Learn Data Engineering
at LearnDataEngineering.com

Road to AI

Currently, the big buzz about big data is probably apt with the number of technologies and tools available to build products and services. Uber, Google, Microsoft, and now Apple are implementing AI to their core business operations to provide real-time AI services in their ecosystem.

I personally believe once due to this success of big data companies, the hype behind AI has blown out of proportions. All businesses are keen to implement some sort of AI technologies to automate processes or at least keen to test the litmus paper.

Andrew Ng, one of the leading pioneers of AI has suggested that the next big innovation in AI will come in the non-software industries, where there might be a huge potential for the market ( estimated 13 Trillion). Advances in AI is also paving way for small data, open frameworks, and auto-ML ( which might eliminate data scientists in a way)


I have always been passionate about statistics and AI since highschool, and this led me to take up Masters course in Data Science and then subsequently take up a role in a real estate agency (SME). While I was able to deliver high-quality analytics by merging and mixing a lot of excel and CSV's, it quickly became apparent that this is not scalable to run in the future. While I become good to clean and visualize data, I am barely being able to to