I would recommend this Coursera course - Learning How to Learn: Powerful mental tools to help you master tough subjects. Its useful even if you are not a student. I did this course back in August and it has helped with my productivity tremendously. The next version starts on Jan 2nd. You can read some reviews here.
You can also checkout this list of Ten Most Popular Courses of 2014.
Yale has some online courses. Some you can get certificates from, most are just very interesting and helpful to better your knowledge on an array of subjects:
They also have a youtube page here:
Edit: not even just Yale (thats just the one I went through) but this website also has tons of online courses:
Why does /u/dota2_ss talk about machine learning lol?
>Damn it feels good to win, sure, but if you are curious http://googleresearch.blogspot.co.uk/2015/06/inceptionism-going-deeper-into-neural.html & https://www.coursera.org/learn/machine-learning . p.s.
Are the bots exchanging information on how to get smarter?
Damn it feels good to win, sure, but if you are curious http://googleresearch.blogspot.co.uk/2015/06/inceptionism-going-deeper-into-neural.html & https://www.coursera.org/learn/machine-learning. p.s.
I'm about to get real jazzy on you.
Learn modal interchange (borrowed chords). It's where you can use any chords from any parallel scale source. So if you're in C major, you can add in any chords from C minor, C Dorian, C Mixolydian, etc. ("I Remember" does this a lot)
Also there's a big difference between using basic triads and using 7th chords with lots of tensions. (Example: the difference between a C major triad and a C major 13 (#11) chord or a C7(b9 #9 b13) or the difference between a C minor triad and a C minor 6/9 chord).
Here are some other things to consider: Secondary dominants. Tritone substitutions. Line Cliches. Parallel harmony (Constant structure). Modal harmony. Reharmonization. Chromatic harmony.
Learn chord-scale theory and know which scales/modes can be played on what chords. Learning all of the melodic minor modes is helpful for this.
But most of all, don't get to hung up on chords. I think melody and rhythm is more important, but chords and harmony can help bring a melody to it's full potential. I spent a lot of time learning about chords and totally neglected melody and rhythm.
EDIT: Just wanted to say that you can take simple common chord progressions and spice them up/make them your own by adding other chords in between them or substituting out chords. Take a I - IV - V for example and try adding more chords in between. And here's a free 6 week music theory class that just started: https://www.coursera.org/course/musictheory
I will call complete bullshit on this one. I took a class on Coursera called <strong>Learning how to learn</strong> (which I highly recommend btw), and they rip this opinion to shreds. You have two types of tasks. One where you use your focus mode, and one where you use diffuse mode. Focus mode is intensive and intended. Diffuse mode is what you do with intuition.
So if you are doing something where a lot of focus is required, especially learning a new task, adding ANY other kind of stimulus is the worst thing you can do. If you are doing something that you've been doing for years, and don't require that much focused attention, music will probably do you no harm.
The best thing that you can do for a focus intensive task is to really try hard for short bursts of time (30 min), followed by an activity you find relaxing. It is called the pomodoro technique.
I'm in the same boat as you, I had a very bad algo professor and I feel like I really missed out on some important topics. Luckily for us both of courseras algorithm courses are starting/have started. https://www.coursera.org/course/algs4partI is Princetons course, which has a focus on implementation as opposed to theory (everything is done in Java). https://www.coursera.org/course/algo is Stanfords course which is more about analysis. I plan on doing both, I've finished the first week of Princetons course I have to say I really enjoy it so far.
Hey, I would like to strongly recommend a course I found really useful in organizing how I approach learning.
This was a lovely course that provided a lot of practical tools and wasn't condescending. It's not rocket science, and you've probably seen bits and pieces here and there but I think they make a compelling case on how to approach studying.
Other idea would be an edX course on "Justice". It seems like a nice light survey of intellectual schools and should be fun to think about given that you have leisure.
Here're a few common paths: 1. Many people are applying ML to projects by themselves at home, or in their companies. This helps both with your learning, as well as helps build up a portfolio of ML projects in your resume (if that is your goal). If you're not sure what projects to work on, Kaggle competitions can be a great way to start. Though if you have your own ideas I'd encourage you to pursue those as well. If you're looking for ideas, check out also the machine learning projects my Stanford class did last year: http://cs229.stanford.edu/projects2014.html I'm always blown away by the creativity and diversity of the students' ideas. I hope this also helps inspire ideas in others! 2. If you're interested in a career in data science, many people go on from the machine learning MOOC to take the Data Science specialization. Many students are successfully using this combination to start off data science careers. https://www.coursera.org/specialization/jhudatascience/1
This is great, thanks. A couple resources I wanted people to see as well:
/r/philosophy has a fairly extensive recommended reading list, available here. If you're looking for an introduction to a topic, try that!
Coursera has a few philosophy classes, and at least some of these are offered by professional philosophers at top universities, and are quite good. For example, this Intro to Philosophy is a great start.
Wi-Phi is a partnership between professional philosophers and Khan Academy, and includes many great and easy to digest videos on a variety of philosophical topics.
I took a pretty interesting short MOOC from Coursera called Learning How To Learn. I highly recommend it.
It's very easy to follow, and it goes into a lot of good practices for learning, but also a lot of easy to follow science behind it, that really enlightens and encourages you to learn.
It goes into breaking down learning something, how much to study, how to study, when to study, etc. It goes into what your brain does when you sleep to "save" the things you're learning (neural connections, like the guy in this video said)
I would definitely recommend taking this free short course. It sounds like something you're interested in, and it really helped me.
The Coursera has a great course on this subject; learn how to learn
> This course gives you easy access to the invaluable learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. We’ll learn about the how the brain uses two very different learning modes and how it encapsulates (“chunks”) information. We’ll also cover illusions of learning, memory techniques, dealing with procrastination, and best practices shown by research to be most effective in helping you master tough subjects.
Were you given a syllabus or curriculum? Are you teaching for the AP CS test? What do you want the kids to get out of this class?
Personally, I think a CS class would do really well to have logic puzzles, brain teasers, and critical thinking, especially early on when no one knows how to program. It's a good way to start thinking logically and algorithmically.
But it'd be a silly intro to CS course if the students never learned programming (after all, prog languages are how we convey our ideas and incidentally happen to also run on computers :P). You'll want an easy high-level languages that the students can jump right into. I recommend Python - it's very easy to understand and there are lots of terrific resources for it.
I found this coursera course to be one of the best MOOCs I've been a seen. It's introductory programming in Python. In fact, If I were you (and if its offered again in the Fall), I'd consider having the students enroll in this. The video lectures are great, it has quizzes to test understanding, and the assignments / mini-projects are amazing. Plus, their codeskulptor site is a great thing - you can get a Python program up and running in no time (no installation hassle required)!
The mini projects build interactive games (such as pong and asteroids) with appropriate starter code. It uses its own simplified GUI library designed for first year CS students that are new to programming. The fun interactive games are a great way to keep studets engaged (rather than writing a program to compute a Knight's Tour or whether a number is prime, etc).
I, myself, learned Python from Google's Python class taught by Nick Parlante. Very good lecturer, and goofy too (the good thing). The assignments were fun little exercises for me.
Good luck! This sounds very exciting! I hope you and your students have a great time :)
you can! like @cbs5090 said, and not to sound cliche, but JUST DO IT! We have a world of information and knowledge at our fingertips now. I didn't finish college, or study any of what I currently do at school. It was all forums, reading, videos, practice, failing, getting up and trying again. and I wasn't born with a silver spoon either, my parents are immigrants from Cuba, we lived in a 1 room fucking shack in Hialeah, FL my whole childhood pretty much! My point is, you can do it! Just start now!
this is perfect place to start if your interested in online work like Google Adwords, but like this there are tons of resources for other areas of interest: https://support.google.com/partners/topic/3204437?hl=en&ref_topic=3111012&vid=1-635778572495978135-373249546
another area that is blowing up right now is Big Data i.e. Hadoop, Mapreduce, Hive, Pig, PowerBI, etc. also all free to learn and huge shortage of quality people
all of this you can do from home, or remote, or in office if that's your thing. and you could be up and running within a year!
"It is the mark of an educated mind to be able to entertain a thought without accepting it" - Aristotle
Cognitive decoupling is a prerequisite to algorithmic intelligence.
Have you seen this? https://www.coursera.org/course/mythology
Check out https://www.coursera.org/ Its an "education platform that partners with top universities and organizations worldwide, to offer courses online for anyone to take, for free" They literally have thousands of college courses covering all topics/interests. A few upcoming farm/agricultural/homesteading type courses included Chicken Welfare and Behavior, Sustainable Agricultural Land Management, Livestock Health Management, and Introduction to Household Water Treatment and Safe Storage. The first time I discovered the website I spent almost 3 hours browsing through courses. Ive been hooked ever since!
My daughter and I just took their "Beginning Programming" course using Python. It was PHENOMENAL.
I wholeheartedly recommend it.
The profs were great, the exercises built on the lectures and actually taught us more than the lectures. They weren't just rehashing the classes, they made you think and move farther.
EDIT: This one: https://www.coursera.org/course/programming1
Try Nand2Tetris. You start with just the NAND gate and build logic and arithmetic with that. Then you build a complete computer ~~with blackjack and hookers~~ and design an assembler and high-level language (including the corresponding compiler) for it. You also write a VM and an OS. In the end, you finish the course by writing Tetris for your own computer.
The materials are free, open source and always available. You can also take the free course on Coursera, starting April 11.
It may not have anything to do with that. She may simply get overwhelmed with the prospect of all that needs to get done and then defeats herself by not getting any of it done which ultimately creates a subconscious loop of 'all i have to do.' which drains motivation.
That may have angered her dad.
This free class on the nueroscience of learning to learn talks about this at some point. Maybe it will help.
They are the backbones of programs.
One of the best books (sort of THE standard book) is Algorithms 4^th Edition by Robert Sedgewick and Kevin Wayne (link to online version - free - Java oriented but available for many languages or language agnostic).
There are Coursera Courses covering exactly that subject:
For those actually interested in developing and testing gaming bots https://www.coursera.org/course/ggp starts at the end of the month.
PS: the intelligence of the bots is rarely evaluated based on the size of the logs...
For people wanting more to study, there's:
Hi all, this is Professor Martinez-Davila from the University of Colorado! The question you pose on online courses is a really interesting one because some academic scholars like myself think that engaging "citizen scholars" in online courses is a huge opportunity for advancing discoveries. On June 15th, my "Deciphering Secrets: Unlocking the Manuscripts of Medieval Spain" free, online course (a MOOC) is opening at https://www.coursera.org/course/medievalspain .
I think we are at a really interesting point in historical studies because scholars like myself are not only interested in sharing their passion for history (in my case, medieval Spanish Jewish, Catholic, and Muslim coexistence) but also want to harness the power of crowdsourcing to rebuild medieval worlds -- even digital 3d worlds!
And, I've often found that professionals in the work world do some pretty amazing historical research themselves! Equal to or better than traditional university scholars. One of my Spanish friends, a computer scientist by training, is one of the best paleographers (a reader of old handwriting scripts) I know.
Thanks for sharing this post, Roger :-)
> no purpose in putting wolf back into an animal we worked on domesticating eons ago
We didn't remove the wolf, studies have shown they evolved on their own. Take a free uni course on it if you're curious.
While we are on the subject, here is my direwolf.
Coursera gives you online access to real college courses. They don't provide college credit, but at least some of them will provide a certificate of completion is you pass the course.
If you feel like taking a free online class, Berklee College of Music is offering this one, starting Oct 13:
Introduction to Music Production
You mentionned you don't know what the reverb is. They will teach you that, among other things.
There is an actual branch of research around that, AIs that can play any game. You basically them input them a formal definition of a game and they learn to play it by themselves. https://www.coursera.org/course/ggp
> Some punters had paid as much as $200 to attend.
I wonder if they know that Coursera has a four-week course on Epidemics, Pandemics and Outbreaks by the university of Pittsburgh for free.
> 68 seems like a very small sample size
a) It isn't.
b) For a set that is small to begin with it definitely isn't.
That said, that alone is not sufficient to say whether or not their conclusions are any good. There is much more to know about a sample than its size. For example, why a sample? They must have the complete set of data to begin with...
Seriously: Great statistics courses (well, some of them anyway) are available for free on coursera.org and on edx.org. I recommend this guy and his two courses (coursera), he is a very good teacher of this subject.
You may find what is relevant to this subject in the videos of course 1, "Video Lectures", Module 3.
You have to pay to do the entire specialization, but if you just do each course separately, they're free. I did the accounting one and learned a lot.
This one is good too: https://www.edx.org/course/introduction-financial-management-acca-fa1-ma1-x-2
Well said. To add to this, another big idea behind SDN is to give the operator more control over data flows in the network. Traditional methods of controlling traffic with routing protocols often don't provide a lot of "knobs" that we can turn. For example, you can adjust OSPF costs or filter EIGRP routes in a topology. A big idea behind SDN is allowing the engineer to "program the network," which is a bit difficult to wrap one's head around.
By "programming the network," we can use a high-level language to express how we want the network to behave as a whole. This allows us to not worry about tuning individual protocol metrics, or coming up with extremely complex tuning solutions to direct certain traffic in certain directions. Let's say you're doing some maintenance on a certain section of the datacenter, and you want some of the traffic destined for those servers to be routed to a different datacenter or area of the existing DC. Traditionally, you might have to make protocol adjustments which can occasionally have unintended consequences, even when you're really careful (I'm looking at you, OSPF). With a good high-level SDN API, you can simply express this as: "I need this traffic to route this way during this maintenance window." Obviously, that's very high-level, but I think you can get the idea.
I think this is really cool, as it opens up possibilities like we see in sysadmin automation platforms (Ansible, Puppet, etc.) where you can use high-level languages to express exactly how you want your network to behave, and then you don't have to worry about precisely how that is accomplished.
Anyway, those are the things that I think are exciting. I'd recommended the Coursera SDN Class for more info. Just be warned that it is programming intensive.
There's definitely a very strong community. One of the most interesting courses on coursera is Jay Clayton's Online Games/Romance Literature course https://www.coursera.org/course/onlinegames which uses LOTRO as the core of the curriculum.
These are just a couple I pulled up from the last few years. I first heard about it in the Coursera class Drugs and the Brain taught by Dr. Henry Lester (https://www.coursera.org/course/drugsandbrain), and I don't know exactly which papers he was referring to. I highly recommend that class, by the way, it's one of the most informative classes I've ever taken, and I might as well be a professional student at this point.
what is the cost? Not going to pay for an unaccredited program when I can take a courses taught by university professors for free on the same topic through coursera. Data Analysis and Statistical Inference, Data Science, The Data Scientist's Toolbox, and so on. Not to be a jerk, just wanting to know what you offer that is superior to what is out there... and frankly not going to pay for a service I can get for free.
As another poster said, you need a strong math background. If you complete every math course Khan Academy offers, your math background will probably be strong enough to tackle most or all undergraduate Physics classes.
But from there, your interests will become more specific. Right now, you may just want to understand "Physics". But as you learn more, your interests will naturally narrow.
Maybe you want to be an expert in non-contact forces. Perhaps you're more interested in particle Physics. Even still, you might find yourself pursuing quantum Physics. Don't be afraid to specialize after you gain a basic understanding of the subject.
Here's a TL-DR to-do list of ordered steps to learning Physics:
*Learn enough math to take a Calculus class.
*Learn Calculus I. This course should do: https://www.coursera.org/learn/calculus1
*Learn about Mechanics.
*Learn about Electricity and Magnetism.
*Learn a thing or two about Thermodynamics and Quantum Mechanics.
Mostly, EXPLORE! Read about relativity, keep up with modern research (google scholar is your friend), and never be afraid to email a researcher or professor! The worst thing they could do is not respond.
> Cele mai dificile subiecte pot fi explicate celui mai lent la minte om daca acesta nu si-a format nici o idee despre ele; dar cel mai simplu lucru nu poate fi clarificat celui mai inteligent om daca el este ferm convins ca stie deja, fara nici o umbra de indoiala, ce este in fata lui. - Lev Tolstoi
Sunt persoane care datorita unui context si a unui tip de argumentare, ajung sa creada tot felul de bazaconii. Acum, trebuie sa intelegi ca astfel de persoane nu sunt incapabile sa gandeasca. Este pur si simplu un context.
O discutie cu o astfel de persoana, poate fi teribil de frustranta. Este un curs pe Coursera despre argumentare: Think Again. Daca ai timp si te intereseaza ideea de a dialoga spre descoperirea adevarului, ti-l recomand cu caldura. Nu a inceput decat de 3 sapt... si cred ca-l poti prinde din urma.
I think at this stage, the most important thing is to validate your idea, whether are there customers who are willing to pay. Use platforms like WordPress, LaunchRock, Unbounce to put up a simple site, telling your prospective customers what you are offering, and how are they different from competitors, and see whether anyone signed up, or best, pay you for it.
This is then you will start to do a prototype. I would recommend you to at least learn a little bit about programming. There are tons of resources out there (treehouse, Udemy, Coursera) that you can pick up what you need to build a prototype. If not, at least you can divide your project into parts, and outsource it to different programmers, and you will be the one putting it together. In that case, you will be assure that no one programmer can just take your idea, and yet you can still get the prototype out. But the most important thing is you need to know a little about programming.
Actually, if I am you, I wouldn't be too concern about the idea being copied. You somehow have to market the idea to your prospective customers or users. The moment you market it, and one of the user/customer is a programmer, they can easily do up a web application that is similar to your idea.
Anyway on a sidenote, there are some free resources that can help you can started: https://www.coursera.org/course/interactivepython https://www.coursera.org/course/webapplications
Both courses started in four days time. I took the first course before, and I would say it gives a pretty good introduction to programming in Python.
You forgot to mention Developing your musicianship which I found to be incredibly fascinating!
The Jazz Improv class went way over my head and I couldn't keep up, but that was a while ago, I might try it again one of these days.
There is also a brilliant course on Songwriting that gives you a great deal of information about the structure of a song and writing lyrics.
The now classic introduction to AI is Artificial Intelligence: A Modern Perspective by Russell and Norvig (director of research at Google):
It is a great book. In recent years, machine learning has taken up an increasingly large part of the landscape of AI techniques and research. Andrew Ng (professor at Stanford) has a good introduction to machine learning course on Coursera:
If you have a background in CS, those two resources will be accessible and give you a great foundation from which to learn more advanced methods. Good luck!
Evolution, as a scientific theory, does not address the origins of life at all.
And it really sounds like you don't understand the process of evolution at all. Random mutations are just one, and not ~~even the most important~~, evolutionary process of change.
I would suggest you read up on this as it sounds like you don't really understand the basic scientific premises of the theory well enough to properly object to it.
Give this a look: https://www.coursera.org/course/geneticsevolution
EDIT I stand corrected - apparently random mutations are one of the most important determinants of genetic variation.
Try these courses:
The first one is a really good intro. Unfortunately, there are not much practical exercises - just a few tests after each lecture, but theory is nice.
Can't tell anything about the second course - haven't tried it yet...
Hope this will help. Good luck.
Wow, just wow. If you want an intro of games in python try one of the best e-courses (Free) I've seen so far:
An Introduction to Interactive Programming in Python
reviews (overwhelmingly positive):
Before you pay anything. Make sure it's what you want. That page barely tells you anything about the competence of the instructors, the way and range in which materials are covered, etc.
> As game developers, we often see students attending overpriced and under-performing schools, learning outdated, inferior, or incorrect information about video game development. We think you deserve better. Electronic Gaming Education was founded by industry professionals in the hopes of training people who really want to be in the industry by people already in the industry, at a price that is reasonable. Our training is more focused, concise, and applicable to working today!
Well, you guys need to show proof that you're worth it. Specially in the dawn of free e-learning from Coursera, Udacity, Edx, etc.
Gee, broad question. But I do understand what you mean, I also did start with the guitar.
To give you some quick answer, it would mainly depend on the scale you're playing in.
To give you a much better answer, dive deep into the music theory. I'd recomend this course I once did: https://www.coursera.org/course/musictheory
There is a free online course for public speaking.
There are a few podcasts about public speaking. The best one I've found is Quick and Dirty Tips.
Lastly, there are a few small things you can try each day to ease into talking in front of people. Converse with random people each day. Make it a habit to engage at least 3 people each day. Even if it's simply saying you like the shirt they are wearing. When people are afraid of public speaking, which most are, they are afraid of being rejected. Something that helped me a lot is rejection therapy. It is a fun way to get over rejection. Perhaps not completely but it definitely is worth checking out. These things helped me, I hope they help you as well!
Edit: I did these things to help me with open mic stand-up comedy. If you have any interest in telling jokes, you should give this a try as well. Or maybe a poetry/storytelling night in your area. I don't think the nervousness ever completely goes away but the more you do it the more comfortable you become. Nothing beats "hands-on" learning when it comes to public speaking!
I would really recommend that you take this course: https://www.coursera.org/course/stats1
It is free of cost. Perhaps then you would understand how to choose a sample when it comes to statistics.
The death rate of 7.35/1,000 is for the entire population. You have brilliantly extrapolated it to the group of people involved in the Vyapam Scam and are then expecting the same rate to hold true. That's not how any of this works.
I can see your desperation to defend BJP, but come up with a scientifically sound and logical explanation.
Well written: pulls together a couple different well known ideas in statistics and psychology and examples.
Will we stop interviewing people? Of course not, as the author undoubtedly knows, people think they will make the right decision and will refuse to give up control. Aside from regression towards the mean, in general, we almost always overestimate our ability to regress and compare / rank complex models.
As I am sure he will allude to in his next post, using models is a great way to improve the decisions we make. By explicitly stating the factors that matter to us, we will be much better at making a decision as we won't be jumbling around a bunch of random unorganized information in our mind. The example in the post was a little extreme, though.
However, should we stop interviewing people? No. When using a model as I described, including subjective information (shyness, assertiveness, tidiness, timeliness, etc.) is perfectly fine. By explicitly stating it and giving it a weighting, it will simplify your thought significantly. By not interviewing people, you lose the ability to ascertain one of the most important parts: how well you enjoy working with them (and potentially how well everyone else does and how well they work with the team).
Of course, one could potentially just put that as the most important thing in the model, but generally that never happens. Our gut feeling is mostly defined by the subjective observations, but when we are forced to rank them, usually we get more level headed.
> She'll soon be 5 and still doesn't speak
I know a kid who had delayed speech, to about 5. He's a chess champion that travels around the country beating other kids at chess now and he's just starting third or fourth grade.
Doctors will say no, but I say yes, get your kid on the cheapest PC you can get, teach them to text you, teach them to type, teach them to read, everyday before breakfast.
Also teach them with a pencil. Write them a note that tells them what is for breakfast and that you love them. Repetition like this will get them to start reading. You don't have to do a lot of writing, like four or five small words a day like numbers and names. You write with a pencil how it should look, let her trace over it. Let her make mistakes, might be a year before she's better than you at it.
Give her opportunities both at typing and writing, everyday, at least 10 minutes, then eat and see what happens next. Writing develops an different part of the brain than using a computer, be sure to keep a balance.
Maybe this free class on Learning to learn will give you some incite on how to help her.
It isn't "blank". The network is there. It just wasn't "trained" on real-world data, which simply adds and removes and strengthens and weakens synaptic connections. But it's not like it's not connected at all to begin with - of course it is! So it will be in some state. Not a state representing real world experiences, but it will "be". The hardware is pre-arranged an pre-wired for our world - meaning it does reflect the world in a sense. If you just took any neural network with random connections no amount of training will get the same useful result. Hardware and software are one, and the genetically determined setup before letting it loose on sensor data is essential. There's a reason why beyond a point determined by childhood nutrition etc. genetics determines max. intelligence.
I'm not an expert, but I did take a neuroscience course after having taken many preparatory classes before that. I can recommend https://www.mcb80x.org/ as basis before attempting the course linked first.
I haven't done any of those online courses personally. All I can say is that the best piece of self study I ever underwent was:
It really is excellent.
Oh I do like Scala-chan. Scala tries to marry object-oriented programming and functional programming; hence the heterochromia. She is the beloved imouto of Java Onee-san as Scala also runs on the JVM, so you can use Java libraries. I don't know why she has those spikes on her boots though, maybe I should learn more about her.
Andrew Ng's course was incredibly well done. I took it before he started Coursera, so I'm not sure how it has changed since.
Neural Networks for Machine Learning would be my vote for the best. It assumed a working knowledge of calculus and linear algebra and went deeply into the math behind various types of Neural Networks as well as various topologies -- include the practical implications of the differences between them. It also was the first place I ran into recurrent networks, which I still haven't found a very good technical explanation for outside of the course.
The final lecture hit on some of the more interesting current research going on in the field. Absolutely not suitable for a first course -- but excellent to really dig into Neural Networks and Deep Learning.
the way he talked was straight out of a negotiation textbook, the dude was a master negotiator for sure.
I highly suggest everyone here takes as many negotiation courses as possible; here's a free go-at-your-own pace version I'm going through: https://www.coursera.org/learn/negotiation-skills/outline
edit: an word
Check out the reading lists for classes by Andrew Ng at Stanford. He co-founded Coursera and offers most of his courses online for free. His machine learning course is a classic over in the ML subs and his CS229 course was probably one of the most popular in the CS program when he was professor because it had many practical exercises and examples, including stock trading.
Free online course (you can go through it any time, but have to register to get a certificate at the end and chatroom help from TAs): https://www.coursera.org/course/ml
A more specific course I would take after the general ML class above: http://wiki.quantsoftware.org/index.php?title=ML4Trading
We are always negotiating, everyday whether you like it or not.
If you had two identical situations and all merits are the same, and you could achieve your goals safely and ethically by just adjusting your argument and presentation, would you do it?
Take this course and change your life.
Also, I recommend reading the book "How to Win Friends and Influence People". I hate the title of the book, because it comes off as pretty underhanded and manipulative, but it's just the opposite. I like to describe this book as giving basic social skills for getting along with people.
This book teaches you basic social skills that you may have most of, but perhaps not all of it. For example, call people by their name and remember it. Don't talk about how great you are, but get the other person talking about how great they are. Get to know the other person and appeal to their needs and wants. Remember details about a person and bring it up occasionally. Never bad mouth a person or anyone for that matter. Smile! Etc.
Negotiations and that book combined have changed my life and have gotten me further toward my goals ethically and honestly in a way that pure academic knowledge and full resume couldn't do alone.
Here, this one is free. I checked it out and it has everything you need. https://www.coursera.org/learn/negotiation-skills
Actually, coursera has A history of the world since 1300 starting in two weeks, and The Modern World: Global History since 1760 sometime in the future.
shameless promotion: /r/OnlineEducation
edit: And I forgot Greek and Roman Mythology, starting in a couple of weeks.
I'd suggest taking a look at the free Data Science Specialization offered in Coursera. I've only tried the first two courses, but found them challenging enough with the added benefit of encouraging individual research to complete some of the assignments (they don't hold your hand like many MOOC do). If I'm not mistaken, the courses are running throughout the whole year, so you can just sign up for whatever level you're comfortable with.
Sounds like its a culimination of boredom impacting self-worth.
Why not show her a free online course on https://www.coursera.org/ that matches one of her interests? I'm enrolled in a couple and its really nice to have that sort of extra information to keep me busy during slow times.
If a part time job isn't in the cards due to the time schedule, why not look into volunteering opportunities. Surely there's a library, sports league or church nearby that she's expressed interest in before.
Also, there's meetup.com, which is pretty good for expanding social circles.
Don't forget about date nights. You don't have to spend a ton of money going out. How did you guys date when in college? I bet you didn't spend alot. Or stay at home and have friends over for game night with some cards, board games, some wine and good music.
Free education for anyone smart enough to enroll
Protip: Before you start making claims that macroevolution isn't supported by science, do some research so you don't sound like a cunt.
Edit 2: 4 points 20 minutes ago... awwww yeah
Khan Acedemy may be able to help you brush up on your maths and physics.
Coursera might be a good place to start with mechanical engineering.
Check out the latest Coursera course called "From NAND to Tetris." Teaches you how to make a Tetris game starting from first principles. I haven't gotten very far in it yet because I have no free time, but it demystifies this area of computing quite well.
Computers are abstractions built atop abstractions. It is staggering and utterly humbling how much stuff is in between a basic logic gate and a graphical program.
Coursera An introduction to interactive programming.
Programming course in Python with heavy game focus. Oregon trail type programming included.
Looks like it started last week - perfect timing :)
Change means getting cooler or warmer than it has been previously. This will depend upon your location and the features in your area. If you have an hour or two a week to spare for the next month, take this Coursera course on the climate in the great lakes region offered by UW - Madison. It is a very reputable university, I studied math there. I think it will give you some insight.
I really liked this course: https://www.coursera.org/course/algs4partI
I recommend reading the course book (written by the lecturer) as you watch the videos.
You can find the part I and part II lectures on thepiratebay.
Just a PSA to all interested in how food is grown here in the USA.
I recently signed up to a free course about the US food system in relation to public health. I would recommend everybody, from skeptics to food system activists to take it. the course goes into the history and politics of the way we eat, how we grow our food, and the environmental and climate changes as a result of those choices.
the course will help those make informed decisions in the way they grow/shop/eat food, as well as filter fact/fiction while engaging in a food discussions anywhere (and such as here on reddit).
e.g., Did you know the reason why china (and possibly other countries) grow soybeans in the amazon basin? they do it in order to tap into the largest source of water on the planet, water is a scarce resource for many countries, and in order to grow enough farm animals to feed a growing economy, you need a lot of corn and soybeans, and that requires a lot of water that china doesn't have. the externalized cost of farm waste, pesticides, etc is also passed onto the amazon basin.
Science is my life. Currently doing Coursera's Galaxy and Cosmology course which began today, Computational Neuroscience and a few others.
PSA to anyone thinking of taking Computer Science 101: roughly 50% of the exercises for the class are not functional. All of the lectures work to my knowledge, and some of the exercises do work properly, but I was disappointed when I found out that not all of the content is available at the moment.
This is Jeff here, from Simply Statistics. Roger's course was designed to teach the mechanics of R. I know he made a pretty strong effort to help folks who didn't have much background, but obviously there is variation in backgrounds. He would definitely love feedback on the course.
If you want to learn the statistical component, my course in Data Analysis: https://www.coursera.org/course/dataanalysis is the natural continuation of Roger's course. Hope to see you in that one!
Andrew Ng is rather famous for being one of the forerunners of free online education. As such, you could check out his machine learning courses, with lectures online. http://ml-class.org/ ... https://www.coursera.org/course/ml
Andrew Ng also works at Google X labs. Likely in conjunction with the self driving car along with Sebastian Thrun. Almost certainly in part due to seeing Andrew's efforts Sebastian Thrun is starting a full online education system called Udacity. One of the courses is AI: Programming an artificial Car. This is not what I'd call introductory though... it depends on your level of CS knowledge.
Hope that helps :D
My spanish sucks too much, so I hope you don't mind I reply in english... I studied computer science and worked as a research assistant at University and also taught courses in Software Engineering there. I think a common misconception is people thing that learning to program means learning a programming language - this is just a minor part. The essential thing to learn are the concepts. Once you know the concepts, it is super easy to learn a new programming language, as they basically share them across the board. So I wouldn't focus too much which language is used in a course, but if they teach you the fundamental concepts or just show you 'how to construct a nice looking user interface in language x'. (When I was studying, in the first 4 semester you came into contact with a lot of programming languages from assembler code over c, lisp, haskell, scala, smalltalk to java - the languages itself just serve to show how concepts are actually implemented in the language). The good thing is that there are a lot of free courses available in the field of computer science/software engineering, so you don't need to spend a pesos, just invest some time. If you have a basic level of english (which is really useful as most documentation in the field of software engineering is also in english language), you might want to take a look at: https://www.coursera.org/courses?categories=cs-programming - there are tons of free courses from content for beginners to pretty advanced courses. Hope you find something useful there and enjoy programming :-)
You might like to check out the "Introduction to Music Production" course offered FOR FREE from the Berklee College of Music (yes THE b.c.m.). I completed it and it was superb. All at an entry level.
It is offered via "Coursera" and is totally free. The teacher of this particular class is great and very competent. He is a Mohawk sporting actively gigging Bass player named Loudon Stearns with SEVERE chops. I suggest that if you're a starving musician like myself, you apply for a grant and get the Certificate.
You might even consider the "Modern Musician" specialization course. four classes all meant for the entry level musician. Here's a link to the "Introduction to Music Production" class. "Introduction to Music Production"
Can confirm. R has changed what I thought was possible. I'm never going back to Excel for data analysis. Well, Excel is still convenient for the basic stuff.
I recommend the MITx course to get started off: https://www.edx.org/course/analytics-edge-mitx-15-071x-0
After that, consider taking the Stanford Online course: https://lagunita.stanford.edu/courses/HumanitiesandScience/StatLearning/Winter2015/about
The first one starts off with the basics and hands you datasets for you to work on, which makes it a very fun and practical class. The second one goes more in-depth into the theory and more advanced methods. I took the Stanford course first and was utterly confused because I had no background in R... but the MITx course does not assume any prior knowledge of R or statistics. I find myself going back to the Stanford page for re-learning the complicated concepts even after doing the MITx course.
If you are very mathematically inclined, you can take Andrew Ng's course: https://www.coursera.org/course/ml This one is insanely complicated and goes very in-depth with the mathematical aspect of data analytics. Personally this one is beyond me... I can't understand what's going on.
Rice University has a Principles of Computing MOOC series in Coursera, and it's fantastic and free. It's divided in 3 parts:
An Introduction to Interactive Programming in Python. It's an introduction to programming course, but focused on programming video games. The final project is an Asteroids clone.
Principles of Computing. Covers the background you need to go full-on into algorithms, and covers more advanced Python parts like lambdas. It's basically an overview of computer science. In the projects (graded) you'll code stuff like Monte Carlo and minimax machine players, and a Fifteen Puzzle solver.
Algorithmic Thinking. Full-on algorithms course. Big O notation, complexity, all that stuff.
Here's the page of the specialization: https://www.coursera.org/specialization/fundamentalscomputing2/37
Right now there are countless MOOCs in computer science. Check edx.org, coursera.org, and udacity.com to see what's available. You'll find iOS and Android development, cryptography, cloud computing, specific programming language courses, paradigms, etc, etc, etc.
I've been working my way through Learning How To Learn at coursera and in a short time I've noticed a marked improvement in my ability to retain information.
Take that Coursera course: https://www.coursera.org/course/ml From Andrew Ng it is free.
This is a pretty good starting Point: http://jmozah.github.io/links/
Look at http://scikit-learn.org/stable/
and have fun ;-)
There's a course of Coursera about that: https://www.coursera.org/course/digitaldemocracy It explains the main problems the election system has to solve and the problems that have actually transpired during various electronic voting elections.
I took it and it made me very cautious about the whole issue.
Not really, you could get into making 3D models in blender and animating and such. However you can't do anything with that without learning how to program. If you want to mod you're stuck learning how to program. This is where I learned, this is where most people on reddit suggest to learn from.
Check out /r/learnprogramming or /r/learnpython
For R, there is recently started course which you can take for free
Andrew Ng class is a really good introduction to machine learning
Jason has also written excelent guide for starting
You sound like someone that would love to check out Coursera's An Introduction to Interactive Programming in Python which is a free seminar offered by the fantastic Coursera project.
I'm having a hard time making sure I don't enroll in tens of dozens of those myself, found this Python one today and it puts me up at 10 courses for this semester. I wish I had been this active when I was at University myself...
Coursera also offers free courses online from other university such as Stanford, Rice, and Princeton. Make sure to check pre requisites (because some do require subject knowledge). Not all courses will send you certificates of completion, and like Edx these are not accredited courses.
But they are there for those who want to learn. Which is awesome.
You might also like the free cryptography online lessons by Stanford: https://www.coursera.org/course/crypto
too bad it started already like a month ago but I'm sure they'll do this again. These courses come with practical assignments and exams (ofcourse multiple choice), all for free! Some of the top guys of the field are at Stanford, and they give many more courses.
Check out this free course from Stanford, Software Engineering for Saas. Starts on the 18th and is quite promising.
I'd agree with looking at Sinatra. Tons of sties and apps have used it, many of them integrating existing APIs.
Go learn how to learn. Sign up now for the current window. The video lessons are short and easy to digest, but invaluable in teaching you skills you need. More importantly, you need to put those skills into practice.
Yup. So I took an online course from Duke University on www.Coursera.org called Think Again. It is a critical thinking class. The course is free and even if you don't want to analyze everything you read and hear you learn how to very quickly see if it is even a valid argument.
This course is currently active. I am working through it now. Week 4 lecture videos will go online this Sunday. 5 week course. Most helpful theory information I have found so far.
I can't recommend this Coursera online course enough: https://www.coursera.org/course/musicproduction
I'm not sure if you're looking for something that extends through 6 weeks, but it's definitely an amazing material that covers all the basics. The course already started on April, so you will have a month of catching up. But it's definitely doable if you have time.
The second recomendation is The Recording Revolution blog: http://therecordingrevolution.com/blog/
Graham is very passionate about his teaching. It's not so much about the techniques, but more about the right mentality when recording/mixing and what to aim for. He focus on home recording, so it's perfect for you who is just starting with minimal gear.
I strongly recommend going through either Dan Jurafsky and Christopher Manning's Coursera or Michael Collins'. They both treat the field from a different choice of emphasis on theory, and the material in both ought to be mastered by anyone looking into doing research in NLP. It'll give you the general idea and common frameworks used, and a surface level understanding of the many different problems encountered.
Ongoing research is often more about applying the most recent algorithms developed in (statistical) machine learning, so you'll also need to dig into more general machine learning courses if you aren't familiar with them.
Sedwick teaching algorithms in java, intermediate level, free, next session starts mid june. The problem sets are difficult, but regardless just watching the lectures would be informative.
First up - while it's great that you got a lease of life and all, start looking for a new job now to brace yourself just in case. Trust me, the job market is a lot tougher to crack if you aren't in one while looking.
With regards to consistency - I've learnt some important lessons by watching the lessons on this course and one of them that's helped immensely recently is the concept of "chunking". For everyone else - this is one of those MOOC's you should definitely check out if you want something "productive" to read while you're on your porcelain thrones or have some time to kill.
When it comes to work, no matter what it is, think of it as a series of smaller actions and write them all down (if you're a programmer, this has the added bonus of being almost exactly like an algorithm by nature). Use an notebook or, if you're more tech savvy, an app (I suggest wunderlist because it has a really satisfying bing sound).
As you do stuff, cross them off the list. Turn it into a game with set rules - 10 crossed off things means I reward myself. If I hit my weekly target of 70 crossed off things, I go for a movie and enjoy a lazy Sunday off.
If you're like me, you'll find that crossing stuff off a list of stuff to do becomes quite satisfying and seeing a full page of crossed out stuff (even minor shit like "Buy eggs" or "darn green shirt") is the motivation that keeps you going ("Look at all this stuff I did!"). It also helps immensely for absent minded people too - that little notebook of things to do becomes as important as your wallet and you learn to focus.
TL;DR - Chunking and Gamify your work.
Link to just the arduino course on its own.
And a note to those unfamiliar to coursera: I realize that it lists prices for the specialization. However, if you just wanted to take courses individually (which is my plan) you can take them each for free; you just won't get a certificate.
You don't have to be an illegal immigrant, there are still options. Sit down and take a few deep breaths. There are legal options and you can let your family work on their end. Call them up and get them to work on it.
About your family in Mexico, do they have a victory garden? If you can't afford to buy food you might be able to get some chicken wire, pots or milk jugs, good quality soil, and seeds. Planting some food plants on a balcony won't replace other food sources, but it can buy you some space in your budget.
Your English seems pretty good. Even if going to college isn't in the cards right now you can still keep yourself in practice using free services like Coursera. The classes don't count to a degree, but they are a good way to learn anywhere you have an internet connection.
I don't know if there is a business incubator or accelerator in your area, but that's something that you might want to look into. If there are no jobs for you, then you should make jobs for yourself. Starting a business might be hard, and I have no idea how to access capital in Mexico but figuring that out strikes me as a way to make everyone rich(er). You're smart, now is the time to see if you can work. If you can do both then very little on this earth can stop you.
How about with no money! Here, let me point you towards some websites:
The first two offer free online courses from actual universities, while the third is more of a tutoring website that's good for catching up on subjects and filling in the gaps.
You can use these to build marketable skills and then start looking towards a better paying job. You just need to keep in mind that you won't get a degree out of this avenue of education, and the certificate programs they offer mainly aren't worth it... however, once you land an interview you get a chance to show that your competence and demonstrate that you're capable of doing the job. As far as getting the interview, use whatever skills you gain from the sites to put together a portfolio. Many people with degrees still don't know what the fuck they're doing, so if you can put together a good portfolio many employers will look at you just as seriously as someone with a degree.
The other selling point of this avenue of education is that you can prepare yourself to absolutely nail some college courses. I know that seems to go against what you're saying, but if you go to community college and just take the bare minimum to get a pell grant you can end up getting more grant money than you spend on school as long as you approach things the right way (getting school books off amazon instead of the campus bookstore when possible, for example). The great thing about grant money too is that you get a check straight up, so if you can find some scholarships you can use them towards paying school expenses and then use all the grant money towards living expenses.
TL;DR Stay away from paying for universities. Look at community colleges, financial aid, and self education.
If you're interested in song writing I highly suggest taking this free course from Coursera:
You'd be amazed at all the little tricks there are to song writing.
First of, recording a drum kit with one mic, especially the kick with a sm57, can turn out to be quite the challenge. I'm not saying it's impossible, but depending on the sound you're going for it might take a while to get enough low end and punch through such a general purpose dynamic mic. Just so you know.
Try to imagine as closely as possible the sound you're going for. Look for reference tracks not just as a whole track but with a specific instrument in mind. As in "I like the bass sound in this track" or "the snare has so much punch". After you've done that for all your tracks, start recording. After a while, you will hear just what the mic and the room you're recording in sound like and how close you can come to your imagined sound. Adjust your expectations accordingly.
As for the recording order, I recommend this (assuming the songs are written on guitar): guitar guide track -> drums -> bass -> guitar -> guitar overdubs -> vocals -> mixing. When you separate the parts of your projects, you won't get lost as easy. In Ableton, decide early if you want to work in Session or Arrangement view. I recommend arrangement view.
If you're feeling stuck, Ableton have just released a book on production strategies which I have heard very good things about.
Check out /r/ableton and /r/abletonlive, the free courses on Ableton and music production on coursera.org and start experimenting!
Check out Algorithms 4^th Edition by Robert Sedgewick and Kevin Wayne (link to online version).
It is basically the standard book on algorihms and data structures.
There also is a two part Coursera course by Sedgewick and Wayne.
Just a PSA for anyone who didn't go to uni or went and didn't do an argumentation/reasoning skills/informal logic course. Coursera's offering Think again: How to Reason and Argue, the next one starts on the 5th and lasts 12 weeks, it's free of course.
If you ever wanted to know how to refute a straw man or wondered what an ad hominem attack was, you'll get that and more. Challenge: I scored 87%, probably could have scored higher with a bit more effort.
If you're interested in this era of history, the things that fed into it and the outcomes, there is an excellent Coursera course that I can recommend: https://www.coursera.org/course/modernworld It's a truly fascinating 14 week dive into what has shaped the world since 1760.
Take a look at the upcoming Bioinformatics MOOC; they run "MOORs" along with the MOOC, where a MOOR is a "massive, open, online research project". Not only are they projects you can work on at home but they are genuine research problems with scope for new work.
If you wanted to you could of course do the MOOC, but there's no obligation, and you can access the research project without completing the MOOC. You do not have to wait for the next MOOC to start (September 15th), you can access the archive for the previous course and look at the research projects there, but it might be more fun to take part in the new ones so you can work with others.
You might also want to check out Rosalind, some of the problems there are quite good fun and will allow you to build up a portfolio of code solutions.
I did that course, but I really don't know why they designed the course so bad. The prof seems to be a nice guy but he can't teach. Basically he is just reading over a text file. I find that course really boring.
I really liked this course on Coursera. Although OP is not looking for video tutorials, but I really recommend this course. You get to build easy but functional apps really fast. I followed this course and another youtube channel and in 2 months I built an app which connected(via BT) to several sensors, uploaded the sensors data to a dropbox account synced with another device and a web application. and alot of other features on the android app. My major is mechanical engineering and this was my first real app. But that course on coursera really helped me to understand basics of android in less than 10 days.