Data Analytics

Image by Author   When I first started learning about how data science and machine learning could be used outside of finance and marketing, healthcare immediately stood out to me. Not just because it’s a massive industry, but because it literally deals with life and death. That’s when I stumbled into something that kept…

Image by Author   In today’s fast-evolving tech landscape, mastering frontend development is more important than ever. While AI can help automate parts of the coding process, building a polished, user-friendly web application still requires a solid understanding of frontend fundamentals. Many experienced developers find that relying solely on AI models like Claude 4…

Image by Author | Canva   #  Introduction   Traditional debugging with print() or logging works, but it’s slow and clunky with LLMs. Phoenix provides a timeline view of every step, prompt, and response inspection, error detection with retries, visibility into latency and costs, and a complete visual understanding of your app. Phoenix by Arize…

Image by Editor | ChatGPT   #  Introduction   NotebookLM is a powerful AI tool launched by Google. It is designed to augment analytical capabilities through advanced natural language processing and insightful summarizations. One of its most fascinating applications is the ability to generate insights, summaries, and even audio overviews from documents. While NotebookLM does…

Image by Author | Canva   It’s not necessary to go into debt if you want to master Python. Many online courses are free. When researching for this article, I was honestly surprised by the quality and the choice of free online Python courses. These are my recommendations.     #  1. Python Full…

Image by Author | Canva   Python is widely known for its popularity among engineers and data scientists, but it’s also a favorite choice for web developers. In fact, many developers prefer Python over JavaScript for building web applications because of its simple syntax, readability, and the vast ecosystem of powerful frameworks and tools…

Image by Author | Canva   Despite the rapid advancements in data science, many universities and institutions still rely heavily on tools like Excel and SPSS for statistical analysis and reporting. While these platforms have served their purpose for decades, sticking solely to them means missing out on the simplicity, power, and flexibility that…

Sponsored Content       The landscape of big data analytics is constantly evolving, with organizations seeking more flexible, scalable, and cost-effective ways to manage and analyze vast amounts of data. This pursuit has led to the rise of the data lakehouse paradigm, which combines the low-cost storage and flexibility of data lakes with…