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Data Pipelines basics - the backbone of data apps

6 minute read

Published:

Data is everywhere, like a river flowing into a city. But raw data, like river water, isn’t always ready to use. We need to clean it, process it, and get it where it needs to go so it can be helpful. That’s why data pipelines are important.

An easy to implement AI Voice and Video Agents with Livekit: A Straightforward Approach

6 minute read

Published:

In this blog post, we will discuss the implementation of AI-powered voice and video agents using the Livekit platform. Our experience demonstrates that setting up these agents is a straightforward process, especially with the comprehensive documentation and tutorials available on the Livekit website. We have successfully implemented two versions of these agents: one focused solely on voice interaction and another that incorporates both voice and visual assistance.

Crafting a Standout Data Analyst Portfolio

4 minute read

Published:

A well-constructed portfolio is your golden ticket to showcasing your data analysis skills and landing your dream job. It serves as a window into your expertise, showing potential employers not just what you’ve done but how you think, solve problems, and communicate results. Let’s break down the essential elements of a standout data analyst portfolio and explore how to build one that truly stands out.

Analyzing Manufacturing Data - Cpk and Six Sigma

16 minute read

Published:

I’ve been working in Automotive manufacturing for more then a year now and there is one concept that is holy grail in this industry, and that is Six Sigma. It’s a methodology for achieving near-perfect quality in manufacturing. But how can you could leverage Six Sigma tools right from your Python environment? That’s where the manufacturing package comes in.

Mastering the Art of Data Cleaning

6 minute read

Published:

As data analyst, people often ask me where do I spend most of my work time, besides scrolling through the internet. When people think about data analysis, they often imagine building predictive models or creating dazzling visualizations. But beneath the surface of every successful data project lies an essential yet often underestimated step: data cleaning. This critical process lays the foundation for trustworthy insights, making it one of the most valuable skills for any data professional.

Becoming a Data Scientist in 2024: Roadmap

3 minute read

Published:

As the data landscape continues to evolve in 2024, becoming a data scientist requires a multi-faceted approach, encompassing coding, mathematical proficiency, data analysis, and machine learning. This guide outlines a comprehensive roadmap to becoming a proficient data scientist, integrating essential skills and modern practices such as working with Large Language Models (LLMs) and prompt engineering.

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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.