Staying Motivated: Check-in Thread to Share DQ Progress

Hi everyone! :blush:

I’ve been using DataQuest for a few weeks now, and recently finding it a bit hard to make
consistent progress self-studying when other things in life start getting in the way.

I think back to when I was the most productive (a while back, around the 3rd year of university): in addition to deadlines, having peers to work towards the same goals together, and compare progress (or the lack thereof :sweat_smile:) was also really important in staying motivated, and making steady progress.

:bulb: If you feel the same and could also use some help to stay on track, I suggest we update our daily or weekly progress together in this thread! (or it could be a thread in another category, where the DQ site moderators decide is more fitting).

It could be like those social media posts of people updating their daily diets or gym workout routines. It could be something short like:

May 19-25: Completed Pandas and Numpy Fundamentals, 6 missions
May 27: Completed Screens 1-7 of 14, Functions: Intermediate Mission

Another advantage to sharing progress is it might be easier to find someone who is working on the same mission, or at a similar pace, as you are, so that sets it up nicely for working together on projects/helping each other with questions!

(And hopefully we can maintain an atmosphere of friendly competition on here - don’t judge others for how much or how little work they did one week - they might have a lot going on in their lives! Steady progress is what counts :wink:)

Let me know what you think about this idea!

I haven’t had much interaction with other DQ learners so far, and I hope this could help improve the learning experience on this platform! :smile:


-----------------------Edited May 31, 10:30PM------------------------------
Xinru’s DQ progress as of May 31:

9% Data Scientist Path (14% Data Analyst Path)
(I’m skipping around on the path a bit, hoping to get to the DS path and start doing ML projects soon because I’m working on my portfolio; also started going to networking events in May as well as a PT job so haven’t spent as much time on this as I hoped :sweat_smile:)

Python for DS: Fundamentals – 70% complete
Pandas and NumPy Fundamentals – 10% complete
Command Line: Beginner – 42% complete
Git and Version Control - 53% complete
SQL Fundamentals - 2% complete

My goal is 10-15 hours/week, hopefully finishing all of the above courses (and maybe start a couple of new ones) in June! Happy learning everyone! :blush:


I really like this idea. I find myself struggling to stay motivated at times too, especially after working a long day. I think having something like this would give me more accountability :slight_smile:

I almost completed the second project.


May 28
Course: Python for Data Science: Fundamentals
Mission: Dictionaries and Frequency Tables
Completed screens: 8, 9
Well said, @floraxinru! This is a great idea and will partake in this :raised_hands:


How’s Ella’s progress?

Thank you @floraxinru. This is a great initiative. I would also share my progress and I think we should ask each other every now and then to see where we are. :slight_smile:


I agree with this idea. My plan is to only do the Python Path, but sometimes it is difficult to keep up the progress. When I a down, it helps that I can visually see, how much tasks I have already successfully finished :slight_smile:


It’s a great idea @floraxinru. You are certainly right that life gets in the way of study :smile:
I assume the best way forward is to just update/edit our own posts on this thread?

Studying: Data Scientist In Python Path
29-05-2019 - 14% complete
05-12-2019 - 15% complete
05-19-2019 - XX% complete
05-26-2019 - XX% complete

**Dashboard stats - studied this month: **
May - 34 hours study time - Python for Data Science: fundamentals 100%, Python for Data Science: Intermediate 100%, Pandas & Numpy Fundamentals 78%
June - 7 hours study time - Pandas & Numpy Fundamentals 100%
July -
August -
September -
October -
November -
December -


im redoing the fundamentals of numpy and pandas onward. im hoping to have my own project with atomic properties data to make visualizations with. starting right at numpy beginning to get pandas and numpy into my muscle memory to feel comfortable with it.


I am working on the course too, I think it’s great!

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That’s a great idea… It’s probably one of the most important and I feel like it’s not sitting as it should. Does doing it a second time help?

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My study process the first time I skimmed through it was flawed now I’m going through with what I think a good understanding of basic python, I need to work on making my own funtions and classes still and to start learning more deeply oop.

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That’s good idea. I’m a construction worker right now and i have to work in the other country. Studying in every free time so I can change my life and come back to my family. Keep going guys!

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That’s some solid progress Rob! And I like your method of an uninterrupted hour each evening in the self-studying post - I’ve been trying that, but need to put my phone in another room.
I’ll be updating/editing my post to share progress also.

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I have finally finished the Data Scientist Path in Python.

Keep up the good work and don’t give up!


Awesome!:clap:t2: How long did it take you to finish it?
I was aiming for 3-4 months but I’m a bit behind schedule now due to job applications

About six weeks + slacked off for a year. 3 weeks (about 150-160 hours) for Data Analyst and 3-4 weeks (about 75 hours) for Data Scientist.

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Hi @floraxinru, This is awesome thread to keep each of us motivated! I just started on the learning path and still feeling pretty fresh on learning new stuff. I will like to hop on the bandwagon and updating my status in this thread as well. :slight_smile:

Path: Data Scientist
05-June-2019 – 16% Complete
14-June-2019 – 26% Complete

Dashboard stats - studied this month
May - 20hours study time

  • Python for Data Science: Fundamentals 100%
  • Python for Data Science: Intermediate 100%

June - 40 hours study time

  • Pandas and NumPy Fundamentals 100%
  • Exploratory Data Visualization 100%
  • Storytelling through Data Visualization 100%
  • Data Cleaning and Analysis 100%
  • Data Cleaning in Python: Advanced 27%

July -
August -
September -
October -
November -
December -

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Hi there,

I started just 2 months ago.
May - 34 hours study time - Python for Data Science: fundamentals 100% , Python for Data Science: Intermediate 100% , Pandas & Numpy Fundamentals 78%
June - 7 hours study time - Pandas & Numpy Fundamentals 100%

I am on the final page of chapter “Numpy and Pandas fundamentals”–the project.
I was a bit slow at the beginning. Never had any experience in coding. I thought I was doing great in individual missions or exercises at first but when it came to projects, especially when there were less line-to-line directions. I kinda got lost and could go any further. So many concepts and syntaxes to digest or master, not easier to start the first project, which was kind of hard. It was not until I finished all the intermediate level of python exercise that I felt a bit comfortable to start working on the first two projects.

I wish Dataquest would talk more about pseudocodes or flowchart for each project before we simply apply some syntaxes there.

I also start Andrew Ng’s neural network course on coursera- week 6. Using matlab to code vectorized equations or math was way easier.

Also I wish there were some offline exercises from dataquest. Right now it is summer, everyday I have to take my kids for summer activities, I wish I could code on my cell phone.


Hi @yoyotooie
You should feedback to Dataquest your experience. Explain to them how you think others who follow a similar route to you would benefit if things were presented in the way you think you might have benefitted from.

I have heard that Andrew Ng’s course is really good. I thought I would wait until I get into machine learning stuff first and learn a bit more of the maths before taking his course. It also gives me time to become more comfortable with my knowledge in Python before I confuse myself by taking a course that uses Matlab to explain it’s concepts.

There has been a number of requests about offline content and mobile apps. I would recommend getting Khan Academy app and working through some of the numerical challenges they offer. I’m sure I’m not the only one here who left school to find I practically never used maths in the working world, until now that is.
Wanting to progress towards data science I’ve found the need to refresh all my basic math understanding and rebuild on statistical knowledge.

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Hi everyone! :smile: I’m new here. So far, it’s great! :slight_smile:

Just signed up for a plan a few hours ago. And I’ve completed my first mission for Python Fundamentals in the Data Scientist track. (7% as of June 6th, 20:33 - Manila Time)

Hoping to put in as much time as I can learning about this stuff. So far, my DQ experience has been more than what I’m expecting. :slight_smile: The concepts being taught is great!

Excited to learn more. :slight_smile: Thank you, DataQuest team! God bless you.