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Some Notes on the “Andrew Ng” Coursera Machine Learning Course (ftrsn.net)
62 points by harveynick 11 months ago | hide | past | web | favorite | 30 comments

I took the 11-week Coursera course last year (and even paid for the 'verified' certificate). It was worth it, I think. I may not have a deep understanding of the different ML algorithms that were presented, but at least I know of their existence, and to what problems they are suited (and then I can look up the details when needed).

Granted, that's not enough to actually find work doing anything ML-related, as there are now plenty of experts with years of experience out there on the job market, but hey, I like learning stuff for the sake of it. I'm thinking of taking one of the follow-up courses on NN.

What made you decide to take the paid certificate route? I've browsed job boards for the past few months; but have seen that employers are increasingly looking for degrees as a minimum requirement versus having a Coursera certificate. Especially with regards to anything involving the ML space, it seems like employers are more interested in it as a supplement to a degree rather than being useful on its own.

Well, I have a BS in Comp Sci as well as an MBA. Moment of weakness, I guess. Besides, since I paid for it up front, I had that much more motivation to finish the course :)

In any case, it's on the resume. No idea if it looks good or not.

Of course, if I were really serious about it, maybe I ought to go for a PhD in CS. But at 37 years old, I'm approaching the end of my useful life as a software engineer. I understand I have to report to something called "Caoursel" on my 40th birthday, whatever that is.

EDIT: Allright, I took it because at the time I was working as a software development "SME" on a program in which AI, ML and data science terms were being bandied about by the PhDs and I wanted to be able to sit in on meetings and at least follow the conversation (And not look completely stupid. Adopting a stern look and nodding along will only get you so far, occasionally you have to speak). The course largely fulfilled its purpose on that score.

I'm a bit younger on the age range at 23, and taking some time out of school since my grades and finances weren't quite where I wanted them to be. Would you say a person who has a handful of relevant Coursera certificates and does well on an interview would be able to compete against a degree holder who also did above average?

For your case of staying current in newer tech I can see the market reason for taking it. People like Knuth who're well into their 70's still seem to find ways to remain relevant as well. What is the "Caoursel" you're referring to?

After 40 you'd be actively managed out by a company, even if you built their business from the scratch. You see it happening all the time, once you start thinking you should now reap rewards of your hard work, you'll be shown the door. Better start your own company and fight for life than to end up 40-year old unemployed burned out developer.

^ This is one person's opinion that reflects their own experience.

I am a 35 year old who has done development, and may do it again in the future. I have kept my skillset updated by taking several AI courses during a sabbatical.

If you are competing against a group that competes for roles that select for what you think is silly, you'll never win. This does not describe most startups; it may be an indicator of bad startups.

There is age discrimination, for sure. In the startup cohort study of the future, I am quite confident those exhibiting this discrimination will not be on the successful side.

Younger devs focus on their skills. Older devs focus on the value they bring to the company. Companies that focus on the latter will do better.

YMMV, we live in a probabilistic world.

It's not my experience, it's my observations on people that graduated MIT and similar top schools, created awesome things and got the boot from companies they built without any remorse from management that sensed more money to them. At 35 you are likely at the peak of your abilities and just starting decline in your employability. Try to apply to some companies online for the fun of it (e.g. practice current crop of interviews) and report back on how many want to talk to you and how many want to give you more $ than you are earning right now.

It's a reference to the 70s sci-fi classic Logan's Run :)

Also, I've worked with non-degree holders. If they were good, they managed to find employment. Though, often employers will use the lack of a degree as an excuse to pay less, which isn't right.

Oddly enough, I was thinking about that on a bus ride today. How it's both normalized to value non-degreeholders less and for compensation to plateau at a lower rate. While I do think there's a skills gap that exists, having at least one degree seems entry-level for a lot of people nowadays.

And Logan's Run looks like a neat movie, in my city we have a monthly mash-up of old films that play at an independent theater, so I'll check it out sometime.

It would definitely depend where you apply. If you have no experience and no degree, you should have a GitHub to backup your claims - and apply to companies who would dig through that. There are certain companies and industries who would not touch you with a 10 foot poll w/o a degree, but hire a degree holder who sits there and looks pretty (i.e. government contractors, consulting).

In reply to your Knuth comment...Tom Brady is 40 years old but you're not going to find many football players who are 40 and still playing in Super Bowls.

> But at 37 years old, I'm approaching the end of my useful life as a software engineer

I hope that’s not the case. 45 and still going strong...

I know MIT CS graduates with massive achievements that went long-term unemployed after hitting age 39 years. World is going insane.

It helps (unfortunately) if those 39+ year old coders stay fit and somewhat hip (god I hate that word, but if you are into, say, gaming, Game of Thrones and a recent-ish programming language, and you don't dress like you just stepped out of the 80's or 90's, it does seem to help). Additionally, MUCH more challenging if you are a parent. Fitness, jeans, sneakers, a hoodie and a laptop bookbag can hide a lot of off-putting "age" IMHO.

But at 37 years old, I'm approaching the end of my useful life as a software engineer. I understand I have to report to something called "Caoursel" on my 40th birthday, whatever that is.

I hope you are just trying to be darkly humorous about ageism because this reads like a plot point from a dystopian sci-fi horror movie.

It is the plot of a dystopian sci-fi horror movie. Literally.


Relevant scene:


Thank you. I didn't recognize the reference because I never watched the full movie. It isn't anywhere near as good as the book and I think I turned it off after a few minutes.

No problem, I’m glad to help. I also strongly agree that the book was superior in every important respect.

Since you read the book, did you also read any of the sequels?:


No. I had no idea there were sequels.

Yes. And also, yes.

Oh wow, looking at this the morning after I finally noticed I misspelled Carousel as "Caoursel." Too late to edit :)

Hi, post author here. I paid for the certificate as well. Partly out of curiosity, partly because I thought Coursera / Ng had “earned” it.

I should probably update the post to say that...

I have tried to get into Machine Learning/Deep Learning a few times, but I found it difficult to get motivated because I feel like I don't have any immediate use cases in my own personal or professional life to which I can apply them.

Even areas in which my company can potentially benefit from Machine Learning, we don't have access to vast troves of data to use as training sets. So our brainstorming sessions have gone nowhere.

So many use cases! Take the course! You can use regularization to learn from small datasets by penalizing learning extreme biased feature weightings.

For finding a use case or at work just think of any normal problem like UI or ux design, or showing someone an enjoyable loading screen or funny picture, anyone can make something okay but to solve a problem close to optimally you start to need to gather data and do ml/ai

Well, for example, can I look at the company's sales performance over the past 24 months (along with various factors such as number of sales staff on the field) and accurately predict its numbers next month?

Where would I start with this? Is this even an ML problem?

Time series data is hard, especially without lots of training examples.

Consider looking into traditional forecasting methods as a baseline. AR(I)MA based approaches with seasonality might actually be fine for you.

However, it all changes if there are structural breaks in your dataset. Look into Rob Hyndman's free online book (https://otexts.org/fpp2/) for an excellent introduction into timeseries forecasting.

Ended up founding a ml startup predicting crypto currency prices https://bitbank.nz after finishing this course! such a good skillset to have I didn't know what I would do when I started the course just that I should learn this ml stuff

Post author here :-)

Oh wow, this is right in the wheelhouse of my site... have you written anywhere about the process of setting it up / the progress you’ve made?

serious question: how well was bitbank able to predict the recent bitcoin selloff?

given that he gives only 1 day free trial, clearly he is not confident of his system.

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