I've rarely encountered technology that has left me in awe. However, during a recent presentation segment of Nvidia GTC, I found myself repeatedly experiencing those "wow" moments. This realization has brought me to a crossroads. I stand poised to either choose the right path and adapt to the rapid progress of AI or risk being left behind by both the technology and those who have already taken steps to prepare for the future.
Since starting to use ChatGPT roughly three months ago, I've taken some time to reflect on my short-term goals and remap my learning path. Watching the Nvidia GTC keynote solidified my belief that 'To embrace the future is to embrace AI', and I decided to shift my focus toward exploring this inevitable future.
This is what I have been doing:
80% - Studied concepts and fundamentals(Data Structure, Algorithms, Python, Git, ML)Sources: ZTM, Coursera, Udemy, edx, youtube20% - Practiced by building mini programs
Starting today I will transition into the "infrastructure stage":
60% Study concepts and topics20% Learn frameworks, tools and libraries20% Create small Machine Learning Projects to accumulate experience
The plan after the infrastructure stage:
30% - Study concepts related to projects70% - Create projects using GPT4 or possibly 5*And I'll continue to increase the portion of time on projects as I catch up with current technologies and methods.
So,
I predict that the infrastructure stage will take approximately six months to complete. Compared to when I first began learning about computer science, I now have a much better understanding of new information and concepts. I'm ambitious, curious, and excited about what I will be able to achieve within a year.
While I hope to work and learn as a software developer, I understand that I still have much to learn before I can provide significant value to potential employers. Rather than stressing about this, I plan to focus on preparing for the future.
For me, the question has never been about how to get there, but rather when.