Introduction to Programming

My first "professional" program

Hello, long time lurker of this sub. I've been wanting to learn python for a long time because I've been making computer graphics with blender 3D for over 10 years.

So a little over a year ago I decided to start teaching myself. I started with codeacadamy's python course and then worked on several small personal projects. Such as automating some stuff at work. I then did Udacitys Intro To Programming Nanodegree. I overall feel pretty confident with python now, but it's hard to gauge how good you are at something if you don't reference it with other people. So here I am to share!

So I currently work as what is probably best described as a "security guard supervisor" all though it is a lot more than that. I work at a charity with a low income housing complex in which all guests or staff are required to sign in and out of the building. This is necessary because of certain laws requiring it with charities(it's complicated). And also so roll calls can be done with the staff if there is a fire alarm.

Before they simply had a binder with a pen and paper to sign in and out. I asked around and found out that we could print barcodes easily on to our ID cards. So I figured the entire process is pretty low hanging fruit for automation. So I presented my idea to my manager and then later some directors and they approved, since it was practically a free solution, aside from my time on the clock.

I did a back of the envelope calculation and determined this program would save about 400+ man hours a year.

TL;DR: So long story short even though I'm a technically a security guard they let me write python and implement this new system. Which I've had a bunch of staff thank me for because the old way was a a lot more of a pain in the ass.

Here is the program I wrote.

I want to pursue programming as a career now so any advice is appreciated too.

How good is Udacity's nanodegree "Introduction to Programming"?

I am a beginner when it comes to programming and is thinking of taking a course on the same. While I was trying to zero in on a course I stumbled upon [this nanodegree] (https://www.udacity.com/course/intro-to-programming-nanodegree--nd000). Please advice on should I be taking this course? Fees would be INR 9800 per month. If no, what are the better alternatives?

I recommend having a look at Udacity's online courses. Their Intro to Programming Nanodegree could be exactly what you're looking for. The courses are all tailored to teach the skills tech companies are looking for.

I'm doing their AI Nanodegree at the moment and having a blast

Help critique my ML curriculum!

Hi everyone! I've been doing some research on how to get started on machine learning as a beginner and have come up with the curriculum below for myself to follow. It would be great if those proficient in ML, or even those currently learning, help to critique or provide suggestions. Additional courses, literature, programs, or advice would be greatly appreciated! It may be difficult to critique without having firsthand experience of each course or program, but I'm more concerned the with subject matter included than the courses themselves. As I go through each course, I may decide to change them if I feel that it is not pertinent to the goal or lacking in quality. There's no way I will become an expert after this, but I'm simply looking for a good starting point. I hope this will help others as well.

 

As a point of reference, I've graduated with a B.S. in Mechanical Engineering, have taken several math courses (calculus, linear algebra, differential equations), and have taken a few programming courses (CS50, Intro to Comp Sci on eDX, CS 101 at University). I'm currently working part-time as a mechanical designer / energy analyst and have 40-50 hours a week to spare.

 

For the curriculum, I've broken it up into 5 sections (programming, statistics, linear algebra, data science, and machine learning) which will be overlapping. I plan on taking 3 courses at a time starting with Udacity's Intro to programming, Stanford's probability and stats, and Udacity's linear algebra refresher while reading "An Introduction to Statistical Learning."

 

Here it is!

 

Curriculum:

Programming

1. Udacity Introduction to programming https://www.udacity.com/course/intro-to-programming-nanodegree--nd000
2. Learn the basics of programming through HTML, CSS, and Python.

Statistics

1. Stanford Online: Probability and Statistics https://lagunita.stanford.edu/courses/course-v1:OLI+ProbStat+Open_Jan2017/about

2. Broken into four sections: exploratory data analysis, producing data, probability, and inference.

3. Stanford Online: Statistical Learning http://online.stanford.edu/course/statistical-learning-winter-2014

4. Introductory-level course in supervised learning, with a focus on regression and classification methods.
5. Lectures cover all the material in An Introduction to Statistical Learning, with Applications in R.

Linear Algebra

1. Udacity Linear Algebra Refresher Course with Python: https://www.udacity.com/course/linear-algebra-refresher-course--ud953

2. UAustinX Linear Algebra - Foundations to Frontiers edx.org/course/linear-algebra

3. Connections between linear transformations, matrices, and systems of linear equations.
4. Partitioned matrices and characteristics of special matrices.
5. Algorithms for matrix computations and solving systems of equations. Vector spaces, subspaces, and characterizations of linear independence. *Orthogonality, linear least-squares, eigenvalues and eigenvectors

Data Science

1. Udacity Introduction to Data Science https://www.udacity.com/course/intro-to-data-science--ud359

2. Focuses on Data Manipulation, Data Analysis with Statistics and Machine Learning, Data Communication with Information Visualization, and Data at Scale -- Working with Big Data

3. Udacity Data Science Nano-degree https://www.udacity.com/course/data-analyst-nanodegree--nd002

4. Learn to organize data, uncover patterns and insights, make predictions using machine learning, and clearly communicate critical findings.

5. (optional) UCSD Data Science Micro-masters Program (4 course program) https://www.edx.org/micromasters/data-science

6. Four courses: Python for Data Science, Statistics and Probability in Data Science using Python, Machine Learning for Data Science, and Big Data Analytics Using Spark.

Machine Learning

1. Udacity Intro to Machine Learning https://www.udacity.com/course/intro-to-machine-learning--ud120

2. How to extract and identify useful features that best represent data, learn a few of the most important machine learning algorithms, and how to evaluate the performance machine learning algorithms.

3. Coursera Machine Learning by Andrew Ng https://www.coursera.org/learn/machine-learning

4. This course provides a broad introduction to machine learning, data-mining, and statistical pattern recognition.

5. (with job guarantee?) Udacity Machine Learning Nano-degree https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009

6. Apply predictive models to massive data sets in fields like finance, healthcare, education, and more.

 

Literature:

1. An Introduction to Statistical Learning http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Seventh%20Printing.pdf

2. The Elements of Statistical Learning: Data Mining, Inference, and Prediction https://web.stanford.edu/~hastie/ElemStatLearn/printings/ESLII_print12.pdf

 

Other (after curriculum):

https://www.reddit.com/r/MachineLearning/wiki/index

 

Let me know your thoughts! Have you taken one of these courses before? Think there's too little programming or know of a better course/program? Chime in! Would be really grateful for any feedback.

Big Thanks!

-sleepyowl

Ich hab zunächst den Introduction to Programming Kurs absolviert und bin gerade dabei den Front-End Web Developer Kurs auf udacity.com zu beenden.

https://www.udacity.com/course/intro-to-programming-nanodegree--nd000

https://www.udacity.com/course/front-end-web-developer-nanodegree--nd001

Which resource should I learn HTML and CSS from?

I want to choose only one to follow for now. Im a MIS undergrad with some basic programming background.

Which one would you choose:

1. MDN Learn web development

2. Udacity Intro to Programming

3. Modern HTML & CSS From The Beginning (Including Sass) by Brad Traversy

4. Build Responsive Real World Websites with HTML5 and CSS3 by Jonas Schmedtmann

Please don't factor money into your decision, I just want the best avaialbe resource to learn from.

I think the only thing you can realistically work as is as a programmer and/or web developer. There are many great online programs that you can complete (the really good ones, which actually teach you the material in depth, cost money, but not a lot), include, [this Udemy course, i've heard great things about it] (https://www.udemy.com/the-web-developer-bootcamp/). There is also [this Udacity program called Learn to Code] (https://www.udacity.com/course/intro-to-programming-nanodegree--nd000). It's a great program that will teach you the fundamentals and beyond of programming, after that many people enroll and complete their more complex [Full Stack Web Developer program] (https://www.udacity.com/course/full-stack-web-developer-nanodegree--nd004). Pick one or the other programs to complete and I can assure you that you will attain an in depth knowledge of programming/web development. Many people have been employed after completing such courses.

Have you explored potential courses or learning paths on sites like:

• Coursera's online programming classes
• Udacity's intro to programming
• Udemy's online classes

There are plenty of online learning resources on those websites that are much cheaper and higher quality.

Finally, I would suggest looking into an example of an entry-level software engineer job description you'd be interested in, just to see what skills/responsibilities you'd have. Then you can design a learning path that gets you those skills/responsibilities.

Something to note is that programming interviews at larger, more established tech companies, can be a whole course in and of itself. It's a little bit like studying for the SATs, where beyond the subject matter material for the test there are also a whole load of ins-and-outs about test-taking strategies.

Once you start doing interviews, you may want to watch some examples of anonymous, real programming interviews from companies like Interviewing.io (their YouTube channel has lots of recorded real programming interviews by interviewers working at Google/LinkedIn/Microsoft/Slack/Netflix/Amazon etc).

Triplebyte has also posted some pretty useful free, comprehensive guides on doing well in programming interviews.

Good luck!

I see, well probably it is more of a step by step learning. I like codecademy and datacamp for the basics, and then move into the coursera/udacity for the more advanced topics. Others have mentioned Edx, I think it will be more your style regarding what is better for you.

Edit: adding stuff now that I am in front a computer

Very easy starting tutorials:

(https://www.codecademy.com/learn/learn-python) (https://www.datacamp.com/courses/intro-to-python-for-data-science) https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-11

Longer intros (multiple courses with a capstone): (https://www.coursera.org/specializations/introduction-scripting-in-python) (https://www.coursera.org/specializations/python) (I know some of these had been mentioned before, but just wanted to compile them for you)

I'd encourage you to go through all the courses and do the capstone, since it seems to me you are serious in getting a good leg into the capstone.

More personalized bootcamps: (https://www.udacity.com/course/intro-to-programming-nanodegree--nd000) (https://www.thedataincubator.com/foundations.html) (Springboard's requires you to do a couple of required courses before, the datacamp intros should suffice) (https://www.springboard.com/workshops/data-science-intensive)

Going all the way to a masters's from Udacity (https://www.udacity.com/georgia-tech)

Packt Publisher oand O'Reilly have a good suscription for reference (https://www.packtpub.com/) (https://www.safaribooksonline.com/)

Anyway, I think 5k is an amazing budget, if I were you I'd look for the more personalized learning things, but I'd also look into a good suspcription for datacamp/codecademy and safari/packt. You are the one that knows how you learn best, and as asuch, I'd explore which one works best for you. Have fun1