Machine Learning Fundamentals Literacy

Growing as a data scientist has many facets, one of which is staying in tune with #machinelearning literacy, and even includes mundane activities such as reminders of the very basic and fundamentals.

Through Women In Data, I decided to group together with the #datacamp learners to do a track from DataCamp called “Understanding Data Topics”, part of my goal to be actively engaged in maintaining a data literacy mindset.

Some of you may know (from following my 1 data camp course per day last year) that I am a pretty big fan of DataCamp, and I believe it has a lot of benefits in terms of learning.  

I have completed:
✨ 7 learning Tracks
– Python Fundamentals
– Importing & Cleaning Data
– Data Manipulation
– Machine Learning Fundamentals
– Data Scientist with Python
– Data Analyst with Python
– Machine Learning Scientist with Python
✨ This all includes about 58 courses

🎯 This year, I want to keep learning on DataCamp, primarily data literacy courses for becoming and staying well rounded.

🎯 But something I am super excited about also, is taking some projects (guided and unguided) and challenging my creativity in building more items for my portfolio.

Exciting stuff!

Enjoy some of the notes I put together in a presentation, on the concepts I learned and that I find important from the data literacy course on machine learning from the track “Understanding Data Topics”.

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