What is Reddit's opinion of
Datacamp?
From 3.5 billion Reddit comments
➔ Datacamp website
By popularity on Reddit, this Service is:
68 reviews of this app found across Reddit:
Hey! I work as a financial analyst in a corporate finance setting and I too started with R due to my lean in statistics; R has a ton of ready to go packages that make statistical tests a breeze. I've gotten to the point where I can develop shiny apps to create easy to use tools for the end user (when Excel just doesn't cut it). I came across the exact same bridge you're looking at haha. I started learning python about 6 months ago. It's actually not as scary as it seems and I think you'll find your R experience will transfer nicely.
From my experience thus far, I've found there are some areas where Python has R beat; mostly data wrangling, regex, and explanatory data analysis (EDA). Pandas makes it super easy to clean and reformat a data-frame. Once I'm satisfied with that stage of an analysis, I'll usually export it to csv/sql upload to be used by R for harder stats (should they be needed). R is definitely not a bad option for EDA, especially with the tidyverse (dplyr, ggplot, ggvis, etc.), but I feel Python has an advantage in that realm.
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Here's a link that helped with my transition (R to Python equivalencies around Dplyr)
https://gist.github.com/conormm/fd8b1980c28dd21cfaf6975c86c74d07
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In terms of learning platforms, I'm a big fan of Datacamp.com. In my opinion, the premium version pays for itself but there's a ton of options online. Still learning myself, but I feel it has been a great addition to my skillset.
Cheers!
Well, it depends on your experience with programming and what you plan to do with Python. I don't know much about freecodecamp, but if you're going into research, you can check out datacamp.com. You can get a free 3 month trial by having a Github student account and learn things like numpy, sci-kit learn, and so on.
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But again, depending on your experience and goals, some resources are better than others.
It doesn't sound like you are on a deadline, so I'd recommend datacamp as the easiest tutorials to get your feet wet. They are basically "fill in the blanks" short exercises which would familiarize you with the progamming syntax and most common problem solving strategies. Data Science is a very broad field and it's easy to get lost from all the things you need to learn. I would recommend starting with a course on python and pandas and sticking to it at least until you can do everything you are able to do in excel, but with code.
It really doesn't matter which tutorial/bootcamp you pick, but it helps to enter a structured learning program rather than wander around picking up books on dozens of subjects.
I'm currently pursuing a masters degree in this space if you have questions. As a starter, you should sign up for datacamp.com. if you can grind through unlimited hours of data science courses then you are in the right place.
I am guessing you are referring to free resources. If so, I recently found out about a youtube gem: StatQuest with Josh Stammer. His videos are so informative and bite-sizeable at the same time. He explains complex ML and statistics content with as little math as possible. Definitely check out his ML playlist. It is the best course on ML theory.
If you want something more practical with code, I recommend datacamp.com. (No affiliate!) Their career and skill tracks are awesome, I have been a paid subscriber for almost a year now.
DataCamp.com is awesome for Python or R based data science training if that's also something you're interested in. I started it but am currently finishing up FreeCodeCamp's Data Visualization before really diving in.
If you want to move to live dashboards then relational databases and SQL should be your next stop. DataCamp.com is an excellent platform to learn (and extend your Python and R as well)
Yeah 431 only deals with R and using it for data analysis, but he gives you access to a website called "datacamp.com", which helped us learn R and like 200 other courses like "Introduction to SQL", "Intermediate SQL", etc. After doing R, SQL felt like such a breeze. We learned similar stuff in R like creating tables, extracting data, which definitely looks good on resume since it sort of relates to SQL.
Have you tried going over some online courses first before jumping in with $14,500 investment ?
a little of googling I came up with:
- http://dataquest.io/
- datacamp.com
- Andrew Ng Coursera
I started out with Data Analysis, I really loved python and how it was structured but I didn't know where outside of scripts it could be used, so I said fuck it I'm becoming a data analyst, DataQuest.io and DataCamp.com are two good resources for that, both Freemium. Yet as I was progressing along I discovered that python can be used in web development, and websites can be turned into applications, so now I could build applications using python and html.
SQL can give you a better path for your career. I will recommend you the resources like StrataScratch.com and datacamp.com. I found stratascratch the most helpful as they have datasets pre-loaded with questions and answers we can practice with for interview preparations. On the other hand, Datacamp is cool for very specific niches.
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stratascratch.com They have datasets pre-loaded with questions and answers you can practice with. They source their questions from technical interviews from companies so I found it helpful to use for interview practice. Otherwise, Datacamp.com is cool for very specific niches.
First
It's not as bad as you think. Some of the hardest parts are getting set up. Download R 3.5 and R Studio in that order and learn how to create your own R Scripts and projects. I'd start with datacamp.com and do some very basic manipulations of data that way and then mimic them in the actual RStudio environment. I wouldn't even start learning the algorithms or any ML at all at this point. Just learn the syntax so you won't have to learn so much of that in real time while solving problems.
Next
Learn how to manipulate data. 80% of real world work is going to involve manipulating data. Learn how to extract data from .csv files, from databases and f*rom .*xlsx files.
There are tons of resources for R help but nothing will prepare you more than being able to manipulate the data to the correct formats for piping it into a model or a visualization.
Keep Plugging Away
At first, you will have to search for pretty much everything and it will be frustrating. Faster than you think, you will soon commit it to muscle memory. When that happens, the fun starts. Twenty minutes a day is better than nothing!
Learn Layman Terms
Listen to podcasts and overviews of what is to come, not necessary to actually know the math yet. My favorite is this guy here: http://ocdevel.com/mlg . I listened to every single episode. He really knows how to break down problems. Start with the very first episode. Put it on 1.5x speed to save time.
Speed Up Your Life
That being said, put all the Youtube videos on 1.5x if you can hack it. Especially if it's not intense and it's just overviews and some concepts. With straight math, slowing it down might be better. Ha ha. Seriously, put your life on 1.5x as you watch tutorials and listen to podcasts. Learn the lingo through these mediums as much as you can, it will help get you started.
This might sound counterintuitive but if you are someone that learns by "doing", it might be more helpful to learn R+Stat Concepts at the same time. By learning R you will have the opportunity to actually learn by doing rather than by reading/watching a video. How will the mean change if I make this one value 100? For me, I could read about it in a book until my eyes fell out but it never really made sense until I was able to play around with data first hand.
There are many online resources that teach many basic stat concepts while teaching how to explore them in R. For example, the R Stats Cookbook (https://rc2e.com/), datacamp.com has courses on R that review stats info in addition to just basic stats courses that also let you learn by doing.
You will learn a language you might want to learn anyways that will advance you in your career. Even if not for work, R is pretty powerful stats wise.
Howdy! You should probably look up a video like "How to clean and plot data in R". And then look up the portions you don't understand, and so on. It'll take a while to get a whole of things if this is your first programming language. I took a course on Datacamp.com and found it useful. At the very least, you need a "First Day in R" tutorial just get a lay of the land.
In general you want to:
- Understand the R Studio IDE and what the buttons do, how the flow of a script works.
- Look at your data (what are the values? is it formatted nicely? is there a lot of 'junk values' in the dataset?)
- If it's pretty bad, you need to clean your data (see guide below). R calls this Tidy Data.
- Then, and only once it's all clean, you can begin to visualize by using R's ggplot2 package.
I have a beginner guide to cleaning data in R on my website, if you are interested!
coding is an essential part of it. Almost every company has some sort of data team so you can literally work anywhere which makes it easier to translate past experience. Take a few classes in SQL and see how you feel. I like datacamp.com. If you decide coding isn't for you then data science is going to be pretty tough.
I actually am terrible at math. I failed Calc multiple times. Stats was the only thing I was half decent at. It made me steer away from IT/CS careers for a very long time. Even now, I still struggle. Being able to communicate is a lot of it. People like to ask "where did you get that number from" and you need to be able to explain it to someone who has no math background.
I was an electrician for about 10 years. Got sick of the work and environment and knew I needed to get out. I did part of the freecodecamp.org course, and learned the basics of javascript, HTML, and CSS. I then dabbled in Python at dataquest.io and datacamp.com but realised I wasn't interested in data science. However, I learned Python had more versatility than analytics. After 8 months of playing with Python I managed to land a gig as a junior dev where the JS and HTML skills also came in handy.
Just start programming, write crap code, break things, fix it, google stuff. Then when you feel ready start applying.
potentially datacamp.com. i kinda like it. others don't like it. what i like about it is that it has coding exercises. they are sort of like filling in the blanks and follow examples from slides and videos.
Same! I just started looking around on datacamp. So far I like it, but like I said, just started with some free intro's and stuff.
If anyone has any experience with datacamp.com I'd love hearing about what your thoughts are about it.
I do recommend learning SQL - it'll be just another tool in your belt. If something happens to cause you to get out of your current field of study, bam, you have a door open for you in the realm of D&A work. You could go into data visualization fairly easily, for example, with a basis in SQL, you then learn Tableau etc. (other data viz platforms) on youtube. And those jobs are in DEMAND. Btw, I have found datacamp.com very useful for learning SQL. Of course there are many ways to do it.
try datacamp.com. There are also a lot of youtube videos for any language you can think of.
https://www.datacamp.com/search?facets%5Btechnology%5D%5B%5D=sql
Seguramente Python/Jupyter notebook, Pandas, Matplotlib y Numpy hablando de "tecnologias"/lenguaje.
Si pensas pagar, algun curso de udemy o sino tambien tenes datacamp.com si te gusta ese estilo de aprendizaje.
Si no pensas pagar, el curso que te recomendo el otro usuario se consigue por torrent si buscas.
I found links in your comment that were not hyperlinked:
I did the honors for you.
^delete ^| ^information ^| ^<3
Hi there, I would say why don't start with W3Schools, or if pressure can deliver better results, try some paid course on datacamp.com BTW, I am a beginner myself, just share my experience after watching my youtube videos I feel youtube is helpful but not systematic enough for me. Hope this is helpful. All the bests, Crimsoncoffee
I've been learning programming through a job training program through my state's unemployment services. Also DataCamp.com has a subscription service where you can learn any coding language you want.
First off, Thank you for the response.
> Do you mean you want to write software, as you say below, or you simply want to work at a tech company?
Writing software for any company is the goal.
> You could also get a minor in CS to help things out
This unfortunately is not a option since outside factors (ie. parents) are pushing towards a degree and a nest leave at some point in the near future. Though I read about the coding bootcamp my university offered, what are your thoughts on these bootcamps? Worth it or?
> Can you link us to the github repo?
https://github.com/Modiodal/Mastermind
Any criticism would be much appreciated.
I spent the first couple of months working on understanding pandas and other topics in data science, which was introduced to me by DataCamp.com. Though I realized if I was actually going to learn the material instead of fill in the blanks, I needed to create something on my own.
> What excites you about software engineering?
I think the thing that excites me the most about software engineering, is the ability to take ideas and thoughts and create something people can actually use. I guess this is where the entrepreneurial side of me comes out. I realized that I had no direction and realized if I work hard enough, I could change my future for the best.
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Again, thank you for reaching out. Hopefully I answered all the questions you had.
Best display of your skill is coming up with something novel. Doesn't have to be the next Facebook or Snapchat, but something simple and neat. The "go to" beginner projects are things like a weather app, currency converter, simple card game.
You can create more wow factor if you're good at UIs as well.
Freecodecamp.org - Web Dev curriculum with milestone projects (HTML/JS)
DataQuest.io - Data Science in Python with projects
DataCamp.com - ML/AI/Data in Python with projects
I don't know what you do in finance, but if you like data analysis or science (financial data perhaps?), Python is very big in that area, check out DataQuest.io or DataCamp.com
If you're after that portal style learning where its all inbuilt into the website, try CodeAcademy.com, its freemium however.
If you don't care which languge, Python is a great starting language, super versatile and powerful. Automate the Boring Stuff is a an online text book which a lot of Python beginners follow.
Or there is DataQuest.io and DataCamp.com which teach Python with a data science focus (Machine learning, AI, etc.)
Data Analysis or Science. But what specifically do you mean by Finance? You want to work for a Bank or you want to work with financial data?
I found links in your comment that were not hyperlinked:
I did the honors for you.
^delete ^| ^information ^| ^<3
I am currently learning ML and DL in python. There are a lot of resources to learn. A few are Google's machine learning crash course, IBM's cognitive class(they also provide some badges for completing courses) and there are a lot of good courses on Coursera too. I am personally learning from Datacamp. Its courses are paid but you can get them for free by having GitHub's student pack(it will take more than a month to get the pack after applying for it).
There are also many good channels on youtube which you can follow. Talking about some books, my favourite book is Hands-On Machine Learning with Sklearn, Tensorflow, and Keras by O'Reilly publications. This is a really good book which is more practical and code-based than theoretical.
Hi guys,
I've just started to learn Python and I'm really interested in the DS path with a lot of curiosity in Machine Learning an IA. I'm a 'information management' brazilian student and a Mech. Engineering Document Analyst Trainee, i don't have any degrees or good programming skills and not even a English course soo sorry for the bad english (classic!), but I have some good friends on the field that recommended me some DS books like 'Data Science for Business' by Tom Fawcett and 'Python DS Handbook' by Jake Vanderplass and one of them helped me to get the Github Student Developer Pack, where i signed for 3 Free Months on datacamp.com which, atleast from a newbie perspective, they have some great career tracks (I've started the 'Python for Data Scientist' one right now).
Well, thats a pretty basic background, i know, and its the first time i took courage to comment on a Data Science Thread, and my questions are simple:
Is it a good way to start? What knowledge or skills are expected to apply for a DS "Junior Job"? And what are the best Certifications in the field?
Also I'm accepting any books, youtube channels, online courses or anything that can get me immersed on the field.
Help us spread the word about our Free Week! Share the link datacamp.com/freeweek and make sure to include the hashtag #DataCampFreeWeek. We’ll give free one-year subscriptions to the authors of the Facebook, Twitter, and LinkedIn posts with the highest number of combined likes and shares!
I don't have a degree. Learn to program in your spare time, build a solid portfolio, apply like crazy, earn some certifications (networking, security, or cloud). I started in IT a year and a half ago, began as a Junior Dev on about $60k, built up my experience and got certified in Google Cloud Platform, basically doubled my salary ($130k) the following year jumping ship to be a Cloud Engineer.
Free Code Camp is amazing for getting into web development, the other two are great for data science/analytics and picking up Python (super versatile in-demand language).
I was an electrician before, you've already got a foot in the door, network and try and make some contacts, you never know.
In terms of self-learning, I started with FreeCodeCamp.org which is a free web development curriculum (HTML, JS, CSS) that boasts it can get you job ready. I don' doubt it, its definitely a really good resource to build skills and a portfolio. I completed the first half before going out on my own.
I then learned Python by doing a data science course (free version) at DataQuest.io and DataCamp.com but ultimately stuck with web development but incorporating Python into it.
I learned cloud engineering basics on the job as a junior developer.
In terms of disadvantage, yes and no. There's a lot of fundamentals I'm missing, but most big companies are open to training and up-skilling, they're more about attitude and willingness to learn.
And to counter that, Cloud technology and IT in general moves at such a rapid pace that most degrees are redundant at the technical level. A degree in algorithms and computer science might stay more relevant, but I have no degree and majority of my colleagues have no degree. Ironically, the only person I know who has a degree started at a lower level graduate role than me.
Definitely agree on learning tech skills. I surpassed many of my business school classmates by learning SQL and Python. Coding is an amazing mental exercise. Datacamp.com is a great place to start.
Hi there! Did you try out sites like EDX.com? Microsoft offers some good courses on Microsoft Power BI there for example, but there are some other great programs hidden in there. Just search for Business intelligence and see if there is something in there for you.
Also, try out sites like datacamp.com and dataquest.io, these provide more guide learnings and some programming skills. You can get a lot of basic skills there for free but you need to pay up for the more detailed courses.
Are you just interested in Python? You could expand your skillset and learn frontend development and tie the two together to build Web UIs for python scripts.
Learn persistent storage and using databases to store data that the UI can display. Maybe something like a simple Task/Todo app?
Basically build up a "fullstack" skill set. Otherwise have you looked into Machine Learning or Data Science?
- Data Science - DataQuest.io
- ML/AI/Data - DataCamp.com
- Frontend - FreeCodeCamp.org
Do all the free stuff on DataQuest.io and DataCamp.com, it focuses on Data Analysis but it teaches the fundamentals of using python to manipulate data, work with files, etc.
Did you have specific questions in regards to the script you posted? It's fairly straight forward once you know what you're looking at.
BeautifulSoup is a package, and that's just code someone else has made and literally packaged in a way for reuse by others. BeautifulSoup specifically is a package for scraping data, most commonly from HTML, whether files or live websites. You could write your own custom script to do this, but why bother when someone has already done the hard work.
The first section of the script is opening a file. That's a great place to start, creating and opening files to save data. You can practice creating files and reopening them:
with open("my_file.txt", "w") as f: f.write("Hello, Reddit!")
The file will be created wherever you ran the script from, if you did it in PyCharm it will be the project directory.
Now you can create another script to open and read it:
with open("my_file.txt", "r") as f: text = f.read() print(text)
>> "Hello, Reddit!"
Now ask yourself what some important checks should be so your script never fails?
- What if the file already exists when you try to write to it?
- What if the file doesn't exist and you try to read it?
My hot tip to learning to program in python is to break your problem down into simple steps, each step then can be turned into a line(s) of code. Trying to write from the top of your head is doable but planning code out is a great way to talk through a problem with yourself.
personally I took a quick crash course on SQL and then added it to my resume. Got a job using SQL, realized I didn't know as much as I thought but was able to learn really quick on the fly and using datacamp.com. 6 months in and I feel comfortable with intermediate queries.
I was hesitant to learn on my own so my first introduction was from a class, but as I learn more the more I see all the resources available to help people learn. I've used udemy.com, youtube tutorials, just googling articles, other university classes, and datacamp.com. There are a plethora of resources available to learn out there. Don't be afraid to take the first because its the biggest and get out there to learn!
Before you know it you'll have your own side projects of interest going!
The Carpentries do this regularly in two days. tidyverse alone a day probably. check out the lesson materials https://software-carpentry.org/lessons/ And Dave Robinson @drob has 4 hours course at datacamp.com doing exactly the same as you want in 4 hours.
DataCamp.com is a good intro. They teach both R and Python.
Also, if you're on Twitter, check out the #TidyTuesdays hashtag. Every week there's a data set provided freely and people use R to make visualizations of the data. It's great practice.
I use datacamp.com They have a mobile app that gives me a daily quiz and a lot of mobile content.
If you can do an MS in Stats you can definitely learn to code. Coding is best learned with practice.
Try DataQuest.io or DataCamp.com
They'll give you the basics in Python for data analysis and machine learning, if those topics don't interest you then take the skills they teach and apply them to your own projects afterwards.
datacamp.com has a free 2 month trial if you use a Microsoft login. google "my visual studio", first link. login. benefits tab. Then find the data camp tab and its already activated. I'm working thru the python data science part which is pretty incredible so far
I'm not a network engineer, but work in telecom and am interested in learning more about networks - and how program such as python can be used in the industry. I already know a little python as I've been using datacamp.com. would this be useful for me, or do you have any other suggestions for learning material?
Couple of suggestions.
1 - Bootcamps can be a good path, but are expensive both in time and money. You might consider other options like evening programs structured for working adults (UW Certs or BAS programs at North Seattle or Bellevue colleges)
2 - Data Science is complementary to your finance background, where CS is more general. Have you considered a data science program?
3 - If considering a DS track, I'd suggest starting w/ online learning - e.g. datacamp.com and various resources in /r/datascience - before committing to a more expensive program.
4 - Start with Python as a programming language, unless you really want to break completely from your past experience and target pure SW engineering roles.
If you don't have much time to practice and don't have internet access I'd suggest downloading the mobile app DataCamp for a quick 5 to 10 minute practice session a day. was able to get the basics of Python down in a week.
Don't need to dish out money, there is hours upon hours of free material on Python, employers don't care about programming certifications, they care whether you can actually solve real world problems and write clean documented code. I recommend getting up to scratch with Python through DataQuest.io or DataCamp.com in any stream you want, take all the free courses. Start writing basic scripts by yourself that do simple tasks like move files around, change network settings, audit security settings, data extraction from files. Create a GitHub if you don't have one and do simple write ups about your scripts:
Script to Scan Folder:
this script will recursively scan a folder and output filenames.
Dependencies
import pandas import os
Getting started
for dir, subdir, files in os.walk('/Users/JohnSmith'): for file in files: print(file)
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That is a super basic example, but you get the idea, you basically want the reader to be able to recreate your script without any hassle, but this also shows you can document your code and communicate well.
At the very least you need to understand statistics. Math will be important but you're not going to need to use linear algebra or multi-dimensional calculus unless you really want to get into algorithm design or machine learning.
You can make a good career with a focus in genetics and strong programming skillset.
Learn Python, R, be comfortable in Unix environments.
After your second year start looking around to see if there are labs you can volunteer with (if you're still interested).
Check out sites like datacamp.com, codesignal.com, codeacademy.com, and others.
Don't worry too much about the social life stuff with respect to your career. Most people will have very active social lives if they want them.
You will figure it all out, just make sure you take a breath and enjoy your new surroundings. Figure out what subjects you enjoy learning about and pursue them. Take a music history class if you're into music, and maybe a creative writing course to feed that part of your brain if you're still interested in it.
If you take a course unrelated to your major that you love, don't panic. It can always morph into a hobby/interest you have outside of work.
Finally, talk to TAs and Professors of classes you really enjoy and ask them about how they got to where they are now, etc. Most will be very happy to chat with you about subjects you have genuine interest in. We're normal people just like you.
I would suggest you to learn from datacamp or stratascratch. DataCamp.com is cool for video tutorials and Stratascratch.com has the exercises with the questions directly from the technical interviews taken from companies and universities.
I don't have much to say on your career choice. However, I'll recommend DataCamp.com to you for learning these programs for data analyses.
You can take classes in R, Python & SQL. A really great way to build up your skills. I get it free with a class at my university - But I would honestly have paid for it. The classes are so amazing and easy to follow along with. They allow you to build up your skills from beginner to advanced. You can focus in data analysis in Python & R.
Will teach you awesome skills working with data using Python, if you want to move past the basics. It has a code along sort of website, where it tells you the challenge and you write the code into the browser.
Learn basic Statistics & R Language . Easy way to emigrate is via Masters. Start researching about genuine universities.
It may not be so easy to get a job and move unless you have good knowledge of your domain and exceptional skills to impress hiring managers to sponsor a visa for you.
Take a look datacamp.com (not affiliated) for some course ideas if you want to learn on your own.
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I have. It was not that difficult to complete per se. But take in mind I was studying the whole day to finish the course as quick as possible so 12+ hours a day and I have 3 years of experience with python and programming. All in all it took me 17 days to finish the course. I did learn allot from it. I am practicing what I have learned on datacamp.com and have managed to completed 29 of their courses and 6 projects in a month thanks to what I have learned from the training I received doing this program. Basically it made data science easy to learn and fun for me. The results might differ for every one.
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Don't do the course for the certification, no hiring manager is going to care about a programming certification, they're going to want to actually see how you write code and what you have written. Do the course to learn, but learn independently as well; write your own code, solve your own problems, upload your projects to GitHub to show people. CodeAcademy is a great starting point but its not a ticket to getting a job. I have zero certifications and spent 7 months just learning and got a Python developer job just from demonstrating my understanding of problem solving and writing code in Python.
>Is code academy good? Yes, it's a great place to learn.
>
>Is the certification good? No, I don't think it'll be worth anything to employers.
I would say do as much free course material as possible before buying anything. In saying that I have bought some excellent courses off Udemy.com for like $10, which pretty much take you from basic to proficient and include milestone projects you can use to show your knowledge.
Another similar one to Code Academy is DataQuest.io and DataCamp.com but they focus on using Python for data analysis/science but still great skills to have, free and premium options.
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I just renenewed my subscription to datacamp.com for the third year and I have found it very useful for learning and maintaining my skills in Python, R and SQL. They have (or had) a yearly sale around the holidays that's 50% off, and maybe other sales around the year too.
Sometimes their questions can be annoying because they'll want you to solve something in a specific way, and there are other more obvious solutions available, but it is usually because they are trying to teach some particular method or practice.
I think you should focus on a particular area you enjoy.
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You mention analytics - have a look at datacamp.com and see if you like the BI / data analytics side.
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I've worked with a lot of data analysts, and found the ones who were great technically needed a lot of hand-holding to do ads-related stuff. I've worked with one data analyst with not so strong with her tech skills but from an adops background who was head-and-shoulders above the pure BI people.
Data Analysis
Machine Learning
AI
Reddit Bot
Twitter Bot
Learn how to use databases - ie. Store/retrieve data from an online SQLite database, maybe something like netflix movies you've watched (title, director, lead actors, your rating). Then when a friend says "Hey whats a good movie?" You can retrieve all the movies with ratings greater than n
Are you just directionless of where to go at the moment?
Do you know how to implement databases yet? Make an app that gets user data, then store that data in a SQLite database, then let the use view the current data. ie Movie database?
What about data analysis? try DataQuest.io or DataCamp.com
I think you first need to define, 'exactly what you need.' Then your definition will help guide your decision. In my personal experience, I find that Datacamp.com works best for me.
Stick it in a HISA and try to live as cheaply as possible.
I'd suggest skilling up in one of the following areas:
- AWS via https://acloud.guru
- Data science via https://datacamp.com
- Cybersecurity via CISSP or OSCP.
The above I've selected because they're cheap and effective, and can be done largely online. AWS/CISSP/OSCP certification is sought after, and will make you valuable in the job market.
In the meantime pick up what work you can to pad out your resume.
I used datacamp.com after writing L2 last summer (they have courses on python and r for datascience and some specialised courses on finance with r). It isn't really cheap, but I really liked the very learning-by-doing approach of it. The Intro to Python and Intro to R courses are free.
Overall, I prefer R slightly to Python. The syntax seems much more intuitive and straight forward.
Long-time reddit lurker. First post ever. Two months ago I abandoned my pursuit of medicine to learn coding. Since then I have absolutely fallen in love with Python. It is phenomenal. Right now I'm teaching myself the fundamentals through datacamp.com and this week I'm learning how to beautify soup : )
Start small. Learn the command line, Bash and Python/R at codeacademy.com or datacamp.com. Overtime you'll get better at understanding tools and documentation. For now just focus on the basics. You have plenty of time.
I am on the same learning journey.
Datacamp offers hands-on courses on many Data Science tools and practices.
Consider also the free ebooks by Allen Downey: