It took some time, but rogersm.net can be accessed via SSL:
Since the appearance of the Apple App Store the software engineering community has a huge repository of untapped data to analyse. Although this data is compiled code (for source code we already have some projects mining open source repositories) there are some interesting possibilities that, until now nobody was exploring:
Of course this level of detail requires an advanced understanding of low level analysis techniques, but already have techniques to mine all this data and get the useful information.
And I said before ‘until now’, because after reading “Amazon Is Downloading Apps From Google Play and Inspecting Them” we see Amazon is tapping this huge amount of applications to check for good security practices.
Of course these kind of techniques should be applied in the publishing phase of the application, but because currently no app store is doing this level of analysis during publication the first case of binary analysis has been done by Amazon (a platform provider) to ensure the good use of the API.
Personally I want to congratulate Amazon for his interest to improve his platform security (and their users) doing a binary analysis of the applications.
And this time the experience has been disappointing. I have to admit I have a long time pharma experience, including supporting Clinical Trials, but this is not the point.
Frankly, the course content is too introductory, even for people with no knowledge of what is a Clinical Trial. And if this is your target, please provide a first lesson explaining
what are the main processes in pharma R&D and why clinical trials were introduced.
Also, the materials are poor. Having a voice reading slides is not the most pedagogic way of presenting content. Also, the lack of exercises (collaborative exercises would have been great) makes the course a poor fit for current MOOC systems.
So, is this a course for you? It depends, if you have a basic knowledge of Clinical Trials, probably the answer is not. The course does not provide any value over reading some Wikipedia pages.
Otherwise, it may be useful to you, if you start with this introduction in Drug Discovery, Development and and Approval.
Just in case you’re surprised on how slow things are moving in this blog: not only I’m doing some interesting R&D on analytics and big data for a new data analysis product that takes a lot of my time, but I have moved almost my internet posting activity to twitter.
So if you want to keep updated that what I’m doing, twitter is the right place.
After some weeks of waiting, the course record of the Healthcare Innovation and Entrepreneurship is public.
The experience has been interesting as it was with the venture-lab course or the machine learning course, but completely different.
The Duke felt like a class based course moved to the Coursera training platform. Less interactive between students and between student-teaching team.
The content was good, but probably too US centric for non Americans. Anyway, the healthcare world is highly localised, so that was not unexpected.
Was the experience good? Yes, the content was a good introduction to innovation in healthcare but felt slightly old. Regulatory rules make difficult to apply fail early methodologies to healthcare, but the course contents and teaching tools where extremely formal. Some references to funding would have been useful.
Did you attend to the course? What do you think about it?
If after a visit to an Apple Support Service they return your computer without the serial number set in your motherboard, this walk-through may be useful.
It is not for complete new users, but does not require shell access, so it may be useful if you are out of Apple Care or do not want to move your computer again.
If you want to comment, please use the comments in this post, not on the walk-through page.
We’re on the last lectures of Startup Boards course and from all the courses I have attended this year, this one has been one of the most interesting. And this time I think is not only Clint Korver but the community created around the course.
Of course, there are some barriers to keep the course pace: not only the difficulty to rganise management boards when the members are living in different time zones, but also the issue of executing the tasks recommended by the Management Board: basically the course is set too fast to the development of a Startup.
The main cause is probably the Stanford main course is not developing real Startups, but it is role playing the creation of new companies. But unfortunately for our course (and thankfully for us) we’re working with real start ups with a much slower pace than the course. The result is the Management Boards are moving slowly than the course and assignments are left unfinished. This is clearly an issue with the way the course is defined.
And as a recommendation, review the last lecture of the course about ethical decision making: probably one of the best of the course.
Yes, long time without any updates. I’ve been involved in the Venture Lab Course lately and it is an interesting and busy experience. The main difference with previous courses I took (NLP or Machine Learning) is the group experience. Venture Lab is a team based course and it is not possible to do it alone.
So, here I am, working with a wonderful team of people from all around Europe trying to create a great product for the Corporate World.
I’ll keep you updated!
After reading the course outline I have decided not to take the Software Engineering for Software as a Service. I find the topics uninspiring, not related to SaaS, software engineering or an university level course.
I cannot understand how a software engineering course may be specific to SaaS, but if you put SaaS in the name, please try to add some SaaS related themes to the course.
But the most surprising part of the outline is that the course is basically a learn ruby for web programming. The only part remotely related to software engineering are weeks four and five, but even in that chapters the material seems to have been chosen for trendiness rather than for teaching.
So if you want to understand what is software engineering, read any edition of Pressman instead of taking this course.
Yesterday night I finished Stanford’s Machile Learning Course. The last two lessons did not include any coding exercise, but the Photo OCR lesson was invaluable: the description of a real problem with the introduction of the pipeline, an engineering concept uncommon in academic world, was a surprise. Also, the cost related questions in the test were fairly basic, but useful to understand how research decisions modify research costs.
Finally, to Prof. Ng: a big thanks from Barcelona. It was great to go back to university and to find such a wonderful teacher.