One of the things that I really love about the tech industry is how often different terms – buzzwords especially – can cause confusion. It isn't hard to see this in the wild. Quora is replete with confused people asking about the difference between a'developer' and an'engineer' and how'infrastructure' is different from'architecture'. One of the biggest points of confusion is the difference between data science and machine learning. Both terms refer to different but related domains – given their popularity it isn't hard to see how some people might be a little perplexed.

As the driving force behind machine learning and Artificial Intelligence (AI), data science can be found at the heart of some of today's most exciting technological innovations--from self-driving cars to surgical robots and beyond. So it should come as no surprise that the best and most exciting careers of today and tomorrow belong to those who know how to work with large sets of data in a variety of environments. The Machine Learning & Data Science Certification Training Bundle will help you get certified in this increasingly important field, and it's currently available for over 95% off at just $25. With eight courses and 48 hours of in-depth content, this training will introduce you to both the fundamentals of data science along with its more advanced platforms and methodologies. After an introduction to the basics, you'll learn how to implement important deep learning frameworks using Python, integrate TensorFlow into your projects, gain valuable insights from complex sets of data, use R in order to build powerful networking systems, and much more.

One of the things that I really love about the tech industry is how often different terms – buzzwords especially – can cause confusion. It isn't hard to see this in the wild. Quora is replete with confused people asking about the difference between a'developer' and an'engineer' and how'infrastructure' is different from'architecture'. One of the biggest points of confusion is between data science and machine learning. Both terms obviously refer to very different things, but given the popularity of the two it isn't hard to see how some people might be a little perplexed.

Big data is at the heart of the 4th industrial revolution -- and a new Open Access, rigorously peer-reviewed journal is helping to fuel this. Frontiers in Big Data provides a centralized pool of cutting-edge knowledge in machine learning, cybersecurity, data mining and other data-related disciplines. By making the latest research immediately and freely available through an online platform, the journal empowers researchers, citizens and companies to rapidly and efficiently share and combine knowledge -- and so drive the big data revolution. Two of these sections, Machine Learning and Artificial Intelligence and Medicine and Public Health, will link to the soon-to-be launched Frontiers in Artificial Intelligence journal, which will focus on core AI fields and their various applications. Leveraging the collective intelligence of diverse research communities is critical for fast scientific progress and technological innovation.

In the intervening years British biotechs have been springing up in the fertile space between drug development and big data, including genomics data specialists Congenica and Eagle, while firms like E-Therapeutics use artificial intelligence to help discover new medicines. Not to be outdone, FTSE 100 behemoth AstraZeneca has plans to map 2m genomes within a decade. Dr Jurgi Camblong, founder and chief executive of Sophia, says his firm could ultimately map the genomes of 50m cancer patients alone a year, helping identify the genetic traits that contribute to the disease. He hopes more data sharing will lead to positive behavioural change in healthcare provision. "My father was sick and for my mother it was a nightmare," he says.

I had the opportunity to speak at TDWI in Chicago today. It was a tremendous venue and a well organized event. I spoke on the topic of machine learning and the big data revolution. The slides are below, although they are not all self-explanatory. A company with manufacturing operations around the world had an inherent cost and distribution advantage, leading to more competitive products.

"Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media. Today's column is written by Tasso Argyros, co-founder and CEO at ActionIQ. I lived through one with my last company, Aster Data. But if you survive a tech revolution, you are usually stronger. The revolution I endured was the big data revolution.