The world of AI is evolving, and so am I.

LangChain, LLMs, Knowledge Graphs, LlamaIndex (I genuinely thought this was a meme when I first heard the name) — these terms are now omnipresent.

It's official: one can't work in any field without encountering AI and LLMs, as evidenced by Google, OpenAI, and Microsoft to name a few. My ultimate goal is not just to bear the title of an AI Engineer but to truly possess its corresponding skills and responsibilities. However, given the current employer-driven market and recent tech layoffs, I realize the importance of expanding my expertise and executing relevant projects.

I intend to embark on a project-based, self-learning journey, primarily using free resources, and will share updates on my progress. Expect two types of posts: daily snippets providing a quick overview of my activities, and more in-depth monthly reports showcasing significant projects, breakthroughs, or even the setbacks and errors I encounter.

From October 2023 to October 2024, I'm dedicating a segment of my day to this venture. At the journey's conclusion, I plan to compile and share these resources for anyone who might find themselves in a similar situation. Wish me luck!

P.S. I'm not expecting to jump from Data Analyst to AI Engineer within a year but to progressively go from Data Analyst to Data Scientist to AI Engineer. What I expect in this year long journey is to have the foundations necessary to get to the next step of becoming an AI Engineer.

Do you have any insights, suggestions, or similar experiences to share? I'd love to hear from you!