Staying Motivated: Check-in Thread to Share DQ Progress

Good luck!!

For anyone else with an interview in the near future, remember that we have a fairly lengthy blog post with very useful sample questions, and a bunch of other helpful tips!

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Hello @floraxinru! I am glad you posted about motivation. I will also keep updating my comment once a week. If I forget to update once a week, please, anyone reading this, let me know by mentioning or replying here.


Started on 7/17/2019. Spending at least 2 hours daily.

My progress status as of 9/14/2019:

Data Scientist in Python Path: 42% complete.
Step 1 - Python Introduction: 100% complete.
Step 2 - Data Analysis and Visualization: 100% complete.
Step 3 - The command line: 3% complete.
Step 4 - Working with Data Sources (SQL): 100% complete.


My tips on learning: I am not rushing but taking my time to learn the material from the beginning. In order to retain what I learned, I am taking notes on a word file, which is currently more than 120 pages. Additionally, I am creating my own flashcards for new concepts and python functions/methods with AnkiDroid app. In the morning I will open my flashcards and try to recall each of them. This way I won’t forget everything in the long term.
Solving problems with Python is very important to understand how each function/method works. So I also try to solve one programming problem from codewars.com every day. At the end of the day, it is important to remember that learning should be fun. Therefore, I do not try to complete 3-4 missions in a day.


Question for the reader who has completed more than I did:
I see that after step 2, each step is about different topics. I was planning on finishing the steps in sequential order. Do you recommend I keep my plan that way or can I start SQL or Git steps separately?
Thanks!

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Personally, I started SQL and Statistics before Git too.

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Same! I think I will be done with Stats this week. Will start SQL after that.

@saidakbarp Thank you for your learning tips. I love the flashcard.

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@saidakbarp thanks for the flash card tip! Wish I would’ve started earlier. I’ve been keeping a mix of a google doc with notes and a physical notebook. Sometimes physically writing helps me flush out ideas when I get stuck.

I will update this post as well to keep me on track. Like many of you I’ve found my motivation waxing and waning. The hardest for me is when I can’t/don’t work on it much for a while and it’s harder to come back because I’ve lost momentum and it takes so much longer to remember what I last learned. I would also welcome being reminded if I haven’t update this post once a week by commenting here. Let’s do this!

Status on 2019/9/3:

Data Scientist in Python Path: 17% complete
Step 1 - Python Introduction: 100% complete
Step 2 - Data Analysis and Visualization: 37% complete

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I think this is a great idea! Right now my status on DQ Data Science with Python Path

step 1 - Python Introduction 100% complete
step 2 - Data Analysis and Visualization 78% complete

I’m guilty of rushing thru the missions and not taking enough time to review material before moving on. Been taking detailed notes as I go in OneNote but they are 121 pages long! A lot of that is screenshots.

My immediate goal is to finish the last mission in course 5 step 2 and then review everything before starting the Data Cleaning Project Walkthru mission. Then I hope to get one of the guided projects worked up to the point I can feel good about putting it out there on Github.

I think I’m going to finish step 4 or 5 and then apply for jobs while continuing the course at a slower pace. Ideally it would be better to finish the whole course first, but not sure I can wait that long.

Other study:

Udemy
Data Science A-Z 100% complete (great course!)
Tableau A-Z 100% complete
Python for Statistical Analysis 0% complete
Modern Python 3 Bootcamp 0% complete

planning to take the Python for Statistics course at the same time as the DQ step 5. Sometimes its nice to just watch videos for awhile :slight_smile: the Data Science A-Z course is what convinced me to switch to Data Science as a career path.

The idea behind the bootcamp course is it would be fun to learn how to write actual applications in python. Not sure when I will have time to start this.

Code Signal Arcade
intro 100% complete (Javascript, what was I thinking?)
database 100% complete (love SQL!)
python 16% complete

I will try to finish the python section, but no rush. Just do a problem here and there as a change of pace.

Good luck with your studies everyone!

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Hello everyone! It looks like I cannot edit my comment more than 7 times. So, I will be posting my progress in this comment.
I will also keep updating my comment once a week. If I forget to update once a week, please, anyone reading this, let me know by mentioning or replying here.

Started on 7/17/2019. Spending at least 2-4 hours daily.

My progress status as of 10/19/2019:

Data Scientist in Python Path: 53% complete .
Step 1 - Python Introduction: 100% complete.
Step 2 - Data Analysis and Visualization: 100% complete.
Step 3 - The Command Line: 100% complete.
Step 4 - Working with Data Sources (SQL): 100% complete.
Step 5 - Probability and Statistics: 57% complete.
(UPDATE: It was hard to progress for the last month because of life problems I was facing. I am back in track again!)

My tips on learning : I am not rushing but taking my time to learn the material from the beginning. In order to retain what I learned, I am taking notes on a word file, which is currently more than 135 pages. Additionally, I am creating my own flashcards for new concepts and python functions/methods with AnkiDroid app. In the morning I will open my flashcards and try to recall each of them. This way I won’t forget everything in the long term.
Solving problems with Python is very important to understand how each function/method works. So I also try to solve one programming problem from codewars.com every day. At the end of the day, it is important to remember that learning should be fun. Therefore, I do not try to complete 3-4 missions in a day.

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Hi there,

i am in the Data Scientist Path

Data Analysis and Visualization - 5% complete

think this is great to keep me motivated. but i think i will bust the 6 - 8 months recommended duration to complete DS path :sweat_smile:

@saidakbarp Great Progress. I was bit off track and frustrated due to some missions or project I had no idea where they came from and had to constantly check the solution first. Maybe because we start to learn deeper and broader, it is hard to constantly remember all the syntaxes or the steps how to start with a certain problem. It is like a process of connecting all the dots together. I love codewars and I am kinda addicted to it. In the last two weeks, I’ve finished almost 100 katas. Thank you for the recommendation. Before I tried codewars, I was not confident at all how to even write a function. I could not tell the difference between while, if, for loop, and else clause on loop statement etc. I don’t think DQ has covered much on flow control in Python. Trying codewars certainly helps me to think about how to solve the problem before I even start coding.

Also I have not touched base with my SQL for over one month and now I feel like I forget everything about SQL. Yesterday I started to program with SQL kata in codewars.

At this point, I think I need to redo some of the projects to reinforce some of the concepts. Most “real world” projects aren’t bite-sized tasks like codewars’ kata I can solve with a single function or algorithm. But codewar is still good place to sharpen my coding skill and algorithmic thinking skill.

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Hello everyone! It looks like I cannot edit my previous comment. So, I will be posting my progress in this new comment.
I will also keep updating my comment once a week. If I forget to update once a week, please, anyone reading this, let me know by mentioning or replying here.

Started on 7/17/2019. Spending at least 2-4 hours daily. Doing it when I have free time.

My progress status as of 11/18/2019:

Data Scientist in Python Path: 65% complete .
Step 1 - Python Introduction: 100% complete.
Step 2 - Data Analysis and Visualization: 100% complete.
Step 3 - The Command Line: 100% complete.
Step 4 - Working with Data Sources (SQL): 100% complete.
Step 5 - Probability and Statistics: 100% complete.
Step 6 - Machine Learning intro: 36% complete.
Step 7 - ML intermediate: –
Step 8 - Advanced Topics: –
(UPDATE: It was hard to progress for the last month because of life problems I was facing. I am back in track again!)

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Hello everyone! I just want to quickly update my progress and I might slow down my progress because of my job. As of December 15, I have completed 67% of the course.
I stopped progressing a month ago because I started applying for jobs and finally landed a data analyst job. As a data analyst, I am primarily using SQL and Tableau for reporting.
I am still planning on finishing this bootcamp but it might take bit longer than usual. For your reference, I spent 4 months with one time 3-week-break to complete 67% of the bootcamp. When I started I had tons of motivation and it wore off when I reached 40%. Then I took a 3-week-break which helped me regain my motivation and I was able continue. I will be continuing my journey but it is not going to be as intensive as it was before. Additionally, I am planning on reading and practicing with Aurelien Geron’s ML book. I recommend you, guys, as well to read that book!
Cheers!

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hey @saidakbarp!
Congratulations! It’s a great news! I am highly motivated after go through your post. I am about 36% of the data science path spending 2 months along with my undergrad degree.
I am also reading the book you mentioned. It’s a great one.
Best of luck for your new job!

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I take notes on a doc file too! Something else that I do is whenever I encounter a term or topic that is Greek to me is to Google it real quick, then save that as a bookmark so I can come back to it later in the day. This way, I can continue concentrating on whatever mission I’m currently on and don’t get distracted by the small stuff. :slight_smile:

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I like the idea around this post. It’s not been active, so I will try to jump-start it hopefully.

Current Path: Data Analyst
Start Month: End of March
Time Spent Past Week: ~4.5 hours
Time Spent this Month: ~25.5 hours
Current Step Completed: 53%
Total Steps Completed: 3
Percentage Completed: 63%
Total Time Spent: ~108.5 Hours

I will aim to reply with an update on my progress every week (on Sundays, likely) to hold myself more accountable.

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After a long break, I started learning on DQ again. The last time I checked-in was in December 2019 with 67% completion rate on Data Science in Python track. Since then lots of events happened: I applied for jobs and got accepted as a data analyst; 2020 arrived with the pandemic and protests. It has been a roller-coaster so far. Nonetheless, I am continuing my learning journey.
I resumed my DQ progress on June 8, 2020. Since I am working a full-time job, I am waking up early in the morning (~6am), and studying for 2-3 hours every day. I am still taking notes on google docs and it is now more than 250 pages long. It has been little over a month since I resumed and I am currently at 91% to the course completion (Step 8). Within a month I progressed on 24% of the course. I am in the last step (step 8) and last step is 50% complete. It has been an incredible amount of learning, note taking and problem solving. From a job perspective, I understood that you do not need to know everything; you need to have a foundation and problem-solving skills. I am expecting to complete the Data Science track by the end of this month.
Happy learning!
Said

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Another slow week for me, but it’s still progress!

Current Path: Data Analyst
Start Month: End of March
Time Spent Past Week: ~3.5 hours
Time Spent this Month: ~33 hours
Current Step Completed: 63%
Total Steps Completed: 3
Percentage Completed: 65%
Total Time Spent: ~112 Hours

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Finally today is the day to celebrate - I completed 100% of the course. By the way, I just noticed that the path I took was ‘Data Scientist In Python’ not ‘Data Science in Python’ :smile: I just started looking around and notice these small details. I will post a detailed review of how I studied in a separate post when I get free time.
Anyways, in short, these are some stats on my learning and feedback:

Path: Data Scientist in Python
Total Hours Spent: 255 hours
Total pages of note-taking on gdoc: 270 pages
DQ Courses taken: 36
Start date: 7/19/2019
Course paused dates: 11/21/2019-6/12/2020 (204 days or ~7 months)
End Date: 8/1/2020
Total days spent studying (excluding the long pause period but including short 1-2 week breaks): 125+51=176 days (~6 months)
Satisfaction level with the course: Very Satisfied (covers most of the DS concepts and foundation for continuing into advanced courses)
Explanation level: Excellent explanation of materials (does not go deep into details but gives a very solid foundation to pick up advanced materials independently)
Platform usability: Needs some improvements on the GUI and terminal. Sometimes codes fail or run slow. Other than that the platform is great.
Community support: Great. The community channel is active and very responsive.
Overall Impression: Would recommend to a friend. I liked the way they structured the course focusing on highly demanded DS skills.

This is not the end of learning. This is the start. I will continue studying by taking Andrew Ng’s Machine Learning and Deep Learning courses. I am sure they will take over 300 hours. But as long as I am progressing, I will reach what I aimed for. Whoever reading this, believe in your ability and trust the process. You can do it even when you have a very busy life (I studied while having a full-time 9-5 job). Remember: Slow and steady wins the race. Never compare yourself to someone else; compare yourself to who you were yesterday. This way you will be able to progress.
Happy Learning!
Said

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This week’s progress

Current Path: Data Analyst
Start Month: End of March
Time Spent Past Week: ~6.5 hours
Time Spent in July: ~20 hours
Current Step Completed: 83%
Total Steps Completed: 3
Percentage Completed: 69%
Total Time Spent: ~119 Hours

And congrats to @saidakbarp for completing the Data Science Path! :man_technologist: :man_scientist: :tada:

This week’s progress

Current Path: Data Analyst
Start Month: End of March
Time Spent Past Week: ~8 hours
Time Spent this Month: ~14 hours
Current Step Completed: 93%
Total Steps Completed: 3
Percentage Completed: 72%
Total Time Spent: ~127 Hours