Python for Data Science and Machine Learning Bootcamp

I liked this Udemy course (focuses less on stats aspect of modeling and more on just showing you how to implement in Python).

the same guy does a simialr one for R

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!

Ohne dir jetzt nahe treten zu wollen, aber das Beispiel ist doch recht einfach, auch wenn man eigentlich fast nichts mit Python/pandas zu tun hat.

Falls du dir gerne was mit Kursen beibringst, kann ich dir folgenden Kurs bezüglich Python/DataScience/Pandas SEHR empfehlen: https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ Ich behaupte, dass du deine Fragestellung damit innerhalb eines Tages selbst erlernen kannst, wenn du nur zusammenkopierst wahrscheinlich ein-zwei Stunden. Gibts Videos dazu und man kann in den Jupyter-Notebooks live mitmachen.

Ansonsten ein paar YouTube-Videos, gibt es viele hilfreiche dazu (evtl. "Pandas Grundlagen" und im Anschluss "Pandas Visualisierung" oder "Matplotlib Grundlagen" oder "Seaborn Grundlagen")

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.

May I interest you in Python for Data Science and Machine Learning Bootcamp?

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

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

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._ ?

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:
https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

I am doing a course with the same motive. It's super comfortable with the practical application of code.

Its on Udemy btw - https://www.udemy.com/course/complete-machine-learning-and-data-science-zero-to-mastery/

You can also go for - https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

I have heard good stuff about this one!

To clarify, Jose Portilla has two courses that have similar names.

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
https://www.udemy.com/course/data-science-and-machine-learning-bootcamp-with-r/
The first link is for the one that uses Python.

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:

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

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.

https://zealdocs.org/

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.

https://www.kaggle.com/

This makes much more sense to me. Thank you

The lecture I'm referring to is from a Udemy course

I cannot link the video directly, but here's a screen grab.

https://imgur.com/a/aHIwTsA

>Pandas/Python: 1. https://www.udemy.com/course/data-analysis-with-pandas/ 2. https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ These are my two recommendations.

Are those for complete beginners or should you complete a basic Python course first?

i heard that was a good one, but i used udemy.

​

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

Have you tried any Udemy courses? Don't expect masters level, but it's good for getting the hang of Data science techniques.

https://www.udemy.com/course/machinelearning/

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

This is a good place to start if you are a beginner.

Are you referring to "2021 Python for Machine Learning and Data Science Masterclass" or "Python for Data Science and Machine Learning Bootcamp"? (Given that i have a basic knowledge in python and indecisive in DS or ML)

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.

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

Good luck!

Hmmm, practice, practice, practice

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

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/

Python and its data science libraries sound very hi-fi, but once you start working these are very simple. you can go through this course: https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
This is a very straightforward course, no pre-requirements required. This is around 25 hours course and costs very minimal. Once you complete half of this course, you will be comfortable using python libraries like numpy, pandas, scikit etc

Thanks, can i buy below udemy course at rs.525, is it worth it?

Python for Data Science and Machine Learning Bootcamp

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

currently doing Jose Portilla's Data Science course in order to help me learn how to implement machine learning. https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/learn

​

thanks for the advice :)

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. automate the boring stuff with python is good, as someone else mentioned for automation of basic tasks.
2. Jose Portilla has a good course on Udemy related to Data Science and machine learning if that's more what you're trying to learn.

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

https://www.udemy.com/course/automate/

Also make sure to never spend more than 10-15$ on udemy courses. They have really deceptive pricing practices.

Sure thing. Everyone's situation and progress is different, so hard to speak to your situation specifically without knowing more, but here are some of the things I wish I could go back and tell myself when I was first trying to find my way.

1. Data Science is an EXTREMELY large tent, especially being such a buzzword these days. Understand that there are a multitude of roles focusing on various aspects of the data ingestion and analysis process, and that these roles will pay according to your skill set, not your job title.
2. Most people in the hiring process will have significantly less technical expertise than you do. They also do not care about this and very much care about finding candidates that meet the minimum qualification and present themselves well.
3. You are NOT an aspiring data scientist. You ARE a data scientist. Right now. I do not care your level of proficiency in anything, you are most likely underestimating how you stack up by a significant margin by the time you are probably comfortable appplying to jobs.
4. Lol. You are not going to even get a call back on those data scientist roles you keep applying to. See point 2 about minimum qualifications. HR generally has some pretty strict guidelines to follow to ensure non-discrimination, and would have to restructure the entire job description and pay scale most likely if they were to even think about giving you a chance.
5. Salary = skill set used in work environment + highest degree + yoe
6. The hiring process is a laughable crapshoot everywhere with glaring flaws. It is never personal and being ghosted is the norm, and can happen at any stage in the hiring process. Get over yourself and get out more applications. Make sure you are hitting the buzzwords recruiters are looking for and you should be good eventually.
7. Experience is just as important as financial compensation, and is often worth more in the long run in real dollar value coming back to you. I was not able to land the positions I wanted at first, but I could find ways to advance my skillset on the job, even if I wasn't compensated fairly for it.
8. Learn SQL first. Learn SQL second. Learn SQL third. Find the largest SQL database you can and run a bunch of queries against it. Kaggle is a good place to look for large SQL files. Take advantage of ANY chance you get to query production databases so you can learn how to apply your skills in a real situation.

https://www.udemy.com/course/the-pandas-bootcamp/

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

\^ These courses are what I think put me over the edge and really increased my salary. My first analyst role was a short contract assignment at a large company that mostly expected me to do things in excel, but they had no problem with me using python if I could leverage it in areas better than excel.

That led to several extensions in my contract and the largest pay bump my recruiter said he had seen anyone get. Not trying to brag about anything but more point out that I would see these reddit posts about people getting lucky like that and just KNEW it would never apply to me, and well I was wrong apparently.

I've done a decent amount of these type of posts and its kind of exhausting but I feel like my experience is pretty relatable to a lot of people, and most of them are closer than they realize. You do not need a master's degree, but you are competing mainly against people that do have them. You need to find a way to stand out SOMEHOW, so focus on that.

Hope you find at least a bit of my rambling useful :). Good luck!

Agreed with sambomambowambo: beware of falling onto a course treadmill. If you are planning to go into data science, these projects will serve you well both in learning and for your personal portfolio for when you apply to jobs.

That said, I'm in a similar boat and am working on transitioning into data science, specifically data analytics as a start. As you're in the same boat, I'd recommend to use the below:

• Google Data Analytics Professional Certificate : Coursera
• 2021 Complete Python Bootcamp From Zero to Hero in Python : Udemy
• Python for Data Science and Machine Learning Bootcamp : Udemy

I completed the Google course and would recommend that as quite a useful experience - especially past the first two courses. It is helpful especially if you have no prior experience. I have purchased but not yet started the Python course, but the instructor is well-regarded.

My take on all of this is to work through the courses as thoroughly as possible and to stretch your ability to the extent you can on the projects you're assigned. Do your damnedest in any capstone/ final project for each course and all micro-projects and in-lesson problems. Once you have a decent level of understanding, complete a project to apply what you learned.

​

Personally, I went above what was required for the Google capstone project and stretched my skills- so I'm not completing another analysis project until I've developed other skillsets. Now I'm focusing more on Python and SQL and will do a few independent projects in each until I'm confident. Then I'm moving onto the Python for Data Science course and will do another independent data analysis project once I've completed that.

It appears Udemy does have a sale ending tomorrow. I was looking at the following courses:

https://www.udemy.com/course/complete-python-bootcamp/?signupsuccess=1

https://www.udemy.com/course/complete-python-3-masterclass-journey/

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

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?

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/

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:

1. 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.

2. 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.

3. Here is another good course by the same guy but this one is geared towards data science and ML.

Pandas/Python: 1. https://www.udemy.com/course/data-analysis-with-pandas/ 2. https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ These are my two recommendations.

I would probably do the first one. Then whenever you try to do something in excel at work you go through the effort of doing it in python first. This helped me learn. Once you finish the first video you'll know enough vocabulary to google stuff.

The second course covers more broad topics that could be useful.

For SQL. I started with this tutorial: https://www.sqlitetutorial.net/ This tutorial, like a lot of SQL tutorials are focused on managing a database for applications. But really for data analysis you need to know filters, logical operators, math operations, insert. Knowing primary keys and foreign keys are not that useful in data analytics.

Going through the tutorial will help you learn everything you need to know though.

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?

Just read this post and it's what I'm following for now, maybe there are more updated answers though.

1. https://www.reddit.com/r/MachineLearning/comments/5z8110/d_a_super_harsh_guide_to_machine_learning/
   To add, I enjoyed this course on Udemy
   https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/learn/lecture/5733492#overview
2. Sorry not sure

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:

https://www.udemy.com/course/complete-python-bootcamp/

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

Do you have any thoughts on these?

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 :

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

https://www.coursera.org/specializations/data-science-python

​

I do not advertise them but these have helped me

P.S this is his Bootcamp link. This Bootcamp focuses on SKLEARN more, and then TF1.

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

-> ML / Big Data course / bootcamp?

Hi,

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!

Here’s the ones I completed - couldn’t say whether they’re the best out there but they got me up and running:

https://www.futurelearn.com/courses/data-to-insight

https://www.open.edu/openlearn/science-maths-technology/learn-code-data-analysis/content-section-overview-0?active-tab=description-tab

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/?utm_source=adwords&utm_medium=udemyads&utm_campaign=DataScience_v.PROF_la.EN_cc.UK_ti.5336&utm_content=deal4584&utm_term=._ag_73899881953.ad_532713166723.kw__._de_m.dm__._pl__._ti_dsa-774930027489.li_9046609.pd__.&matchtype=&gbraid=0AAAAADROdO0qdZP-LVdD1AL0txDvdmxHW&gclid=CjwKCAiA-9uNBhBTEiwAN3IlNPbFd-S29R9PUBzgHtZ5FNWbM1Cl0cQpYm4z4zcET98J3WBDPW9HJxoCaQUQAvD_BwE

https://www.udacity.com/course/data-analysis-with-r--ud651

All relatively short and cheap/free

This I did after I got the job but I found useful for coding principles:

https://pll.harvard.edu/course/cs50-introduction-computer-science?delta=0

(Free without the certificate - which I haven’t got)

I’d also recommend data camp/code academy - lot of free modules that are very accessible

I’d say a grasp of SQL is probably essential - this is a really good website that I used (also free)

https://www.khanacademy.org/computing/computer-programming/sql

Finally, recommend Kaggle for picking up interesting data to play around with

https://www.kaggle.com

Python for Data Science and Machine Learning Bootcamp

Python for Data Science

Python for Data Science

How to Learn Python for Data Science In 5 Steps

Data Scientist with Python

Python Data Science Tutorials

Python Data Science Handbook: Essential Tools for Working with Data - Book by Jake VanderPlas

I'm sure there is more these are from the front page of a Google search

I have a internship interview coming up that is going to focus on " W....Python skills including handling large datasets using data frame Note: any experience with Tensorflow package within Python would be a plus."

I'm comfortable with Python, but haved used it for large datasets and data frames.

I was wondering if anyone had some suggestions.

I do have access to this Udemy Course and theres a few CodeAcademy courses as well

https://www.codecademy.com/learn/paths/analyze-data-with-python

https://www.codecademy.com/learn/paths/build-deep-learning-models-with-tensorflow

https://www.codecademy.com/learn/paths/machine-learning

If anyone has some suggestions on how to prepare for this, I'd appreciate it.

https://academind.com/learn/web-dev/web-development-overview/ (learn the ones you havent learnt yet)
https://academind.com/learn/web-dev/trends-2020/
https://www.youtube.com/watch?v=0pThnRneDjw&t=3674s
https://insights.stackoverflow.com/survey/2019

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.
https://www.udemy.com/course/datascience/
https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/
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.

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

Pandas - https://www.youtube.com/playlist?list=PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS

Matplotlib - https://www.youtube.com/playlist?list=PL-osiE80TeTvipOqomVEeZ1HRrcEvtZB_ or https://www.youtube.com/watch?v=3Xc3CA655Y4

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.

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.

https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/

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.)

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

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.

https://www.youtube.com/watch?v=MrLPzBxG95I&list=PLl8OlHZGYOQ7bkVbuRthEsaLr7bONzbXS

http://www.cs.cornell.edu/courses/cs4780/2018fa/

And the book used for the course, Elements of Statistical Learning

https://web.stanford.edu/\~hastie/ElemStatLearn/

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.

there are many free courses
https://www.kaggle.com/learn/overview

https://www.youtube.com/watch?v=6GUZXDef2U0&t=1s

https://www.youtube.com/watch?v=wB9C0Mz9gSo

https://www.youtube.com/watch?v=8Y0qQEh7dJg

https://www.youtube.com/watch?v=PcvsOaixUh8

https://github.com/jpmorganchase/python-training

https://www.youtube.com/playlist?list=PLGLfVvz_LVvQjNJr85J4U_lxDg8vgqvcO

but if you want to pay
https://www.edx.org/professional-certificate/python-data-science

https://www.edx.org/professional-certificate/berkeleyx-foundations-of-data-science

https://www.udemy.com/course/learning-python-for-data-analysis-and-visualization/

https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/

the udemy courses go on sale all the time for $11.99
and they also have a business discount

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:

• where to start
• pacing yourself
• learning tools vs theory
• choosing what to learn

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
• fast.ai

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.