• Product Team changed their schema without notifying you which lead to your pipelines/serving breaking!?
• Tired of messy json data that have no form or structure and hitting your kafka/pubsub Stream?
• Want to make sure data types and fields are consistent when you are recieving or sending API responses?

• Documentation is always a afterthought? Multiple variables and objects to keep track of?
• Data Scientist code is so hard to read and collaborate! It is all over the place!
• Having difficulty to validate data from other parties or databases?

• Hear good things about docker but not sure where to get started?
• Docker tutorials out there not useful as a data scientist / analyst?
• Developing within docker environment! (Remote IDE)

• Introduction to docker compose!
• Want to mock your environment with a database?
• Running an interactive environment micking production workflow?

• What is the deal with testing? How do you even test data?
• Testing is only for software engineers! I am a data scientist!
• How should a data scientist view testing?

• What is this conftest.py and pytest.ini that I see in repositaries?
• How to share fixtures across multiple scripts?
• (Slightly) advance topics with fixtures on scoping and autouse.

• Have external dependencies / requests? But tests should be isolated!
• What about complicated functions that take a significant long time to run?
• How do I check my end to end flow is correct?

• Data Build Tool (DBT) by fish town analytics!
• Having difficulty in managing SQL scripts? Too many tested Query? Or figuring the execution graph? Finding yourself running scripts manually?
• How do you even do testing for ETL jobs or Queries!?!?

• Write better pandas code as a data scientist so that your engineer will love you! (Or easier to productionize your code)
• Frustrated by constant reassignment and/or hard referencing when creating new columns with pandas.
• Like spark Dataframe API or R's Dplyr API or chaining / piping your code in general? (Some sort of functional programming)

• Storing steps/procedures in README(s)? Keep copy and pasting commands to run?
• Forgot your commands when revisiting your projects months ago?
• Wish to hand over projects / commands / procedures to your team mates easily?

• Dealing with latency when trying to make multiple web/DB requests or building your API product?
• Trying to understand what is ASYNCIO?
• Useful to understand if you are going to develop data products with FASTAPI.

• Getting started with metrics?
• Having difficulty remembering metrics?
• Sensitivity, power, recall, precision, ....

• Data Science is not only about Machine Learning!
• Interested to know more about a/b testing?
• Understanding p-value, power, sample size.

• Quick overview of the common distributions!
• Various use cases of each distributions
• How are distributions related to one another.

• For those who are curious about what tools I use.
• How i set up my machine.

• My personal pitfalls and avoid my mistakes.
• How do I decide what to learn?
• How do I stay motivated?

Useful resources I personally used

• Resources I have used in the past
• Such as ML/NN to Programming languages etc
• To be expanded!

• An hour long podcast on how I got started in my career.
• How did i make the switch from a "dashboard data scientist" to putting models in production.
• And other questions such as Python or R?