Insight Data Science

In the second half of 2018, I was looking for ways to upgrade my skill set. What the IT industry has taught me over the last 3 years is to constantly keep updating myself with latest trends and technologies to maintain employability & relevant. I was... Read More trying to find something that would be simple enough for me to start from scratch as well as complex enough to teach me skills to be able to solve real world scenarios and problems that I could face in the industry.
In recent years the rise of MOOCs has been phenomenal, offering learning material across multiple domains and discipline across geographies for a fraction of price. More importantly, owing to the enrolments in MOOCs the students also get to connect with peers across geographies and hence expand their professional networks. I have closely checked the courses in the top 3 MOOCs and looked into their course materials. I wanted to experience Machine Learning concepts and see whether I would like to continue with this as a career option.
Why I finally chose Udacity out of the top three is owing to these three distinct reasons:
1) The introductory courses which act as pre-requisites for the main course (Machine Learning in my case) are very well explained and instils the concepts very clearly so that the same can be used in the future.
2) The course material is easy to follow and the Udacity community is pretty big and extremely helpful (In form of Udacity Forums/Communities, Nanodegree channels in SLACK, blogposts in Medium etc.)
3) If the above 2 points were not good enough to convince me to immediately enroll, the next point certainly did. A limited time offer was going on the Udacity India site, where the Machine Learning Foundation Nanodegree was being offered for a big discount. Well, that was the final catalyst.
The overall experience over the last 2 months have been extremely wonderful. Although the courses are self-paced, there are tentative due dates for each module which always ensures that you are constantly in touch with the course material. Based on my experience, having worked on multiple programming languages in my career, the first module on Python programming passed on like a breeze. The reviews on project submission has been really helpful and the communities are awesome. However, the learning challenges started flowing in from the second and third modules when descriptive and inferential statistics knocked my door.
I had previously studied statistics when I was in school. So, starting again with all these concepts packed up in one module initially seemed too much work! However, the instructors were really motivating and the videos were pretty well organised to ensure concepts are slowly built up. Also hands on exercises after every single module ensures that you clearly understand what you are learning. The initial phase quickly bore off after I started putting a little extra time and effort. Once the same was done, I felt really confident with what I had learned. Whenever I would see data in a spreadsheet, I would literally start planning in my mind the type of analysis that could potentially be performed. The really good aspect about the courses in Udacity is that you are expected to build up your concepts and be strong enough to face real world scenarios once you have obtained your Nanodegree.
Another question which I usually receive from my friends when they hear that I am enrolled in a Nanodegree program is whether the Nanodegree program really worth it. I bet a lot of you would have the same question.
Well I cannot answer it simply as a Yes or No. Rather let me explain you a few points which should help in understanding the scenario.
1) You get to list the Nanodegree in your profile in LinkedIn and your resume thereby highlighting the fact that you have been associated with an organisation and have completed certain assignments and gained specific knowledge on a specific skill set. For employers, a candidate that showcases skill set is lot more job worthy than those who don’t.
2) The Nanodegree Program keeps you motivated to complete your course once you have enrolled. Just like a conventional degree, completing the course will give you enormous satisfaction for the hard work. It will also give you the confidence to highlight your new skill set.
3) Udacity provides a state of the art course material along with real world data sets and files for analysis. While you are working on the Nanodegree program, you can decide to showcase your findings in your blog/website and play around with the datasets and files to freely create/analyze something that you had not been asked to do in your course. This will not only help you to explore your skillset, highlighting the same in your blog/website will be an added advantage for highlighting your skills in the next job interview.
4) The big multinational companies have started prioritising candidates with additional certifications & determine the competencies and skill sets of an associate. Hence a Nanodegree may allow you to switch career path within your current organisation itself.
5) Last but not the least, the feedback that you receive from peers all around the world as well as mentors help in building your professional network as well as builds up your competency.

I am a full-stack developer with over 8 years experience. I have maintained, developed and launched multiple projects on different business.

My current toolset includes Python, JavaScript, Java, HTML5, CSS, Docker, Vagrant, Power Center ETL, BI Applications,... Read More SQL, PL/SQL, Shell Script and all the other various frameworks, libraries, and technologies related to them.

Feel free to ask me any questions. I can help you in your project in all from the back-end and front-end web development to fixing the design and installing & configuration of the application on staging/production environments.

I had enrolled for Data Scientist Nanodegree. The pros of Nanodegree that you get an experienced instructor. The tools are very helpful to complete the course and projects, you just need only a browser and rest Udacity take care of that. The career service... Read More also very good and the customer service also good. The cons of Nanodegree are that you can't get job It is very rare in case you get any opportunity. The cost of Nanodegree is also high If your family income is low. 

Very good experience in learning data science and coding I learned a lot and then applied in my work content Appreciated the opportunity Faculty, program curriculum and support Always there to support on the job support and further opportunities Will... Read More recommend

I know there are other Insight fellows lurking around but I'll bite.

I'm currently a fellow in the Health Data program in Boston. It's a seven week program. There are no "classes" as part of the program, it's mostly small workshops and peer-to-peer learning.... Read More This model worked great for me, I learned a lot from my fellow fellows. More that I anticipated learning. By in large, though, the biggest thing about the program is the network you build. Insight has connections to local area companies and can put you in front of the right people when it comes time to look for a job. Many companies in Boston have Insight fellows working for them, so it is a self-reinforcing processing.

Most fellows would say that it's intense. Week 1 is spent brainstorming project ideas ,finding data, and presenting your project idea at the end of the week. Week 2 is spend implementing your project (which probably includes a web app), and to deliver a minimally viable project by the end of the week. Week 3 is spent doing more tweaking of your project, with the deliverable being your final product. Week 4 is spent practicing your presentation of your project (which you will present to companies). Weeks 5-7 are spent demoing your project at companies and prepping for interviews. Weeks 7+ are when you start to get calls back for interviews. So yes, it's fast and intense.

In terms of the too good to be true bit: I can speak from my own experience in my cohort. We have 18 people in our cohort, and we are a little under two months out from the "official" end of the program. 11 fellows have been placed at companies so far, with a 12th most likely on their way out. In terms of job searching, that's pretty rapid pace from unemployment to employment.

I'm still looking, but the program directors continue to advocate for me at companies they have connections with (I have an interview Friday, actually). You are a fellow till you are employed, technically. Even though the program officially ended, most people kept coming back to the office for studying and practice. I feel very supported, and I feel certain that those of us left will find jobs at least within the next 6-8 months.

I don't know how accurate the 100% placement rate statistic is, but given what I've seen, I really have nothing bad to say about the program. I'm glad I did it.

As a 2014 Insight Fellow, Insight is fantastic and I don't say that lightly. The two best things I gained through Insight are:

an instant network of new data scientists at top tech companies who are bright, enthusiastic, and hard-working, many of whom... Read More I'm still in contact with today
open doors to any tech company through Insight's reputation (including my current position)
If you're considering applying for Insight, I strongly recommend it. Even coming out of Stanford with a Physics Ph.D (one of the most desired majors for data scientists), I don't think I would've been able to break through from academia to industry on my own. Insight is an incredible resource for those trying to make that transition.

TL;DR

show up, work hard, make a bunch of friends, get a job

It's a very good program and it was a fantastic experience. The biggest value, by far, is the network/access it provides (even if you could get a data science job without Insight it would still probably be worth going). I don't think any of the other... Read More data science bootcamps compare in this regard. Most of the learning is self-directed rather than structured, but it turns out that it's also really easy to learn when you are around a bunch of smart, motivated people.

However, it's somewhat more difficult to find good data science jobs now than it was when the program began. At least a few of the partner companies that have historically hired a lot of Insight fellows are no longer actively recruiting through the program. However, I and all of my close friends from the program ended up with jobs at top companies.