NYC Data Science Academy

I took the online part-time bootcamp because I was working full-time as a software product manager, yet wanted to improve my coding and statistics knowledge. I had some background in Python but had a lot of gaps in my knowledge of theory and no exposure to topics like deep learning and data engineering. NYC Data Science Academy was a great place for me to get a deep-enough overview of a wide range of topics; I appreciated the emphasis on R and Python used in the context of real-world projects. The theory was presented clearly without getting too academic, and the instructors were clear, patient and helpful. Highly recommended.

I remembered a year ago going from websites to websites, reading reviews after reviews, looking for the best school for Data Science Bootcamp. I finally stopped at NYC Data Science Academy and one of the main reasons I decided to go with NYC was because I was going to have the ability to learn R and python. After completing the actual bootcamp, I will say that the above reason ended up being the last if I were to make the decision again. 

Here are my best reason why NYC is a great school:

1- Class organization: The entire program is well-organized so students have a full idea of what to expect from day one. The bootcamp preparation material helps students get up to speed with general statistics, algebra, and programming before the beginning of the program. Once the program starts, these topics will be reinforced before moving to Hardcore machine learning. 

2- Instructors: Most of the instructors I had the chance to work with are PhD holders or professionals with several years of industry experience. So when they dispense their classes, they have both theoretical and practical understanding of the material. On top of this, they are extremely patient with students and will go above and beyond to make sure students do not fall behind. One instructor,Thomas Laesch, designed a matrix multiplication game every Saturday for one month just to help us build the reflex of solving matrix multiplication(this is very important in understanding most ML models). 

3- Job search and interview preparation: This is actually my favorite part. The support I received for job search and interview preparation was immense. As I am writing this review, one year after my class, NYC faculties are still helping me with career counseling and responding to background questionnaires from my employer. 

4- Last but not least I did learn Python and R. Moreover, the knowledge I acquired from this institution has helped me so much in my Data Scientist Career. Even today, I still use my class material as reference for many issues I encounter on the job. 

In short, choosing this program was one of the best decisions I made for my education and career. I will strongly recommend this program to anyone looking for a Data Science/Data Engineering bootcamp, if anyone would like to know more about my experience feel free to search me on LinkedIn and I will be happy to answer any questions that I can.

I had a great overall experience with the program and would strongly recommend it to anyone looking to transition into data science. The data analytics and machine learning coursework are taught in both, R and Python, but with different emphasis (inference vs prediction) allowing for a more comprehensive exposure to the different ML topics covered. The one-on-one mentor support was very helpful with coursework and the projects, but also with career advice. I met with the mentors on a weekly basis and all 9 mentors worked as data scientists in the industry.    Job placement support is also great. After completing the program, I have had the opportunity to join several networking events, get interview skills coaching and work one-to-one on my resume with a career services strategist. I think the academy is very good at creating networking opportunities and partnering with companies to help you connect with potential employers and continue to build your portfolio.     My background coming into the program: Materials science engineering PhD, minimal coding experience (a Coursera Python course), basic statistics skills and no machine learning knowledge. Completed NYC Data Science Academy part-time online bootcamp, which I choose because I had a full-time job throughout the program.

I have my masters in computer science and I joined NYCDSA to specialize in data science. I joined NYCDSA based on the reviews online and they did not disappoint. What I found most remarkable is the 1:1 support they provide. The curriculum is thorough and the standards are high but instructors were all dedicated to help students succeed and understand the material. In light of covid-19 pandemic, the team was able to transition the immersive in-person course to online. They did a phenomenal job making sure all the students are interacting with the instructors and working together on projects. Career support is also great—they became that lifelong friend to always go to for advice and guidance.

I won't go into a description of what the Bootcamp offers - you can find that in the reviews below. All of them are accurate as to the material that the program offers.  

I'll give my opinion of the FINANCIAL sense of going to this bootcamp versus others and the level of job assistance provided - which is what most of you reading this are actually interested in.

Let's do a compare and contrast with springboard.com (not paid for this, just using as an example)

Springboard

• $7,500 upfront tuition ($8,900)
• Full Refund Guarantee (after 6 months of no job)
• Deferred Tuition until you land a job

NYC Data Science

• $17,000 tuition ($5,000 deposit)
• No refund guarantee
• No deferred tuition option

You'd think with that price tag, there'd be some awesome job network or assistance provided, right?

Not really. 

They might send you a prospect once every two weeks. 

But, all the interviews I gained were through my own efforts on LinkedIn. 
The most they'll tell you is some superficial styling tips for your resume. 

And that's about it. Connections they do not provide. 

There was supposed to be a networking event with employers at the end of the program.

Didn't happen. 

The closest to that was an invitation to a "Gender Equalithon" hackathon by Esteem whose stated goal is to "Hire & Retain Women, People of Color, LGBTQ, Latinx in Tech". 

The point of this is - is that job assistance is important. The material can be learned anywhere - other bootcamps, online, universities. 

But the major selling point for these operations is the job assistance and access to their professional network.

And by that metric, NYC Data Science doesn't deliver. 

P.S.
The reason you probably don't see more negative reviews of these bootcamps, is because people are still angling for job assistance and most are scared to speak up or burn bridges. 

Earlier this year, I decided to pursue a career change. I was working as an actuary for several years, and became interested in the world of data science. Even though actuarial science is considered to be the original data science, in modern times, the two career tracks are quite different. It felt intimidating to make the transition into the field of data science on my own, not knowing where to get started.  In the beginning I was looking into getting a master’s in data science. However, I was deterred by the huge time, and cost commitment of pursuing a master’s degree. I started investigating various data science bootcamps having known several people who had successfully made career changes by attending bootcamps for programming, or design. A friend of mine recommended I check out NYCDSA. In the end, I chose NYCDSA over other programs I was considering, because it is the only data science academy that teaches both R and Python.  The bootcamp is only 3 months long, but covers a ton of material, and will be one of the most intense learning experiences of your life.  The program focuses heavily on practical applications. and is structured so you’re picking up the right skills in the most efficient manner. The instructors are super knowledgeable, and always there to support you along the way. A career in Data Science is a continuous learning journey, and NYCDSA was the perfect place for me to get started. I think the bootcamp does a fantastic job of helping you build a solid foundation of data science skills applicable to a range of data science career tracks. Simultaneously, there’s a lot of freedom to explore the niche field you are interested in. 

After working in the financial sector for over ten years, I have decided to strengthen data science skills, such skills are increasingly critical in problem solving. I chose NYC Data Science Academy over other bootcamps since it has a more comprehensive curriculum, the quality of faculty and the successful graduate networking. The 12-week curriculum covers the basics of data science, including Python, R and SQL coding skills, machine learning, clustering and algorithms knowledge, such a curriculum is indispensable in developing the data science-based analytical skills. The projects and the homework that we were assigned to are also quite useful to prepare job interviews. Alex and Luke are great instructors who helped out a lot with my study, as did TAs, I also made great friends from the cohort that I worked with here. I received invaluable support from the bootcamp in data scientist and data analyst interviews. I must say this is the best bootcamp to learn and improve data science skills and develop professional networks. 

I had been an advanced analytics director in media looking to make a career change into the healthcare field as a data scientist. I was working with marketing scientists in my prior job that were using machine learning but was not fully aware of the power, accuracy, and methodology behind statistical models and machine learning. Not only did I learn the ins and outs of traditional machine learning through this course, but I also picked up hands on experience web scraping, analyzing many types of data sets, and creating my own algorithms and machine learning models to tackle real-life problems such as predicting critical disease. R & Python are taught side by side, allowing you to pick up both languages and also understanding pros and cons of each.
Don't get me wrong, this was a lot of hard work, but if you're looking to make a career change and become a data scientist there is really no better way than to enter the belly of the beast. This is called a bootcamp for a reason so expect to roll up your sleeves and work very hard. However, if you do all your assignments, listen to the helpful advise from the instructors and administrators, and really make practical use of your projects and career support, this will be a career changing experience for you, as it was for me.

This 12-week course begins with a well-structured introduction to Python, R, and SQL and is friendly for beginners with no programming background. You'll be able to complete the first two projects: one is about web scraping and one is data visualization with R Shiny. We then covered the most popular machine learning models and concepts, which we implemented in the last two group projects. The boot camp also helps with resume, elevator pitch, code challenges, and there is a well-planned post-boot camp review section to prepare for theories and interviews. I have four years of experience working as a financial analyst and managed to get an offer one week after the career event. The things you learn here are the most practical skills in the professional world and will help you continue learning data science on your own after the boot camp. Job support is great!

 

I took  Dr. Krohn's Deep Learning class with the intention of keeping my self updated with new skills. After a week of class I found myself immersed on Deep Learning reading as much articles as I could on the subject. Dr. Krohn taught the class with a perfect balance between the math and the implementations, ideal for our class which had professionals with different backgrounds. We received a lot of information in each of the five sessions but the pace was OK because the 5 weeks were not exactly in a row. I would recommend this class to any body who wants to get ahead with  new technologies or who is just curious about them. If you decide to take the class, make sure to do the reading assignments and play with the software on your own. For the one optional project, I would recommend to immediately start a project with the material of the second class (our first implementation); so that you can get the help that you need if you get stuck and you can even have a chance to make a second project (maybe in NLP).  This would be specially useful  if you are a software developer and want to try the different implementations.