All these questions about the Internet, Data Science, AI, and the future makes me curious that how many difficult problems are being solved using AI and Data. 
How people should be educating themselves about the AI bubble and how you should humans be ready by developing the skills that are required in the next-decade like creativity, empathy, and emotional quotient because all these skills cannot be touched by machines. Questions like these would be discussed in this third episode of Life Tech and Beyond with my new guest Jan Belke.
Jan Belke is the Founder and CEO of Data-Driven Science. Data-Driven Science provides training for people building careers in Artificial Intelligence (AI). He has worked for more than 10 years in tech and now started in his own venture. It brings me immense pleasure to connect with Jan today on a podcast session. He is from Silicon Valley and has been working there for quite a lot of time now.
Let's dive right in with the questions to discuss AI, Data, Education, and Building Tech? What is the future of AI and also what are the problems that are associated with AI, and also listen to Jan Belke the founder of Data-Driven Science about his views on Data and AI?

According to you, where we are with AI? and what is the future of AI and Data Science?
Data and AI are 2 sides of the same coin and how they really impact and benefit covid-19 in response?
How Data is leveraged for analytics and what are some very useful use-cases/case-study that are being carried out in the research or application industry?
How privacy is also an issue when dealing with the data that is collected from around the world to solve a problem? How to make sure that privacy is kept intact?
What are some of the exciting innovations in the data and AI space?
What is the type of non-tech skills which AI can't touch should humans be developing in the next decade? (in short What is AI Bubble?)
What kind of unstructured data we are not leveraging up to its full capacity. Where do you see that going into the future? And how can we leverage that data?
Also, we will talk about how technology should be built, and specifically, I want to talk a little bit about the ways that people should be educating themselves about technology?
How do we get into the world of coding?
What are your thoughts on what are the effective ways to build the problem-solving framework to be Data Scientist/ML Engineer/Data Engineer? And how can you apply that problem-solving framework to actually build useful technology solutions?

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