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Matt Dancho (Business Science) Profile picture
@mdancho84
May 20, 2023 • 7 tweets • 5 min read • Read on X
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As a data scientist, productivity is a 10X super power.

Here's a short list of AI tools to help data scientists with: 🧵

#ai #datascience #career #skills #tools Image
1. Writing code

AI pair programming is a huge benefit.

Tools like #chatgpt & github #copilot can help debug complex code and replace Googling + Stack Overflowing for common scripting.

Key skill: ChatGPT prompting (more on this in my free ChatGPT for Data Scientists) Image
2. Code Quality & Documentation

Great products have great documentation. AI can help produce documentation, comment code, and replace time-consuming manual documentation with automated AI docs.

Key Skill: Using @mintlify to build your docs: mintlify.com Image
3. Presentations

Great data scientists are storytellers. Use persuasion to your advantage.

Key Skill: Generating images with AI using @midjourney_ai . midjourney.com Image
I'm road-testing all of these.

And I've been quietly researching #ChatGPT for Data Scientists (My NUMBER 1 TOOL) for the past 4 months.

I have good news - I'm ready to reveal my chatgpt research!
If you want to understand how ChatGPT can make you a better data scientist (and mistakes to avoid)...

I'll be sharing my research in a Free WORKSHOP: ChatGPT for Data Scientists (Wednesday, June 7th)!
What's Your Next Step?

Join me and 1,000 data scientists as we crush AI in my LIVE ChatGPT for Data Scientists Workshop.

Seats are limited (1,000 max).

👉Register Here: us02web.zoom.us/webinar/regist… Image

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More from @mdancho84

Matt Dancho (Business Science) Profile picture
Apr 15
These 7 statistical analysis concepts have helped me as an AI Data Scientist.

Let's go: 🧵 Image
Step 1: Learn These Descriptive Statistics

Mean, median, mode, variance, standard deviation. Used to summarize data and spot variability. These are key for any data scientist to understand what’s in front of them in their data sets. Image
2. Learn Probability

Know your distributions (Normal, Binomial) & Bayes’ Theorem. The backbone of modeling and reasoning under uncertainty. Central Limit Theorem is a must too. Image
Read 9 tweets
Matt Dancho (Business Science) Profile picture
Apr 7
🚨 BREAKING: Microsoft launches a free Python library that converts ANY document to Markdown

Introducing Markitdown. Let me explain. 🧵 Image
1. Document Parsing Pipelines

MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. Image
2. Supported Documents

MarkItDown supports:

- PDF
- PowerPoint
- Word
- Excel
- Images (EXIF metadata and OCR)
- Audio (EXIF metadata and speech transcription)
- HTML
- Text-based formats (CSV, JSON, XML)
- ZIP files (iterates over contents)
- Youtube URLs
- EPubs Image
Read 7 tweets
Matt Dancho (Business Science) Profile picture
Apr 2
RIP document extractors.

Google just released LangExtract: Open-source. Free. Better than $100K enterprise tools.

Here’s what it does: 🧵 Image
What it does:

→ Extracts structured data from messy text
→ Grounds every field to the exact source location
→ Handles 100+ page docs
→ Generates interactive HTML for verification
→ Works with Gemini + local models Image
What it replaces:

→ Regex/fragile parsing
→ Custom NER pipelines
→ Expensive extraction APIs
→ Manual data entry Image
Read 8 tweets
Matt Dancho (Business Science) Profile picture
Mar 31
Data science killed itself.

Not because AI showed up. Because too much of the field confused running a model with understanding one. Image
For years, data science rewarded people for producing outputs:

A model score
A dashboard
A notebook
A prediction
A nice chart

And a lot of that work looked impressive.
But underneath it, there was a problem:

No understanding of the business value (or lack of) it generated.
Read 7 tweets
Matt Dancho (Business Science) Profile picture
Mar 22
Someone built a free 7-week RAG curriculum on GitHub.

And they're right — it's good.

But, you'll need 1 more thing to get an AI/DS job in 2026: Image
Docker. FastAPI. PostgreSQL. OpenSearch. Airflow. Hybrid search. LangGraph. Production monitoring.

That's a serious architecture. Bookmark it. github.com/jamwithai/prod…
But here's what I've watched happen with 7,500 students over 8 years:

The ones who followed curricula stayed in tutorial purgatory.

The ones who built one real system — in front of a live instructor, with a deadline, with someone watching — shipped.
Read 8 tweets
Matt Dancho (Business Science) Profile picture
Mar 17
OpenAI, Google, and Anthropic just published guides on:

• Prompt engineering
• Building agents
• AI in business
• 601 AI use cases

9 of the best guides you can't miss: Image
1. AI in the Enterprise by OpenAI

Grab the PDF: cdn.openai.com/business-guide…Image
2. A practical guide to building agents by OpenAI

Download here: cdn.openai.com/business-guide…
Read 13 tweets

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