I just revealed the data science project that helped my small business generate $3,500,000 in revenue in the last 2 years.

Here are the juicy details...

#datascience #python #rstats #career Image
It's true. My company did almost $2,000,000 last year with an email list size of under 100,000.

And a big part of it was the Marketing Analytics that I'm revealing in my new Python course.

What did we do?
We used machine learning to score leads.

We then created nature vs sales targeting segments.

Then we did this...
Marketing would target:

1. Sales Segment:

This segment received sales email with our core $2000 product

2. Nurture Segment:

This segment was requested to take actions like attending free webinars that increase their lead score.
Bada Bing, Bada Boom... 2X sales boost.

And the key was not targeting until the prospect was ready...
Want to learn more?

I have a 5-minute youtube video that explains in-depth how the data science lead-scoring project works.

And if you like what you saw in the Youtube video, then...

Next Step?

Attend my course launch event where I detail the steps taken to make the project.

- What tools
- Where I used them
- How to apply Machine Learning
- How to stand up the API
- And the perfect job portfolio project

Register Here: learn.business-science.io/python-ml-apis…

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More from @mdancho84

May 26
ChatGPT just made a Data Science Web App for me in under 15 minutes.

Here's the story. 🧵

#datascience #rstats Image
1. Machine Learning

ChatGPT created the basic code for an XGBoost Machine Learning model

The model is used for scoring the customer spend
2. Shiny App

ChatGPT produced the code for a basic shiny app that packages the model...

...And the app can make new spend predictions based on tweaking inputs for a new customer.
Read 11 tweets
May 25
R users that want to learn Python.

This message is for you. 🧵

#rstats #python Image
If you don't know me, I'm Matt.

I'm an R user.

Nice to meet you...
And, I'm super pumped for today...

GOOD NEWS: My Python Course Launch is happening today at 2PM EST

BAD NEWS: It's officially over-registered. 4,872 registered. But ONLY 1000 get seats.

Here's what you need to do...
Read 5 tweets
May 20
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
Read 7 tweets
May 20
BIG ANNOUNCEMENT: I'm beyond excited to announce that in 5 days, I'm launching my brand new course- The #Python for Machine Learning & API's Course.

This course will transform your #career.

Here's what's inside... 🧵

#datascience #course Image
This launch marks the culmination of 2 years of research...

It covers The 6 Top #Python libraries for machine learning and production:
1. #Pycaret: Low-code machine learning Image
Read 10 tweets
May 18
Over the past 3 years, I've been writing Python code daily.

And this coming Thursday, I'm excited to share what I've learned. 🧵

#datascience #career #python #rstats Image
Most of you know me as an #R guy. And I 1000% love R. ❤️

But I've also grown over the past 10+ years that I've been practicing data science as a data scientist, as a consultant, and as an educator.
What I've come to realize is that no one language is perfect.

Each has its strengths. And weaknesses.

And more often than not we get caught up in debating things that **don't** really matter...

Like R vs Python.
Read 11 tweets
May 18
There are more than 10,685,000 people learning to work with data.

Yet most data science jobs now have over 1000+ applicants.

And only 5 actually make it to an interview.

Learn these 4 skills to stand out (free to steal & use to advance your career).

#datascience #rstats Image
1. Time series analysis

Up to 90% of companies need better forecasting.

And less than 5% of data scientists are competent in time series analysis.
Key Point:

Becoming good at time series is a massive advantage that automatically places you in the 95th percentile of applicants.

Try This:

Demonstrate an application of time series analysis in the interview, and set yourself apart from the crowd.
Read 13 tweets

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