Thread by @thedataprof

Here’s a cartoon illustration I’ve drawn a while back:
The #machinelearning learning curve

👀🧵👇 See thread below

2/ Starting the learning journey
The hardest part of learning data science is taking that first step to actually start the journey.

3/ Consistency and Accountability
After taking that first step, it may be challenging to maintain the consistency needed to push through with the learning process. And that’s where accountability steps in.

4/ 66 Days of Data
Luckily we have the #66daysofdata by @KenJee_DS that helps us to maintain public accountability. As Ken puts it, you just need to:
-Learn or do #datascience for at least 5 minutes a day
-Tweet or post your progress on social media

5/ Overthinking (Analysis Paralysis)
Sometimes we are overwhelmed with the possibilities and this leads to indecisiveness.

Does this sound familiar?
- R or Python?
- Google or IBM professional certificate in data analytics/data science

6/ Solution to Overthinking

Choose 1 and move on. You can always circle back and give the other a try later on.

7/ Videos I’ve made on:

R vs Python


Google Data Analytics Professional Certificate

8/ Blogs I’ve written on getting started with #datascience

Data science starter kit
towardsdatascience.com/data-science-s…

Learning data science in 10 steps
towardsdatascience.com/10-things-i-wi…

Strategies for learning data science
towardsdatascience.com/strategies-for…

9/ Blogs I’ve written on building machine learning models

How to build your first machine learning model in Python
towardsdatascience.com/how-to-build-y…

How to build an AutoML app in Python
towardsdatascience.com/how-to-build-a…

How to use machine learning for drug discovery
towardsdatascience.com/how-to-use-mac…