Wow! That’s awesome to hear. You’re doing great!
@RobLW I was ok with the “machine learning” 's math part. For Andrew Ng’s course, you may need to review linear algebra and calculus, especially multivariate calculus–which khan’s academy has that course. For Andrew Ng’s course and projects I have finished so far, he focuses more on how to write codes on vectorized algorithm. His course already provides most of execution template of codes, all we need to do is trying to find vectorized mathmatic equations and write in a few lines of codes.
I like to code in Matlab because it is a lot easier to code vectorized equations. But I did see some people who mastered python can write all the codes in Python, including the execution template codes that course provided in the Matlab. I hope by the end of this Dataquest course, I will be able to write everything from Andrew Ng’s course in Python.
Regarding Dataquest, I like its interactive exercises. But I did see some people complaining when going thru further of the course, we may forget a lot of things we learn at the beginning of the course. I like to review individual course simply by reviewing the project I did from that course.
Which part of course covers vectored coded equations?
@alvinctk Andrew Ng’s Machine Learning from Coursera. I only finished first 6 weeks assignment and projects so far. I cannot say more about that course. In his lectures he sometimes wrote vectorized equations during the videos or in his after-video notes. I think he gave most of the cost function or gradient descent, or partial derivative function in the vectorized form.
Haven’t seen folks update their progress in a while, so I’m posting my own! I guess weekly check-in is slowly turning into monthly check-in which is alright with me.
Xinru’s DQ progress:
Data Scientist in Python Path
May 31 2019 – 9 % complete
June 9 2019 – 12% complete
Focus this past week:
SQL Fundamentals - 100% complete
Git and Version Control - 64% complete
As of June 9 2019 8:38h Studying this month
I guess it becomes a monthly check for progress. Hope you don’t mind.
Last month, my DQ progress report from 13% to 28% right now.
Data scientist in Python Path
35 missions completed and close to the end of my 8th project.
I am close to the end of step 2 “data analysis and visualization”.
I guess pandas is the core of python language. This chapter has lots of projects to complete. After I complete all the projects of step 2, I feel more comfortable to claim myself an intermediate-level Python enthusiast.
I spent the whole month of June completing Andrew Ng’s marchine learning course on Coursera. I think after August when I finish all the SQL from DQ, I will start to upload my projects onto Github, polish my resume, and looking for jobs.
By the way, I am curious why you started to learn Dataquest’s courses from ‘Command line’ and ‘SQL’?
I have signed up for Dataquest Premium plans on July 12, 2019.
My progress so far is: 27% of Python Fundamentals course which is really really frustrating for me.
I hope to speed it up from today.
Will post my progress at the end of today.
I wouldn’t sweat it. Enjoy the journey! Savour the little moments of exhilaration each time you’re able to understand and write some code independently that you couldn’t before!
Just commit to getting a handful of courses done each week, and the passage of time will see to it that you get to your destination eventually (inevitably).
Thanks a lot. That is a good dose of motivation. I really needed it.
Wow! All of you guys are pretty smart! I am studying daily for some time now and here’s my progress:
Total on Data Scientist Path: 29%
SQL Fundamentals: 62%
Statistics Fundamentals: 13%
60 hours this month. Man, I am a slow learner!
Good progress Sandesh.Keep it up. You are ahead of me. I wish to catch you up. My overall progress on data scientist path is 5%.
My progress after two days: 3 hours of time spent in the platform. Finishing the 2 python courses in the beginning.5% progress on data scientist path.
So far, I have studied 30 hours in the platform. Completed step 1 and one course in step 2 in the data scientist path.
Keep it up, y’all! Everyone is doing so great! I can only commit to learning on the platform for 1 hour per week — I’m currently on the Functions: Intermediate mission in the Intro to Python course.
I am 10% prepare for my interview. Everyone keep up to good work!
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!
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?
Personally, I started SQL and Statistics before Git too.
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.