Matt Dancho (Business Science) Profile picture
May 20 10 tweets 5 min read Twitter logo Read on Twitter
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
2. #ScikitLearn: The premier ML toolkit in Python Image
3. #H2O: Blazing speed + AutoML Image
4. #MLFlow: Easy model lifecycle management Image
5. #FastAPI: Incredibly fast + easy APIs in python Image
6. #Streamlit: Simplified data science web apps Image
Ready to learn more AND advance your career with Python?

Then you can't miss this event.

$400 in giveaways that everyone gets for attending live!
What's the next step?

Just join my course waitlist + live launch event here.

I'm super excited!! 😀

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

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More from @mdancho84

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 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
May 17
Becoming a 6-figure data scientist (with #R) in today's economy is different than it was in 2022.

It requires a transformation...

#datascience #career #rstats Image
And those that successfully make the transformation:

1. Get hired 75% faster (3-6 months vs 12+ months)

2. Earn 17% more ($145K vs $117K)

3. Get promoted 2X faster (1-2 years vs 2-4 years)
Want to learn how?

I have a LIVE Masterclass today where I will reveal the exact steps to take.

Strict limit: 500 Seats (and we are over-capacity)
Read 4 tweets
May 16
There are 100,000 data scientists on the market. How can you possibly get a job?

This is one way… 🧵

#datascience #rstats Image
Imagine this.

You walk into the Central Bank of Canada, the backbone of Canada’s financial system.

You’re applying for a data science position.
On paper the odds are stacked against you.

You use R.

The whole team uses Python.

And you are a complete unknown.
Read 10 tweets
May 16
87% of data science projects fail.

One reason is the lack of production.

Here's an easy solution. 🧵

#datascience #python #R #rstats #career Image
This is called an #API (Application Programming Interface). Image
An API allows the user to make requests using a tool they are comfortable with.

The API runs a program that the data scientist has created on the server.

And the API returns a result.
Read 6 tweets

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