Online Data Analytics Bootcamp

NYC Data Science Academy is provides variety of courses in both online and offline mode. I have enrolled for Data Analytics bootcamp. Bootcamp is amazing. Course content is great. Instructors and staff is so supportive. Commendable!

I’d highly recommend NYC Data Science Academy’s Data Analytics Bootcamp to anyone looking to pursue a career in this field. I first discovered the bootcamp through a family friend who completed the program. After initial discussions and learning about the post-bootcamp networking services, I signed up for the online courses. The three major highlights of the bootcamp are Python, R, and SQL. You are instructed to follow online lectures which are complimented by homework assignments, projects, and weekly meetings with an instructor. This is all done at a rapid pace, so it’s important to stay on track and not fall behind.
Outside of technical skills, one of the biggest takeaways of the program is learning how to tell a story with your findings. By doing so, you can convey your message using various analytical methods, visualizations, and most importantly deliver actionable insights on how to proceed.
Upon completion of the program, there is a great support system through the career services team. The team partners with various companies and alumni to inform students on job openings in a wide variety of industries. In my case, I was able to secure freelance opportunities in the sports industry until I accepted a full-time position that was shared by career services.

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 did the Interactive Distance Learning (IDL) program in 2020, so keep in mind that my experience was strongly influenced by the COVID-19 pandemic. I am a career switcher from the health services industry - this bootcamp got me into the tech industry 2.5 months after completion of the program and taught me fundamental coding and machine learning skills as well as advanced statistics skills. That said, for the IDL course, because it is relatively self-paced, you get out exactly what you put it. I am highly ambitious and set myself up for success really well. Not everyone does. The content, instruction, mentorship, and community engagement are excellent and only getting better - these people are absolutely well-versed in their fields, care extraordinarily deeply about the success of their students, and are constantly iterating. I gave the program 4 stars because I did feel like there was an institutional bias toward the Remote Live Instruction students - when I was there, those students got access to internships and other resources that IDL students did not even though we pay the same tuition. Perhaps it has changed, but if you want the best chance of being noticed, the Remote Live course is the better choice, while if you need flexibility and are okay with a little less support, IDL is still a fantastic choice. Their career and alumni services are also top-notch, but again, only if you take advantage of all the resources.

 I recently graduated from the NYC Data Science Academy online part time bootcamp program and can attest to a very positive experience with Vivian and team. In case helpful for future students considering this bootcamp program, here is a breakdown of different considerations concerning my experience at NYCDSA:  1. Why I picked NYCDSA NYCDSA appeared to be the only bootcamp program that taught both Python and R at the time I was considering enrolling in a data science bootcamp program, which I expected would provide the best optionality in terms of choosing a data science framework both best fit for me and best fit for the industry I would want to integrate both graduation, as the public sector / academia generally lean towards R while private sector and tech industry broadly generally lean towards Python. The NYCDSA curriculum further appeared well structured and paced for someone in my position just learning how to code and getting a first exposure to data science concepts.  2. Overall Experience Vivian & team create an incredible learning environment with in-depth & concise lectures providing detailed overviews of multiple essential data science frameworks such as Python, R, SQL, Docker, AWS, Hadoop and Spark. The team further goes above and beyond for students during the job placement process, such as for instance making themselves available to answer student questions on personal projects and case studies, promoting student projects to recruiters and alumni on their LinkedIn page or providing students with opportunities to present projects to recruiters and alumni. The mentor meeting credit system connecting students to alumni in 1-on-1 30min or 1-hour sessions is especially well designed for students just getting started in data science and provides good opportunities to ask questions and review any material with an industry professional. Overall the lectures are well-taught and provide concise overviews of the analytical frameworks and knowledge necessary to perform in a professional data science environment, while the hands-on labs and projects do a great job of providing students the opportunity to practice learned coding skills.  3. Skills learned The bootcamp does a great job of providing ample opportunities to practice coding skills through projects and labs and I was able to develop strong proficiency in Python, SQL, R and Docker through these various projects, coming from a mostly non-coding undergraduate background, which I was able to apply directly after graduating working as an intern with a tech startup and finally in a full-time data scientist capacity at a large financial services firm.  4. Post-graduation plans I received a data scientist job offer at a large financial services company three months after graduating from the bootcamp after initially working as an intern at a data science startup and could not be happier with the outcome. Vivian and team are truly special and I could not be more thankful for an amazing experience over the course of the past few months. 

In short, the bootcamp excels on the curriculum, providing guidance, and career services. I found this bootcamp online, and I decided to go for this one because of the curriculum and the feel of it during the assessment process - they sounded like they knew what they were doing! They provided valuable feedback on the areas I needed to improve.I have a math degree and was already a Sr. Data Analyst, but wanted to move a step forward in my career by learning Data Science and Machine Learning. What I liked is that the coursework is tailored to each person depending on their experience, strengths and weaknesses.I went for the part time program since I was also working, and I am not going to lie, it is challenging! But worth it. Throughout the bootcamp I learned of many DS/ML concepts that are widely applied across different roles and companies, the projects assigned were the best way to apply and practice the things learned, and I eventually was able to apply them in my own job. They also offer TA sessions that are very helpful to review on the parts that seem confusing. One thing to note is that because of the extensive material taught condensed in a short period of time, studying extra materials is needed in order to get the most out of the bootcamp. Upon graduation, there are helpful resources on landing the next job - mock interviews, career advising, and networking. I landed a job at The Trade Desk as a Business Intelligence Analyst thanks to the stories I was able to tell of the projects I worked on in the bootcamp, the projects I worked on my previous role with the bootcamp knowledge, and with the various mock interviews (I was very bad at interviewing).

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 was in one of the online bootcamp cohorts. Before I registered for the bootcamp, I just finished my graduate school in a biomedical related major. I liked doing data analysis, but I quickly found out that there was a gap between what I knew and what the industry wanted. Therefore, I decided to choose a bootcamp to ramp up my technical skills. I decided to join NYC Data Science Academy because it offered a very competitive curriculum that included Python, R, SQL, Spark, Hadoop and Hive. The projects we did, which includes Rshiny app, web scraping, machine learning, and a final capstone project, are a good portfolio that students can present to potential employers and those skills can be directly applied to work.  It was hard to keep up as I was also doing a full time job while attending the online bootcamp. NYCDSA provided many service to keep students on track. One of the service I like the most is the TA assistance. I was paired with a TA and we met regularly to go over my progress and the questions I had. My TA was also a NYCDSA student before and was working in the industry as data scientist. Therefore, he not only knew what my struggles were on the course work, and he also taught me a lot of practical experience that was using in the industry.