My Roadmap to Learn AI

I have been in the Tech world for over a decade. I’ve been a business analyst, scrum master, project manager, management consultant, and a Director of Tech. But the exponential growth of A.I. has made me feel like a beginner again. I have just started to scratch the surface of what that tech has to offer and I’ve realized the importance of staying ahead of the curve in order to stay relevant.

I left my recent role a few months back and I have started my journey to upskill myself on A.I. and M.L.

My ultimate aspiration has always been to be a CIO and I see that a required skill for that role moving forward will be the ability to apply A.I. and M.L. to solve business problems. In the short term, I hope that I get to a point where I can lead an AI/ML team, craft strategic roadmaps, and deliver tools to help businesses grow.

I started this journey a few months ago, but I’ve talked to a few of my old colleagues and friends that wish to make a similar transition. And I thought it would be helpful to document my journey.

This is the highlevel plan for this journey:

1. Hit the Books: Dive into foundational courses on machine learning and data science offered by platforms like Coursera and Udemy. Goal: Master the theory first to build a solid understanding.

2. Get into the Code: Immerse myself in hands-on learning. There are platforms that provide simple environments for experimenting with code and data, allowing you to apply theoretical knowledge to real-world scenarios.

3. Real World Examples: Explore interactive web tools where you can tweak neural networks and observe their behavior visually. This hands-on approach helps build intuition and deepen your understanding of complex AI concepts.