clear: a 1 hour and 52 minutes of screencasting with audio narration. The video is an overview of the models and techniques related to Business Intelligence topics, predictive analytics and big data technologies (i.e. Hadoop) with some cases to show the potential of analytics in a business context. The slides are available here.
The video is the recording of a presentation held by Ryan Orban of Zipfian Academy and Dennis O’Brien of Idle Games “becoming a data scientist”. Ryan Orban offers an overview of what Data Science is, why the need of it, the different possible pathways to follow in order to become a Data Scientist (MS/PhD in Data Science, internships, self-study and immersive programs) and the disciplines embedded in Data Science. Dennis O’Brien’s presentation is about “What it’s like being a data scientist in a small startup”, sharing his learnings and insights with the audience.
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