General Assembly

I've had a great time in DSI and learned a ton. I went from not knowing python to being able to successfully implement complex machine learning techniques in the span of a few months.

That being said; anyone considering the program should know what they are and are not getting from DSI:

• DSI is not a python software development course. You will learn how to manipulate and analyze data using python, but python itself is not the focus. Your code will not be pretty, but it will get the job done.
• DSI is not a zero to sixty program. If you don't like math, don't have a decent grasp of statistics, and have never used the command line before, DSI is going to be rough. The more you bring in, the better.
• DSI is not a complete Data Science program. They have 12 weeks to take a group of people with varying degrees of familiarity with computer science and statistics and give them a solid, fundamental basis is data science that they can take into the job market. DSI will not take you from never touching python to coasting into a high paying job with facebook; but it will get you on the road that takes you there.
• DSI is a fast paced, guided learning experience. Being the pilot program, there were significant structural problems with my cohort. The question I continually asked myself during the worst of it was: "If I quit my job, took 12 weeks, and worked as hard as I could learning python and statistics, would I end up in a better place job-wise than staying in DSI?" - For me, the answer was always no; DSI provides a framework and resources for learning complex, difficult material that I would not have access to on my own. Additionally, the benefit of learning alongside a large group of others fighting through the same material cannot be valued enough - not to mention the people who I helped and who in turn helped me will form the nucleus of my professional network. No amount of meet ups and personal study would accomplish that in 12 weeks.
• DSI is what you put into it. If you rely on GA to give you everything, to provide all the materials you need to learn a subject - you're doing yourself a disservice. When you enter DSI the clock starts. You now have 12 weeks to learn as much as you can, so you can find a job where you put those skills to practice. DSI provides a great framework, leading you from topic to topic, grouping similar subjects, easing the transition between difficult, disparate problems.
• DSI is not easy. There's a lot to learn, and not a lot of time. If you're not keeping up with the work, you're going to get left behind.

I've had a great experience in DSI, and feel very confident in my career prospects. 

Am I about to step into a senior data scientist position at a premier company? Probably not, but 12 weeks ago I was not in a position to even consider those jobs. 

Now I have a solid foundation in the industry, a growing network of professional contacts, and a roadmap to a successful career in data science - exactly what I was looking for when I signed up.

GA's data science immersive has been the single most intellectually challenging experience of my life, making college look like a walk in park.  However, in the past 11 weeks, I have learned an extraordinary amount and feel confident about my prospects in entering the workforce, particularly given the extremely high demand for data scientists right now.

As earlier reviewers have mentioned, the GA's data science immersive is a pilot program, and GA DC got off to a particularly rocky start, due to some mishaps with curriculum development, followed by our primary instructor quitting without notice a week and a half in.

While this was a very frustrating experience for the student body, I was very impressed with GA's swift and appropriate response to the situation.  They exploited their many connections to hire a highly qualified new instructor immediately, while highly qualified and capable instructors from other immersives helped fill in the gaps.  They also gave a substantial refund and added extra time to the program to insure that students would have adequate time to master the material and complete capstone projects.

GA must have lost an enormous amount of money on our pilot program, but they did what they had to do to insure that we came away with a quality education.  The next cohort will have it much better than we did, as the curriculum has been improved and a strong instructional team is in place.

Of course, this class is still really really hard. Instructors do not, and cannot, take the time to walk you through how to do everything step by step.  They give us direction and help us out when we are stuck, but ultimately, the onus is on us to learn the material.

The instructors were great and very helpful and the TAs were very generous with their time.

However, it's a real grind and the job placement help (they call it "outcomes") was a real joke. Outcomes should have been something tacked on at the end of the actual web development training instead of interspersed throughout (ideally, it could have been optional, giving students the option of not paying for that part of the class.)

At the end of it all, I feel like I've learned a lot, but I don't feel like my outlook for finding a job in tech is very promising and I still have a long way to go before I'll be qualified for any openings I find online. 

Not to mention, the class mostly focused on MEAN stack which already has a ton of free or low-cost tutorials online. If you have the patience and discipline, save yourself $13,000 and learn this stuff online. I recommend starting with Free Code Camp.

General Assembly is an awesome bootcamp, if a bootcamp is what you're seeking. In the three month immersive, we've covered a ton of Data Science topics. I went from hardly using the command line to being able to use a variety of python libraries to query databases, scrape web data, clean and organize data, find trends and patterns in it, build models to analyze and predict it, and communicate results visually from that. This makes up the foundation of data science, and is definitely not something I could have done at the beginning of the course. 

GA is not a Masters program. If you're looking for in depth theoretical analysis and deep dives into lots of microsubjects, you may be better served in a longer program at a university. If what you're looking for is a rapid fire survey of the relevant topics and the ability to dig deeper yourself into the topics that catch your interests, then it's awesome. You'll definitely be able to find your niche and your passions and participate in activities to support that, and they're helpful with finding and providing resources (like books) to further this pursuit. You will definitely come away with a toolkit that is highly applicable to the field. 

I will say that my experience is in the pilot program of the immersive. There are things to be ironed out, specifically in clarity in the curriculum and overall course flow. However I do know that the administration and instructors are aware of this and are actively working to refine this for the next cohort. I see the other immersives around here and their curriculum is very finely tuned, so I know that this is headed to a great place, and quickly. 

Be clear about your needs and make sure that you're a fit for the place. If you're willing to work independently and quickly and get a jump start in the field, this program sets you up for success. They won't hold your hand, but they will give you the tools you need. It's a learn by doing, hands on type of place. If that's how you learn best, I think you could do great things here. 

Oh, and the Outcomes team to help with job assistance - again, you get out what you put in. They won't seek you out necessarily, but they are always willing to provide feedback and support when asked. They structure activities throughout the course and if you hold yourself accountable to their timeline, you'll have a solid job hunting kit ready to go by the end of the course. Take advantage of this!

General Assembly has bitten off way more than they can chew with their Data Science Immersive program. We are told the one new instructor we finally got, weeks after the first one quit, does know what he is doing. However, I am not really sure since he has the TA cramming on the weekends to teach us material and then isn't here when she can't answer the questions we have.

They are also getting ready to recruit for the next running of the Data Science Immersive which is completely laughable at this point. If you are looking at it, save your money. Either do the PT program or wait to see if GA is still offering this a year from now.

At this point I am just sticking around for the career assistance because I do need a job after this and I am really curious to see how they are actually going to find those of us that stuck around meaningful jobs given how poorly we are being prepared for them.

The range and depth of content was perfect for a 'beginner' to enter the world of data science. It also provides a good opportunity for devs (who already have a good understanding of programming) to explore types of business problem they may not have been exposed to before.

I would recommend to get the most out of the course participants spend 6 months (c. 100 - 200 hours) making sure they understand the basic of Python and stats before enrolling. There were some members on the course who hadn't done this and they still learnt a lot - but probably found it more difficult to keep up.