First, decide how much time you have to spend on the problem and whether it should be tractable or not.
If it's very urgent, and you can hack around it, hack around it. If it's very urgent and important, hack around it now to unblock and then dig into it deeper later (more in a bit). If it's not urgent, you can treat it as a learning experience and dig in deeper if you want to or not. (Basically make sure you don't fall into a rabbit hole while attempting to solve one specific error and make sure you're achieving what you actually need to).
For digging in deeper (because it's just that important, or maybe you just want to learn): make sure you RTFM, figure out where your understanding of the system and the actual system differ – what did you expect to happen, what's happening and then tweak one thing at a time to make sure things are behaving as you would expect them to till you find the reason. There's a lot I could keep writing about this, and I'm fairly certain much better engineers and authors than me have – an example error would have made this easier.
For Android in particular, we're more lucky than iOS engineers because you have access to the underlying code (for the large part) so you can dig into the android source and even debug the part of the framework that runs within your application.
Of course, sometimes it's just frustration and exhaustion in which case you should follow the advice already posted and just take a fresh look at it the next day.
PS. I haven't completed reading this but https://www.amazon.com/dp/B00PDDKQV2/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1 was recommended to me and has been good so far.
Amazon has a 3 book kindle edition for free right now (you can use an app on mobile or your PC as well). I "purchased" it but haven't looked through it yet.
https://www.amazon.com/Python-Manuscripts-Programming-Beginners-Intermediates-ebook/dp/B07CQPHC1N/
Du musst dir natürlich die Frage stellen, ob du wirklich (sofort) ins Projekt Management gehen willst. Es hört sich meiner Meinung nach eher danach an als würdest du lieber noch etwas entwickeln wollen.
Wenn ich SAFe höre, muss ich nur kotzen. Das ist ja Scrum auf Drogen :-D.
Ich würde an deiner Stelle mit Google Cloud Zertifikaten anfangen. Ist sowieso gerade voll im Trend in Deutschland ( und so paar Jahre nach allen anderen Ländern :-D) Zum Einstieg das Associate und dann vielleicht das ML Engineer Zertifikat. PyTorch habe ich nie genutzt, aber tensorflow zum Einstieg ist das eigentlich die Bibel
Vielleicht hilft das schon einmal als Anregung.
Per il secondo punto forse questo: https://www.amazon.it/Code-Language-Computer-Developer-Practices-ebook/dp/B00JDMPOK2 ?
Today I stumbled upon a free Kindle Python book set from Amazon here. Maybe it might interest you?
Hust take a look at what the job postings are asking for. Nearly all I've seen want experience in R, SAS. You can run python in R by installing an interpreter and run SQL queries with the function sqldf(). There are a ton of free resources to learn R and several youtube channels dedicated to it. This book will get you started without having to take a formal class: https://www.amazon.com/gp/product/B01NAJAEN5/ref=ppx_yo_dt_b_d_asin_title_o00?ie=UTF8&psc=1
If you want to improve your personal programming craft, it's something that occurs over a lifetime. I've been doing this 25 years, and I still strive to continually improve, and learn new techniques all the time, or re-evaluate old practices.
It's taken me many years to get reasonably decent at writing APIs. You need to have a clear grasp of the problem domains, such that you can anticipate use cases. This is the biggest issue if you're experienced, especially if inexperienced in the domain you're working on.
There are many other factors, such as efficiency, and if your API allows clients to easily make mistakes, or whether it naturally encourages correct code.
I'd recommend an old classic: Code Complete, considered by many to be the best software-writing guide ever. It teaches you bedrock principles, which is most valuable for newer programmers who don't necessarily understand why doing something one way is preferable to another way, etc.
My default rec is always [Gerón's Hands-on ML](https://www.amazon.com/gp/product/B07XGF2G87), but it might be a bit much if you're just getting started and aren't already comfortable with Python.
Gerón does a great job of walking through some actual ML projects while giving some sage advice. That being said, you're not going to be equipped to develop starategies for rolling out ML projects just by reading this book.
You might be better off looking around for workshops where people are breaking down prior use cases in the field which you want to apply ML. Then you'll start building a list of keywords/concepts that you have to learn. Sure there's overlap, but what works best for forecasting in supply chains is going to be very different from information retrieval in large corpora of text, which going to look different from generative art, and then all of those are going to look enormously different from ML applications in finance/accounting.
The book 'Storytelling with Data' has some extremely useful direction on how to convey your point to a lay audience - in other words, how to answer the 'so what?'
You would probably only need to look at the first few chapters which are about identifying and conveying your 'story' to the audience.
I would assume you know or have someone who has expertise in that health field.
Read this book: https://www.amazon.com/gp/product/B07XGF2G87/
Apply one of more of the techniques learn there to solve your problem. Evaluate its accuracy and see where it is failing or coming short.
Dont waste your time with dozens of books and courses, focus. The book is good enough to give you a good start. Only concentrate on that and after finishing it you can come back with a lot more experience.
I love all the pictures nformation people have nowadays. It's awesome but can be a bit overwhelming. I started as a kid in the 80s when every pc came with basic. Basic ( not to confuse with visual basic) was procedural and made you think like a computer thinks. (like c). You wanted to learn more you bought a book or read magazines with code on them.
If you want a holistic overview of code and how computers work, I suggest the book Code by Charles pet old. It's a very fun read that starts with Morse code and ends up in binary/hex and how memory works https://www.amazon.com/dp/B00JDMPOK2/ref=cm_sw_r_cp_apa_glt_780BZNGCV15CV8E58Y0S
If you just want to grasp c#, try a head first book. Learn about classes And how to structure them.
It's a huge topic and I can answer any questions
Recently started learning. Taking the CS50x course offered by Harvard online. Bought this book and am going through it. Also looking at this document to guide me through resources. Basically doing whatever I can to get on the right track. Made a game with scratch and it seems like my CS50 course is moving on to C++ now.
Think I wanna be a back end dev but not 100% sure yet still exploring my options. I got really excited about Pen Testing actually but was told that was basically out of the question for anyone self-studying.
With a new-born + pandemic it's not easy, but it's worth it to be happy and give her a better life.
Understanding enough to write an OS is awesome but please don't get discouraged if you aren't ready in the next 5 years.
Based on your post, i have one of the best books to recommend to you
Code: The Hidden Language of Computer Hardware and Software 1, Charles, Petzold, eBook - Amazon.com
This is a very well written book and eases you into concepts. It covers everything from morse code from braille, to building circuits. This is one of my favorite books of all time and can be picked up from any skill level. It's not about OS development but gives you an extremely solid foundation to learn from. OS dev books/tutorials will be a lot easier to read after this.
I apologies for the confusion I honestly read your post a couple times and thought you were a r/lostredditors.
I would recommend reading the book Code Complete (Developer Best Practices) 2nd Edition. I have read a good portion of the book and it gives a good foundation to become better at software architecture. The book is a bit dry, but many people I have talked to in industry have read this book and found it helpful.
Charles Petzold's book Code: The Hidden Language of Computer Hardware and Softwareis a good one for grasping how computers work at a low level. It's casual enough that you can read it without being at a computer.
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There's also Algorithms Unlocked, which is written by a co-writer of MIT's algorithms book. I haven't read this one but it looks like another good casual text.
Agan's book on debugging:Debugging: The 9 Indispensable Rules for Finding Even the Most Elusive Software and Hardware Problems (I like it because it changed how I think about troubleshooting)
Bentley's Programming Pearls (2nd ed) (a short book, I like it because it is short and full of problem framing perspective - reminds me of Alan Kay's quote, "Perspective is worth 80 IQ points.")
Petzold's Code is a nice armchair book. More about how software and hardware works rather than the development process. Give the Amazon synopsis a look.
reading the amazon page for the book it would seem it go into detail on explaining what software code is the details and everything. It doesn't seem like it delves into actual teaching of a language, but seems like it's worth $16 price tag.
I agree @Taunk, Cole Nussbaumer Knaflic's books are awesome...
Storytelling with Data, A Data Visualization Guide for Business Professionals - Cole Nussbaumer Knaflic (Wiley 2015)
https://www.amazon.com/Storytelling-Data-Visualization-Business-Professionals-ebook/dp/B016DHQSM2
We recommend Python Machine Learning by Sebastian Raschka on the wiki.
> this question has been asked a thousand times
Yes, it has.
Sure! One of the main areas I got a lot of my early knowledge from is just watching YouTube videos. My personal favorite is LinusTechTips (they provide a good mix of both server/workstation videos and more consumer oriented builds) but there are tons of great YouTubers out there. If you watch some of LTT's videos where they actually build PCs or work on their servers/workstations you can get a lot of knowledge.
As for reading, reddit is obviously a great place. I'm not sure how low-level you are looking to get, but if you want a great book about how computers and operating systems run on a hardware level, this book is great: https://www.amazon.com/dp/B00JDMPOK2/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1 It's a bit more about operating system code and binary and whatnot but it taught me a lot about computer science theory and was definitely very interesting.
Yes! The one I've used with success is Raschka's Python Machine Learning. Very hands-on, many examples, great for getting familiar with the basics of data science work, in my experience.
Hadley Wickham actually does lots of data analysis, got his Ph.D in statistics, taught statistics, popularized "tidy data" and "split apply combine", actively contributes to his packages, and stays in touch with the community. It's not a coincidence that his new book is one of the highest rated data science books of all time with 85% 5 star reviews.
Being fond of problem solving is a good indicator. Problem solving and executing a solution is essentially what programming is all about in the end. Pretty much any engineering degree for that matter. The good news is most STEM courseware is pretty much the same the first couple of years of college so you won't really have to commit straight away. Your classes will apply to multiple degree paths and having a few intro compsci courses under your belt will help in literally any major.
A computer science degree is (should be) geared to problem solving more than learning to write code. Writing code is the easy bit and the tech changes so quickly it is something best learned on the fly. You will be taking tons of math, studying algorithms, data structures, learning to play well with others -- that sort of thing.
Being fond of computers alone can lead one astray. The classic example is that liking listening to music doesn't necessarily lead to liking making music.
The Harvard cs50x extension course will give you a straight up taste of what an intro to CS class will be like in university. The pace is fast so fair warning.
A good armchair book is CODE. Nice overview of how computers compute.
It's a great career choice IMO. I've been at it for a long long (long) time with zero regrets. Along side getting to play with all the shiny bits, you can get a constant supply of feel good moments when you see your work actually doing something in the wild and seeing your work impact peoples lives in a positive way.
If you really want to understand how a processor works I recommend Code: The Hidden Language of Computer Hardware and Software. This is a great book that works its way through the history of the development of processors and the code that runs them, easy read and so well written!
Anyone interested in this topic should read Code by Charles Petzold. It's an accessible look at what a "code" is, how it can be digitized, and how computers can be built to interpret that code.
Not exactly what you are looking for, but it provides a great explanation of how computers work from a low-level (but not overly specific or technical).
Thanks so much!
Where do hobbies and interests go? Below Education somewhere? Sample stuff I could add:
I had sort of planned to put all this stuff in my personal website - write ups of personal projects, a good reads feed, an "About me" section, and maybe a page of my sewing/knitting creations.
I'll certainly look into adding some more personality into the resume design, it is currently the result of a google template, which is pretty blah.
Again, Thanks so much for your feedback! It's been really helpful!
If you want a good, understandable explanation of this, read <em>Code</em> by Charles Petzold. He basically walks you through building a CPU from the ground up.
It's an excellent laypersons explanation of how computers work at a very fundamental level. How you can use relays (and transistors, their analog) to read 1's and 0's and make decisions based on that. From there you get to machine language (physically encoded into the chip), and everything above that is basically abstraction.