There was a time when every new piece of tech felt like a leap into the future. But as the years went by, the thrill of the next smartphone or gadget began to fade. The slap just was not there anymore. Then, AI emerged -- a truly transformative wave of technology that reignited that original spark of excitement.

It was this renewed fascination that propelled me back to academia, pursuing a Master’s in Data Science. As a long-time Database Administrator, immersed daily in the flow and structure of information, diving deep into AI felt like the natural, electrifying next step in my career.

The Mission: AI with Ken

Why this site exists

AI with Ken started as a personal proving ground -- a digital sandbox where I could practice building models, wrangling data, and applying what I was learning. My chosen arena? Stock trading. My track record with manual trading was less than stellar. Every buy felt like a gamble. I figured: maybe I can math my way out of this, remove the emotion, and engineer a more logical approach.

This site is the evolution of that idea. It is where I share experiments, the models I develop, and the lessons learned (both successes and failures) in applying data science to the complexities of the market. My goals: to demystify data concepts and AI techniques for anyone interested, and to explore, transparently, whether we can leverage these tools to make smarter, less emotional trading decisions. If the bot helps us all identify better opportunities along the way, that is a win.

The Philosophy

One of the most compelling aspects of AI in trading is its potential to strip away the human element that so often derails us: bias and emotional impulse. We have all been there -- the fear of missing out, the panic sell, the gut feeling that overrides sound judgment.

I believe AI, when thoughtfully applied, can serve as a powerful analytical lens, helping us see patterns and make decisions based on data-driven insights rather than fleeting feelings. It is about augmenting our intelligence, not replacing it, to navigate the markets with greater clarity.

The Arsenal

Building effective AI, especially in finance, demands a solid data foundation. My journey as a Database Administrator has equipped me with a deep understanding of data’s lifecycle, which is crucial for crafting reliable AI systems. This experience translates directly into:

  • Data integrity and governance: quality, consistency, and security of the datasets models consume.
  • Performance optimization: tuning data retrieval and processing pipelines for training and inference.
  • Complex data modeling: structuring relationships that drive feature engineering.
  • ETL/ELT expertise: moving data from diverse sources into usable shapes.

My technical toolkit for AI with Ken leverages these foundations and extends into specialized AI development:

  • Languages and logic: Python, PowerShell
  • Database and data platforms: SQL Server, MySQL, Oracle, PostgreSQL, Azure SQL Database, Azure Data Factory
  • Cloud and big data: Azure, AWS, Azure Databricks
  • Visualization: PowerBI

Current focus: refining predictive models with time-series techniques and continuously backtesting algorithmic strategies for robustness.