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Ajit’s research is focused on Data Science for IoT. He teaches the same at Oxford University and UPM in Madrid (@forumoxford + @citysciences). Ajit is also launching a course / certification in Data Sciences for Industrial IoT. His personal research interests include Deep Learning algorithms for IoT/future city domains.

The selection below features some of his recent articles:

• Tutorial – foundations of ML and data science for developers
• Data Science for IoT vs Classic Data Science: 10 Differences
• Enterprise AI insights from the AI Europe event in London 
• Twelve types of Artificial Intelligence (AI) problems
• Data readiness strategies of AI Start-ups
• Book review: The Mathematical Corporation
• Behavioural Biometrics, IoT and AI
• Non-traditional strategies for mid-career switch to #Datascience and #AI
• Enterprise AI: Learning from the evolution of Robotic Process Automaton
• IOTA – The potential to drive Data Science for IoT
• In 2018 – AI will start to bring jobs back from offshore destinations to the West
• GDPR and AI – strategies and options in a nutshell
• Data Science for IoT – The Big Picture
• How you can stay up to date with your #AI and #ML knowledge
• Four Quadrants of the Enterprise AI business case
• Can we use deliberate practise for learning to code #AI and #ML
• Solving problems with DataScience for Internet of Things
• The applications of AI in the Telecoms industry
• Re-thinking Enterprise business processes using Augmented Intelligence
• How to create an #Enterprise #AI Business case driven by Data
• How to use IoT datasets in #AI applications (full stack)
• Landing a 150k USD #datascientist job – Seven things you need to know
• AI and Algorithmocracy: What the Future Will Look Like
• MBA vs. Data Science qualifications – Does #AI and #DataScience explain the fall in MBA applications?

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