Python for Data Science and Machine Learning Bootcamp
Are you ready to start your path to becoming a Data Scientist.
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Reddit Posts and Comments
0 posts • 31 mentions • top 30 shown below
2 points • dafrdman
I was an econ major in college and realized I wanted to get into ML. The first thing I did was learn basic Python and it sounds like you have that down. My next step was to take this class, which covers Python for machine learning. That class gives you an intuitive sense of the models commonly used in ML and the technical tools to use them. The next step for me was to work on some independent projects so I had something to discuss in interviews. Hope that helps!
1 points • smthhapp
Anyone did this one - https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/?fbclid=IwAR2OswXgIzxWOXo-29h6J_d-1Zv1flrbSU_1keXbzOZS2_6TUKlsb-2wk-Y&moon=tethys&utm_campaign=ROW-FB-DRT-Visitor-Evergreen-ROW-Smartly-EN-ROW_.ci__._sl_ROW.vi__._sd_All.la_EN.&utm_content=.pd_903744.&utm_medium=udemyads&utm_source=facebook&utm_term=.ag_row_3_day_visitors.ad_6176820004688._ ?
1 points • mulutavcocktail
Best money I spent was taking this inexpensive class
Nothing comes close. People can give you suggestions but without any real world problems and putting it all together you are wasting your time.
1 points • Kaze_Senshi
1 points • pekkhum
May I interest you in Python for Data Science and Machine Learning Bootcamp?
1 points • MadeForBF3Discussion
This was the one she suggested: https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/learn/lecture/5733186?start=0#overview
2 points • rotterdamn8
It depends on what exactly you want to do, but for general learning, I took a couple of this guy's courses, which I thought were useful:
3 points • jixistix
I started with a python for data science course on Udemy, it requires some very beginner knowledge of python so if you've ever taken an intro to python course then you should be good to take this one, it does also have a "python crash course" section at the beginning. Also Udemy courses tend to go on sale a lot so check back often if you'd prefer to pay less:
I also use Zeal to quickly look up a term from any of my downloaded dictionaries (numpy, pandas, matplotlib etc.). It's good for people who have slow/ no internet, as once it's downloaded, it can be used offline.
Once you've gotten a handle on a few of the concepts, I encourage you to create a Kaggle account, find a dataset related to your field, and practice doing some analysis on it! It's also a great way to start a portfolio and gain some constructive criticism.
1 points • nrmxndal
i heard that was a good one, but i used udemy.
1 points • chris1666
Hmmm, practice, practice, practice
1 points • Scutterbum
Have you tried any Udemy courses? Don't expect masters level, but it's good for getting the hang of Data science techniques.
1 points • xdonvanx
That's going to take some time. You should take your time and learn the basics, for the Data Science part it's going to take a bit of time since it's very Math heavy so understanding the Math will come in handy.
This youtube channel teaches you the basics: Corey Schafer
This udemy course teaches you the basics of Data Science : Udemy Course
1 points • weareglenn
This is a great Udemy course on Data Science topics such as pandas, numpy, matplotlib, seaborn and scikit-learn: https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
1 points • vb2345
This is a good place to start if you are a beginner.
1 points • rolltide_130
Yeah they're great! I'm getting one moreso for my hobby but I might eventually use it to pick up a side hustle as a land surveyor (I work for a GIS software dev company that doesn't actually do any of the actual hard GIS work - it's backend software stuff)
Also I suggest picking up two courses from Udemy. The Complete Python Bootcamp course: https://www.udemy.com/course/complete-python-bootcamp/
And the Python for Data Science and Machine Learning Course: https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
Both of these will give you a really good head start, and you can probably plow though both of these courses in a couple weeks if you sit down and really focus.
2 points • carhawk95
Which course should I choose?
Hi guys, first time posting and the english is not my mother tounge, so sorry in case of any mistake. I really wanto to get into ML, and I'd like to purchase a Udemy course taking advantage of the discounts, however I'm between two possiblities and I don't know which one could be better for me, the courses are:
Machine Learning A-Z™: Hands-On Python & R In Data Science (https://www.udemy.com/course/machinelearning/)
Python for Data Science and Machine Learning Bootcamp (https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/)
I'd really appreciate any advice or help
1 points • Logical-Win
It appears Udemy does have a sale ending tomorrow. I was looking at the following courses:
Do these 3 courses have a lot of repetition with each other or the two books you recommended? If not, in what order should I tackle them?
1 points • TheFuturist47
I looked up the Angela Yu course and it looks awesome! That really does look worth your money (but again, wait for it to go on sale)
Here's a couple other good ones:
This one by Tim Buchalka - it's long and I like his way of teaching - he over-explains things and starts from the ground up instead of just throwing confusing things at you.
This is a very good intro course by another teacher I like. He also has a discord channel that you can access, which is a great way to meet people and chat about programming and projects, get help on stuff etc.
Here is another good course by the same guy but this one is geared towards data science and ML.
1 points • anomalias
Automate the Boring Stuff with Python Programming https://www.udemy.com/course/automate/
Complete Python Bootcamp: Go from zero to hero in Python 3 https://www.udemy.com/course/complete-python-bootcamp/
Python for Data Science and Machine Learning Bootcamp https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
1 points • Flewizzle
That is a really good point, you have possibly saved me weeks there! really do appreciate it! Yes my project supervisor advised me to learn python before implementing anything as well, I'm doing a literature review for the next couple weeks then will be starting to learn python.
These are the courses I am planning on taking:
Do you have any thoughts on these?
1 points • shaner92
Just read this post and it's what I'm following for now, maybe there are more updated answers though.
To add, I enjoyed this course on Udemy
- Sorry not sure
1 points • chuangchou
-> ML / Big Data course / bootcamp?
I recently completed this course: https://www.udemy.com/course/complete-python-bootcamp/ and feel like I have a basic understanding of Python.
I'm interested in learning more about Python for big data and machine learning tasks. I was considering this course https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/, but it looks like both the ML section as well as the final section on Spark have received a lot of negative feedback.
I've also considered some of the courses at RMOTR, but I'd prefer something more "all-in-one" where I can complete a single (long) course and feel like I have a good overall understanding of how to utilize Python for ML and big data analysis.
Does anyone have any recommendations for a course or bootcamp? Thanks!
1 points • slidedish
Sorry it's no free.I'm beginer to , I did not find free resources, to be as explicit as possible, for my beginner level
I learned from here :
I do not advertise them but these have helped me
0 points • ItisAhmad
P.S this is his Bootcamp link. This Bootcamp focuses on SKLEARN more, and then TF1.
1 points • kingdom-of-freaks
What's a good learning path towards building your own python apps as a means of gaining passive income? I don't expect it to be a lot of income at first, but will be nice to have it.
Based on a post I saw here a few weeks ago, here's my thinking:
- Complete Python Bootcamp — Udemy course
- Python for Data Science and Machine Learning — Udemy course
- Automate the Boring Stuff — Book
- Python Tricks: A Buffet of Awesome Python Features — Book
On the other hand, I'd rather just build apps I think can make money off, and maybe I'm overdoing it with those courses?
2 points • saintshing
https://academind.com/learn/web-dev/web-development-overview/ (learn the ones you havent learnt yet)
Outside of web development, there is a huge demand for cs people who can do data science, machine learning, big data stuff(look at the biggest websites and social platforms like google, facebook, youtube, they are all powered by some machine learning algorithms). Right now you can get 2 months free on skillshare. I would recommend checking out the courses taught by Frank Kane and Kirill Eremenko and see if you are interested.
If yes, consider taking the paid courses(on discount) on udemy.
The free machine learning course of Andrew Ng (more theory focused), free fast.ai courses (more coding focused) and https://machinelearningmastery.com/start-here/#getstarted are also good resource.
2 points • blue_existence
If you have a solid coding background then my suggestion would be not to enroll in DataCamp. You'd be far off better with other cheaper and free courses.
Udemy- Python for Data science and Machine learning Bootcamp It's almost always on sale and you could find it for $10. If not, open it in incognito. I'd highly recommend this.
The freecodecamp is another savior - Complete Data Analysis - https://youtu.be/r-uOLxNrNk8
Numpy - https://youtu.be/QUT1VHiLmmI
For more stuff, you can refer to Coursera deeplearning.ai courses. Or more academic related CS229, CS231n, CS224N courses of Stanford. All of them have youtube playlists.
For getting a job. You can show your skills through Projects and Kaggle.com would be a great place to improve those skills and work on real-life datasets.
1 points • bguerra91
Yes spyder is integrated with Anaconda. As far as what it's good for, this quote is directly from the Spyder homepage and I think it is a pretty fair description for what it's good for
>Spyder is a powerful scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It offers a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package.
I would definitley recommend getting well-versed in python before you start trying to do to much with ML. MIT 6.001 Intro to programming and computer science will get you a pretty solid start.
This next course covers python specifically for machine learning, but you might want know a little bit of python before you start working on it. It goes into detail on some important python libraries such as pandas, numpy, matplotlib, etc. (this one isn't free but very affordable.)
Since you have a strong Math background, at the same time as learning python you could also probably start working on Cornell CS 4780. Kilian Weinbergers lectures are world-class.
And the book used for the course, Elements of Statistical Learning
My last recommendation is too figure out some specific applications you find interesting, and start working on a project. For example, computer vision, natural language processing, etc. I've had the fastest learning curve by doing this, rather than loading up on theory. Hope this helps.
1 points • create_a_new-account
there are many free courses
but if you want to pay
the udemy courses go on sale all the time for $11.99
and they also have a business discount
1 points • The_Amp_Walrus
Since I sort of did what you're planning to do (except I don't work in ML), you might find some of the things I wrote about studying programming helpful:
Looking at your other questions
>Should I study online (Automate the Boring Stuff\> Python for Data Science and ML Bootcamp \> fast.ai and/or deeplearning.ai) or take a 6 month grad cert on ML/Robotics/Computer Vision from a top ranked uni, currently subsidised by the government (AU$2500/US$1700)?
If it's all online then fuck ANU imo, do
- automate the boring stuff
- rice univeristy principles of computing I + II on coursera
plus whatever else you think looks interesting
make sure you're building something concurrently
>If choosing the online path, are there any changes you'd recommend making to my plan?
As I said, I think focus on software 70%, ML 30%, for reasons stated in other post
COVID is kind of screwing you here but getting outside and networking would be helpful when you can. Meetups are great for this.
>If choosing the online path, are there any changes you'd recommend making to my plan?
Learn Git, SQL, command line basics, and unit testing.
>How should I approach building a portfolio?
For a ML project you can either create a working model and deploy it, eg.this site or you can do some analysis and write it up in a blog post. Both are valuable.
For software projects you should create a website or tool, put it on github and document it nicely. Have a personal website that lists all of these projects.
Start a personal blog and write 1 post a week on something you did, learned, or found interesting.
>How will I know that I'm ready to start applying for jobs?
You don't. Start applying after 2 months of study. It's way too optimistic, but you literally lose nothing by applying to 1 job a week.