search

DaedalusDreamJournal / datascienceroadmap

repository of links, video and other stuff related to the #66daysofdatachallenge
Creative Commons Zero v1.0 Universal
4 stars 7 forks source link

Topic ordering issue #11

Open vedanthv opened 3 years ago

vedanthv commented 3 years ago

This is a discussion for topic ordering for the roadmap. Link to Google Docs: https://docs.google.com/document/d/1WN35mSfNXLQc6Dbg-V3GCWIpfgipyyEWHcHVcXngvB0/edit

vedanthv commented 3 years ago

@DaedalusDreamJournal Are you good with the ordering? Any changes needed?

DaedalusDreamJournal commented 3 years ago

all right, did have a look at you google doc file, so far so good and the order make logical sense. That being said, as I've mentioned in the chat, it would be good to make sure the early part of the roadmaps include practice for beginner on theoretical subjects -> like matplotlib for stats. What do you think?

vedanthv commented 3 years ago

At 4. I have included the stats playlist which is easy to follow. Then at 5.I have included matplotlib and seaborn At 6. There is linear algebra which is important for ML and DL and not so imp for Viz. I guess it is in perfect order.

vedanthv commented 3 years ago

My take on the roadmap: Let us divide the roadmap/curriculum into three sections:

  1. Data Analyst
  2. Data Scientist
  3. Data Engineer Each section will have its own set of topics and we can divide that into three sections:
  4. Beginner
  5. Intermidiate
  6. Advanced The learner can gauge where he/she stands and then choose the stage to start with The Data Analyst role will have less number of sections(less things to study for this role) followed by Data Engineer and Data Scientist. After completing the Data Analyst path(which is going to be the first one) he/she can gauge whether to proceed to Data Scientist or Data Engineer part of the roadmap The Data Engineer Path will have a few more courses than the Data Analyst path like Pipelines and the Data Scientist path will have all the content from Data Analyst and Data Scientist Path but excluding a few things like Tableau and PowerBI.