Coursera announces new math courses via California Irvine

One of the obvious gaps in free online math courses was for subjects that are generally taught at the high school or early university levels. While subjects such as Calculus were "on the schedule" at Coursera and available at developed resources such as OCW, the elementary subjects leading up to it were sorely missing.

Coursera is changing that today with a pair of offerings in conjunction with the University of California, Irvine. Beginning in January, 2013, Algebra and Pre-calculus will be offered for free in the 10-week class format.

This is certainly an important step towards making free online education a complete package. While Khan Academy offers a complete set of videos for these subjects, the ability to receive feedback via grades and follow a stricter syllabus is important for many learners. I look forward to hearing reviews of these new classes when they go live.

What I'm Reading - Sept. 12, 2012

Just a quick update on the books I'm currently reading/studying/etc. Both of the books that I'm currently reading (other than my class-centric texts) are from Dover Books, which offers low-priced texts on a variety of topics.

• Linear Algebra by Georgi E. Shilov
• I picked up this book since it's about $10 and was recommended to me. I'm using it as another angle on Linear Algebra while I work through the UIS class on the topic. It approaches determinants early and often, which is very different from the other ways that I've learned Linear Algebra.
• Introduction to Analysis by Maxwell Rosenlicht
• This text was something I wanted to read in my leisure time in order to understand more of the theory behind analysis. I will need to take Real Analysis and Advanced Calculus in the coming semesters, and this text seemed like a cheap one to pick up just to get a preview.

Of course, I'm also reading class texts on Calculus III, Physics II (calculus-based), Mathematical Statistics, and Linear Algebra. Not much time to enjoy much beyond those!

Udacity and Coursera Math Courses for September 2012

Both Udacity and Coursera have officially opened up a few courses this week. Although I'm not planning to devote much if any serious time to them right now (my for-credit course load sits at 17 credits of math and physics), I'm certainly planning to spend a few minutes here and there studying what they have to offer. Here's a quick rundown of the new math-related courses that I'm following:

Udacity CS222 - Differential Equations in Action (officially open)

Coursera / Princeton - Statistics I (officially open)

Coursera / Stanford - Intro to Mathematical Thinking (not open until Sept 17)

TI-36X Pro

It's not often that I buy calculators. My last purchase was the venerable TI-86 back in the late 90's, and that calculator has served my every need for the past ~15 years.

For the Linear Algebra class that I'm taking currently, I needed a scientific non-graphing calculator. I quickly decided to take a look at what TI had in that category, and came upon the TI-36X series. Having read some reviews, I homed in on the TI-36X Pro.

The feature set of this calculator was described as "everything that the TI-84 can do, minus the graphs, for 1/4 the price," and I find that to be accurate. This little monster can handle polynomials, complex numbers, unit conversions, linear systems, regression, and lots more. It has everything I need in a scientific calculator, and I can always reach for my TI-86 when necessary.

All this in a sub-$20 bundle makes it a no-brainer if you need a non-graphing calculator. You can pick it up from Amazon using the referral link below, which supports this site. Thanks for reading!

Udacity CS222: Making Math Matter (Differential Equations in Action)

Along with the announcement that Udacity's Logic & Discrete Math offering would be cancelled, a new course on applied differential equations was announced. The course will be starting up on September 3, 2012, and taught by Jörn Loviscach with Miriam Swords Kalk, who I assume will be TA'ing and moderating the discussions.

Personally, I'm not sure how much time I will have to focus on this course. With a full 17-credit semester coming up, I may have to leave this course for around the end of the year when I will have more free time. I'm definitely looking forward to it, but more important courses must be focused on first.

The prerequisites (more recommendations than requirements) list knowledge of basic computer programming, calculus, and physics. You could tackle the programming and physics requirements via Udacity's CS101 and PH101 classes, while Khan Academy will help you shore up the Calculus. More information from Udacity's course page below:

Syllabus

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• Unit 1: Rescuing Apollo 13, Part 1 

• Introduction to the Forward Euler Method 

• Unit 2: Rescuing Apollo 13, Part 2 

• Comparing solvers, Heun’s Method and Symplectic Euler Method 

• Unit 3: Analyzing the Spread of Diseases 

• Implicit methods and stiffness 

• Unit 4: There’s Plenty of Fish in the Sea 

• Stability, sensitivity, and optimization 

• Unit 5: Antilock Brake Systems

• Friction, equilibria, and control theory 

• Unit 6: The Path of a Forest Fire 

• Partial differential equations and heat conduction 

• Unit 7: Advanced Applications of Numerical Methods 

• Chaos, software, and predictive capability 

• 
  

ST101 Completed

There you have it. I successfully completed the final for Udacity's ST101 course with 16 out of 16 questions correct. I've enjoyed tacking this subject over the past eight weeks or so. I feel that it was a great warmup for the required Mathematical Statistics I course that starts at the end of August.

This was the first course on Udacity that I have pursued to the end. I'm currently working on CS101 part-time, but that may take a while since it has consistently taken a backseat to my academic courses at the university level. I would have liked to aggressively tackle Udacity's Logic course, but that was canned earlier this week after a long delay.

I guess I'll find out soon just how good of a warmup it was. It is my hope that the calculus-based approaches to statistics will be the only "new" material that I have to deal with in a full-on university course, but time will tell!

Udacity cancels Logic & Discrete Math offering, announces applied Differential Equations course

Unfortunately, Udacity has announced that their CS221 course on Logic and Discrete Math has been cancelled. This is only a bit surprising, considering that the course was already heavily delayed.

They've chosen to instead recommend their new CS222 course: Differential Equations in Action. That appears to be an applied course that reviews some ways that differential equations are used in everyday technology and how they were used to "rescue Apollo 13."

You can see the complete announcement below.

Thank you for having enrolled in CS221: Logic and Discrete Mathematics.  Unfortunately, we regret to inform you that despite much preparation and anticipation, we will not be launching this course. 

This was a very difficult choice, but an important one. We continue to push and raise the bar on the courses we bring you.  We want to always ensure improved quality and the educational experience we provide you, our students. We want to make clear this disappointment is in no way a reflection on Jonathan, but on the Udacity team and the constraints we put on ourselves. We hope very much to work with Jonathan again in the future. 

For those of you who are looking for another math course, we recommend checking out our just announced CS222: Making Math Matter, Differential Equations in Action.  We believe this course will delight you with the higher quality bar we have set for ourselves. Enrollment is open and course will start on September 3rd.   

Continue learning and stay curious!

Rob's GPA Report - August 2012

This is the first in a series of posts that I use to keep myself accountable concerning my grades upon returning to university at the age of 28. I believe that "publicly airing your laundry," as the saying goes, means that you can't hide behind shallow excuses or the idea that "no one will ever knew I screwed up." I used those excuses when I was 19, and ended up with an education below what I should have held myself accountable for. I hope that this will help current or future students realize that anything is possible when you keep yourself accountable.


Well, the summer semester is over. Another two classes down, and many more still to go. I've completed the first of my 400-level classes (both were electives) at the University of Illinois at Springfield for my B.A. in Mathematical Sciences, which leaves about 53 credits to go there (that exact number may change). I've also still got four classes (~16 credits) to go for my Associate's degree in Math/Physics to cover the first half of my B.A. credits.

GPA this semester (Summer 2012): 4.00

Running GPA (since Fall 2011): 4.00

Courses Completed This Semester

Course Title	Letter Grade	Percentage Grade (%)
ECCE: Emerging Diseases	A	95
ECCE: Internet & American Life	A	100

Grades are in for Summer '12

I'm quite satisfied with my final grades! I was a bit worried about the final paper in Emerging Diseases, but I ended up acing that and securing an A overall (95.2%, give or take). I was aiming for A's in both classes (the other being Internet & American Life), and am glad that I hit my goal. These were the first 300- and 400-level classes that I've tackled.

Now I can refocus on Math (with a slice of Physics) for the time being. Still a couple more non-Math requirements that will need to be knocked out, but those are at least a year away.

Really looking forward to those two weeks off in a few days.

Summer ends in late July?

... for the student enrolled in extra courses, it does.

I'm glad to be done with the summer session at UIS, and looking forward to taking a much needed three or four weeks off from being a student. The final day of the online semester was yesterday, and that means I've knocked out seven upper-level credits (the first seven credits I've earned beyond 200-level courses). In the four-credit course, I'm 99% certain I've managed an A. In the three-credit course, I'm still waiting on the grade for the final paper (25% of the overall grade is tied up in that), but I'm certain I'll get at least a B (hoping for that A!).

Next up come Fall: Calculus III, Physics II, Linear Algebra, and Mathematical Statistics.

What I'm currently reading over the break:

• Book of Proof by Richard Hammack (also available as a free eBook)
• Introduction to Mathematical Thinking by Keith Devlin
• Paul's Math Notes - Linear Algebra

Upcoming MOOC: Intro to Mathematical Thinking (Coursera)

Coursera has announced another new course offering that should interest anyone studying or planning to study math: Introduction to Mathematical Thinking by Keith Devlin. Dr. Devlin is a professor at Stanford and will be offering the course starting this September.

Teach yourself Linear Algebra for free

Editor's Note: This page has been merged with other topics at my Learn Math for Free page. You can find other free resources for various mathematical topics there.

It's been about eleven years since I last studied Linear Algebra in an academic setting, and that was in Linear Algebra for Engineers (not a more general course on the subject). With a full-fledged course on my schedule for the fall (as a student), I figured it was time to brush up on the subject.

I discovered that WikiBooks (an offshoot of Wikipedia) has a complete university-level textbook -- Linear Algebra: An Introduction to Mathematical Discourse. After spending a couple of days on the beginning chapters, I can say that it is an excellent exercise-driven experience. The book aims to provide intuition and proof with regards to all theorems/examples. The exercises at the end of each chapter are designed to test your knowledge as well as your ability to think about what is happening behind the scenes.

This free book, combined with video lectures such as those at Khan Academy, is (in my opinion) one of the best free ways to learn Linear Algebra from the comfort of your own home. Definitely accessible to high school and college students (or adult learners, like myself) that want to get ahead or catch up to their peers.

There is also an extensive set of course notes by Paul Dawkins of Lamar University, available at Paul's Online Math Notes. These notes cover the entirety of a typical university-level class.

If you know of any other great resources for leaning Linear Algebra, feel free to let me know!

Summer 2012 Update: Three-quarters of the way

A little personal note: I write these update posts to keep myself accountable, and appreciate that you're reading this! I aim for A's in all my university classes. I think that is the only way to approach education (aim high). I know that some people may not agree with this, and that's fine, but I always discuss my grades with that in mind. When you see me say "I need XX points," I'm almost always speaking in terms of how close I am to getting an A overall.


Well, it's been six weeks since the Summer 2012 semester started for me at UIS. That means we're in the home stretch with two more weeks to go, and I can get a pretty good idea of where I stand in terms of grades. The two classes I'm taking this summer are Emerging Disease and The Internet & American Life. Both have been interesting classes thus far.

I'm doing well in both classes at this point. Week 6 was really crunch time in both classes; an 8-12 page final paper was due in Emerging Diseases, and the penultimate review of a recent PEW Report needed to be posted for Internet & American Life.

About the last two weeks worth of grades for Emerging Diseases have yet to be posted, but I do know that I have a 100/110 running total (about 91%, although the final grade will be out of 320 points). That final paper is worth 80 points by itself, so I should be in good shape if that turns out well. I have 22 points (out of the 320) of leeway to maintain an A.

As for The Internet & American Life, I'm currently running a grade of 55/55 (100%). The week 6 project is 15 of those points, followed by weeks 7 & 8 being worth 15 and 20 points, respectively. Class participation will make up the last 5 points. That class is a straight 100 points possible, so I need to net 35 of the 45 remaining points.

These 8-week courses are really hectic at times, and a little slip up here or there can have a huge impact on overall grades. It will really be a a relief when I finish up week 8 and can take a few weeks off before the next semester starts.

Upcoming MOOC: Quantum Mechanics (Coursera)

Coursera will be offering a Berkeley-developed course on Quantum Mechanics, taught by Professor Umesh Varizani. It's currently scheduled to begin on July 17, 2012. It is recommended that students have a comfortable understanding of Linear Algebra (you can study or brush up over at Khan Academy). See the embedded video below for an introduction from the professor.

Much like Coursera's introductory course on algorithms, I'll most likely be viewing the videos of this course to absorb some general information on the topic. I don't expect to have time to complete the assignments, as I'll still be wrapping up my summer session at UIS and ST101 over at Udacity (plus a nice two-week vacation once those are done). Still, it's great to have the opportunity to at least get a basic understanding of a topic that will change our world in the coming decades.

Link to the course: Coursera - Quantum Mechanics and Quantum Computation

Here's Coursera's description of the course:

Quantum computation is a remarkable subject, and is based on one of the great computational discoveries that computers based on quantum mechanics are exponentially powerful. This course aims to make this cutting-edge material broadly accessible to undergraduate students, including computer science majors who do not have any prior exposure to quantum mechanics. The course will introduce qubits (or quantum bits) and quantum gates, the basic building blocks of quantum computers. It will cover the fundamentals of quantum algorithms, including the quantum fourier transform, period finding, and Shor's iconic quantum algorithm for factoring integers efficiently. The course will also explore the prospects for quantum algorithms for NP-complete problems, quantum cryptography and basic quantum error-correcting codes.

The course will not assume any prior background in quantum mechanics. Instead, it will use the language of qubits and quantum gates to introduce the basic axioms of quantum mechanics. This treatment of quantum mechanics has the advantage of both being conceptually simple and of highlighting the paradoxes at the heart of quantum mechanics. The most important pre-requisite for the course is a good understanding of basic linear algebra, including orthogonal bases, eigenvectors and eigenvalues.

Free resources for learning Statistics

I've been spending a lot of time focused on reviewing my knowledge of basic statistics and seeing where there are gaps in my knowledge. I've never formally studied the subject, although I've had quite a few introductions to its various topics. With my degree requiring a formal course on Mathematical Statistics coming up this semester and another one on the horizon, I figure it's a great time to review some of the free resources available online for studying Statistics.

---

Khan Academy: Statistics

Anyone who knows me will find no surprises here. I'm a huge advocate of Khan Academy. When it comes to Statistics, there are dozens of videos on a wide range of topics. If you only use one resource to learn, this should be it.

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Udacity ST101: Intro to Statistics

I've blogged about this course before, and am currently enrolled as of the time I'm posting this. It's taught by Sebastian Thrun, one of the pioneers in online learning for the masses. His Statistics course is full of concrete examples, applications, and humor. As of Week 2, he's gotten into some of the real meat of the topic, and promises that it will get harder and thus more interesting as it progresses.

---

Coursera: Statistics I

This course hasn't officially started as of the time of this posting, but is scheduled to begin in September 2012. Much like Udacity, Coursera's goal is to offer free educational classes on topics in various fields. Their Statistics I course will be taught in collaboration with Princeton University. While it won't get you the prestige of having taken a class at Princeton, it will get you the knowledge, which is the important part in the end.

CS221: Logic & Discrete Mathematics (Udacity)

Although it's been indefinitely delayed for just about a week now, I'm anxiously looking forward to Udacity's second math-focused class. Taught by Dr. Jonathan David Farley, the intro (see the video below) covers the basics of what he'll be covering. Since I have a for-credit Discrete Mathematics on my academic schedule in Spring 2013, this should be a good chance to get ahead on the topic.

Once the course goes live, I'll be sure to update my experiences here. Until then, I'll be waiting for week 2 of ST101 and continue on with my summer coursework.

ST101: Intro to Statistics (Udacity)

This is a short summary of Udacity's new offering: ST 101 - Introduction to Statistics.


Udacity's latest offering is something that interested me as soon as I saw the announcement. Since I'll be taking Mathematical Statistics I in the fall (for credit), the ability to freely review what I know about Statistics and learn some new concepts intrigued me. With Udacity's course offerings being 6-8 weeks, and ST101 starting this week (June 25), it fit very well into my schedule so as not to overload me when the fall semester begins.

I'm had time to review about half of the first week's offerings, which mostly focus on "What is Statistics?" and how to chart and analyze data. Sebastian Thrun begins with a fictional list of houses sold based on square footage and the sale price. From this he proceeds into a concise explanation of the basic, from linearity to scatterplots to various graphing styles. All of it is laced with Thrun's typical humor and obvious love of teaching. Having taken the Artificial Intelligence course last year with Thrun, I can clearly see some of the places where his online teaching style has evolved over the past few months. He's getting better at the intricacies of a field he is pioneering, and it shows.

I've posted a copy of the quasi-syllabus for the class below. If you're interested in following along, the class has just started, so there's still time to begin with playing catch up.

From Udacity: 

• Unit 1: Visualizing relationships in data

  Seeing relationships in data and predicting based on them; dealing with noise 

• Unit 2: Processes that generates data

  Random processes; counting, computing with sample spaces; conditional probability; Bayes Rule 

• Unit 3: Processes with a large number of events

  Normal distributions; the central limit theorem; adding random variables 

• Unit 4: Real data and distributions

  Sampling distributions; confidence intervals; hypothesis tests; outliers 

• Unit 5: Systematically understanding relationships

  Least squares;residuals; inference 

• Unit 6: Understanding more complex relationships

  Transformation; smoothing; regression for two or more variables, categorical variables 

• Unit 7: Where to go next

  Statistics vs machine learning; what to study next; where statistics is used
  Final exam

Coursera Math-related Courses Starting in June 2012

Just a quick update today regarding the Math-related free courses that are starting up at Coursera this month. I'm enrolled in the Algorithms course, although I'm not sure I'll have the time necessary to truly tackle the content. I may just watch the videos for some general knowledge and skip the application exercises.

Listed below is an abridged list based on Cousera's announcement, trimmed to just include the two Math-related courses (both are computer science courses with a heavy application of mathematics).

Classes beginning this month...

Starting on June 11th (today!):

	Algorithms: Design and Analysis, Part I  Prof. Tim Roughgarden, Stanford University, 6 weeks https://www.coursera.org/course/algo
	Cryptography  Prof. Dan Boneh, Stanford University, 6 weeks https://www.coursera.org/course/crypto

On Citations and APA Style

It's amazing how a little thing like the formatting and style of citations can become a big deal. Some students dread citations, although I've always found them to be more annoying than actually difficult. There are, after all, style guides that lay out pretty much a single way of doing them for any specific situation. Sometimes they get a little confusing, but Google is your friend in most cases.

I face a situation that I'm sure most everyone faces at some point in their academic life: I've always been told to use MLA formatting for as far back as I can remember, and now one of my courses requires the use of APA formatting for citations. Not the biggest deal, but something that I'm going to need to review and double check myself on when writing the single paper that requires its use.

After some quick searching, I've found some useful resources and places to find specifics about citing certain sources (including my Kindle formatted textbook for the class).

• apastyle.org - This seems to be the official site of the official style guide. Lots of useful articles and Q&A-style posts that show up in search results.
• Purdue OWL - This was a site that I used for MLA guidance, and it seems to have a great free collection of APA how-tos as well. I highly recommend it.
• Cornell - Cornell has a nice, simple example page for various citation styles.

If I've missed an obvious resource, please let me know in the comments!

The First Day of a Short Summer

The summer semester of university classes is always an interesting experience as a student. I've only made use of this "extra semester" two or three times in my life. Previously, it was in the first couple of years of my twenties, when free time was plentiful and taking a class or two over the summer seemed like a good way to avoid having to find a job (boy, was I looking at the world the wrong way). Now, taking classes over the summer is an opportunity to not only take on more opportunities to learn, but also to (gasp!) move even more quickly towards a new career. Times sure have changed.

Today is the first day of my current load of summer classes, and there are two of them this time. Both are online, and fall under what UIS calls their Engaged Citizenship Common Experience requirement. I'll get into more details about the classes themselves in future posts.

What makes summer classes interesting? First and foremost, summer classes are compact. They tackle three to four credit hours in eight weeks instead of the usual 16 weeks that a fall or spring course would be allotted. For many people I know, this seems like academic suicide, but I enjoy the condensed and high-speed environment. I find that in longer courses that lack consistently interesting material, my interest tends to wane around week ten and I have to double my efforts to remain engaged with the class. For online classes, this is an even bigger issue, as the motivation to log-on and participate is more self-induced than when having to sit down in class and focus on the professor at a set time. If a course never gets to that tenth week, I find my engagement level to be much higher on average.

Secondly, every university I've seen limits summer course loads to ten credits or less. UIS limits a student to eight credit hours during the summer, and I think it's a wise decision. I'm currently taking seven credits, and I believe that it alows me to focus better. Compared to the regular semesters where I find myself taking 16 or 17 credits (on top of my full-time work schedule), the summer course limits allow students to knock out half a semester of credits in half the time without worrying about overloading themselves with four or five classes.

With the next eight weeks of classwork looking me square in the eye, it looks like it will be an exciting two months. I hope to keep up with regular posts here on various topics. Time to get started.

An Introduction

Welcome to Math Majeure!

You're probably wondering what the heck this place is. That's quite simple, really. It's a blog. You probably already figured that out. More specifically, it's a blog about majoring in mathematics. Drilling down even deeper, it's a blog about my personal experiences with being a math major while also maintaining a full-time job. As of the time I'm writing this, my experience in a work in progress.

I began my journey in 2011, at the age of 28. I'd been (and currently still am) working in I.T. support for about six years. While it's not a bad career, it's just not what I wanted to do with the rest of my life. Fixing computers was always a hobby of mine as a child, but I decided one day that I wanted to go back to school and get at least a four-year degree. I started in Computer Science at the local two-year community college, but shortly into my first semester back I changed my mind.

I was sitting in the second or third meeting of my Calculus I class, which I'd decided to take in order to refresh my knowledge on the subject (my last Calculus class had been around 2001-2002). I was enjoying the discussions immensely, and it was as if a spark had reignited a passion in my mind.

Looking at the class schedule for previous semesters, I noticed that most of the required Computer Science classes took place during the day. I worked full-time during the day, so these classes were out of the question (as was quitting my job, if at all possible). I could take all of the math courses I'd need at night, but not the computer science courses. This led me to one obvious possibility: major in math!

That solved my dilemma of how to get my first two years of degree work in, but presented another problem: how was I going to finish my third and fourth years while still working full-time. Most "go to school at night" programs in the area were focused on majors that led to obvious fields of employment: nursing, accounting, technical skills (the same type of fields that got me my current job in computer maintenance), and the like. I didn't want to settle for one of those, even though they are perfectly respectable fields. I wanted to do more math!

I googled, and I googled some more. I tried all types of phrases, from "math bachelors degree full time job" to "mathematics online degree." This eventually led me to the University of Illinois at Springfield's math department (UIS). They offered a fully-accredited, fully-online math degree. "Eureka!" was the first thing that came to mind, but it seemed too good to be true. This was a state university, not a fly-by-night college located in some foreign country I'd never heard of. It was also a true math degree, not one that was focused on applying to a specific field of employment or just teaching. I never had to set foot on their campus, and could keep my job the entire time I was working on my bachelor's degree. There had to be a catch, but I couldn't find one.

I continued searching for other options, but I couldn't find any that fit what I was looking for. So, UIS it was. I decided to finish up my first two semesters at community college (I would need a total of four, two of which are still coming up as I write this post), and then applied to UIS as a transfer student for dual-enrollment. I applied in the summer of 2012, and was accepted under the conditions that I finish my two-year degree on time. The plan was coming together!

My ultimate goal is to get a PhD in Mathematics. Today I don't know how I'm going to do that, but I'm not that worried. One step at a time, as they say. I'm focused on getting my four-year degree, and then I'll go from there. I'm putting the horse in front of the cart, rather than the other way around.

So, here we are today (June 2012). I've got two online summer courses lined up that start tomorrow, and four more courses scheduled for the fall semester (two in-person at the community college, and two online at UIS). I've started this blog to share my experiences and keep myself accountable by social interaction. Hopefully I'll enjoy writing it, and you'll enjoy reading it.