NYC Data Science Academy

Without question, this is an outstanding Bootcamp for those looking to break into the field of data science. The curriculum is structured to help students master the essential vocabulary in Python (and R) needed to gather, clean, analyze and visualize... Read More fairly large data sets(up to a few million records of data) as well as master the theory behind the traditional machine learning algorithms used in supervised and unsupervised learning - ie. penalized MLR, SVM, DA, LR, DT, RF, Gradient boosting algos, clustering and PCA along with hands-on homework, quizzes, exams and project work to consolidate theory with practice. And all this is crammed into 12 weeks so prepare for an intensive ride. But as others have mentioned you will get as much out of it as you put in and this includes utilizing the wealth of resources available to you via the instructors and your cohort.
In addition to the coursework, the Bootcamp prepares students for the job market by emphasizing presentation skills and the importance of using data to tell a relevant story or solve a business problem. The founder of the program is personally involved in the resume and interview preparation as well as many aspects of the job hunt process.
I enrolled in the 12weeks in-person Bootcamp but due to Covid-19, all classes were made virtual. I commend the Academy for making this transition seamless without a reduction in the academic experience.
I certainly recommend this Bootcamp to beginner/intermediary level data science professionals or those looking to make a complete switch. There's unfortunately not enough time and emphasis put into the more advanced machine learning techniques like neural networks or manipulating very large datasets(mm++ records) but for more advanced students, the Academy offers advanced courses in deep learning, hdfs & spark that are unfortunately separate from the Bootcamp(at an additional cost of course!)

NYCDSA is a fantastic bootcamp. I picked them on the recommendation of a former student and it didn't disappoint! It was a seriously tough 3 months, I had never coded before I started the course pre-work having just finished a humanties degree and they... Read More pack a huge amount in. With their syllabus the course should really be much longer than 3 months, so you'll need to spend time on the pre-work and also consolidating post-bootcamp, but they give you a solid base to work off and plenty of material to work through even after you've left.

You get out what you put in to this course. I was often pretty exhausted and increasingly had no weekends! It was no picnic but definitely worth it as I now have a job at a consultancy specialising in data.

I think the best aspects of the course were that you could ask anyone for help, both students and teachers, plus the nature of the project work where you were also judged on your presentational skills.

Very fast-paced, intense experience that gave a vigorous run-through of the Computer Science, Mathematical, Statistical, and Business-oriented skills necessary to break into Data Science. You won't graduate an expert, but you'll at have at least a baseline... Read More understanding of countless tools that you can continue to develop your understanding of upon graduation. The staff is VERY dedicated to student success and will go out of their way to ensure your understanding, and even more so if you approach them first. They do a good job building a strong sense of community among the students and faculty. If you're eyeing a career change or a way of breaking into the field, I'd highly recommend NYCDSA.

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NYC Data Science Academy
Avg Rating:4.84 ( 298 reviews )
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NYC Data Science Academy offers 12-week data science bootcamps in New York City. In these... Read More programs, students learn beginner and intermediate levels of Data Science with R, Python, Hadoop, Spark, Github, and SQL as well as popular and useful R and Python packages like XgBoost, Caret, dplyr, ggplot2, Pandas, scikit-learn, and more. Once the learning foundation has been set, students work on multiple projects through the bootcamp. The program distinguishes itself by balancing intensive lectures with real world project work, and by the breadth of its curriculum. Throughout the program students work alone and in teams to create at least four projects that are showcased to employers through multiple channels; private on-campus hiring partner events, student blogs, meetups, and filmed presentations.

Ideal applicants should have a Masters or PhD degree in Science, Technology, Engineering or Math or equivalent experience in quantitative science or programming. Candidates with BA’s who have appropriate experience are also considered.

Throughout the data bootcamp, students are assisted in preparing for the employment process through resume review and interview preparation. NYC Data Science Academy works closely with hiring partners and recruiting firms to create a pipeline of interest for its students.

RECENT NYC DATA SCIENCE ACADEMY REVIEWS: RATING 4.84
Project-based Learning is a Must for Data Science

Rewarding and Advantageous

12-Week Data Science Bootcamp

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Courses
12-Weeks In-Person Data Science Bootcamp
MySQL, Data Science, Git, R, Data Visualization, Hadoop, Spark, Linux, Data Analytics , SQL, Python, Machine Learning
In PersonFull Time420 Hours/week12 Weeks
Start Date None scheduled
Cost $17,600
Class size 50
Location New York City
In this program students will learn the modern data analytic techniques and master the requisite skills, such as Python and R programming languages as well as Hadoop, to address real-world data science problems. Throughout the program, students work alone and in teams to create at least five projects that are showcased to employers. Along the way, students will have assistance in preparing for the job search through resume review, interview preparation, and opportunities to interview with our hiring partners. Successful completion of the curriculum will present a certification of graduation certified by the New York State Board of Education.
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Big Data with Amazon Cloud, Hadoop/Spark and Docker
Data Science, Hadoop, Spark, Data Structures, Python, Cloud Computing
In PersonPart Time5 Hours/week2 Weeks
Start Date None scheduled
Cost $2,990
Class size 10
Location New York City
This is a 6-week evening program providing a hands-on introduction to the Hadoop and Spark ecosystem of Big Data technologies. The course will cover these key components of Apache Hadoop: HDFS, MapReduce with streaming, Hive, and Spark. Programming will be done in Python. The course will begin with a review of Python concepts needed for our examples. The course format is interactive. Students will need to bring laptops to class. We will do our work on AWS (Amazon Web Services); instructions will be provided ahead of time on how to connect to AWS and obtain an account.
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Data Science with Python: Data Analysis and Visualization (Weekend Course)
Data Science, Data Visualization, Data Analytics , Data Structures, Algorithms, Python
In PersonPart Time4 Hours/week6 Weeks
Start Date None scheduled
Cost $1,590
Class size 20
Location New York City, Online
This five week course is an introduction to data analysis with the Python programming language, and is aimed at beginners. We introduce how to work with different data structure in Python. We covered the most popular modules, including Numpy, Scipy, Pandas, matplotlib, and Seaborn, to do data analytics and visualization. We use ipython notebook to demonstrate the results of codes and change codes interactively during the class. Our past students include people with no programming experience or those who have minimal exposure to Python. Students told us our classes are very informative, engaging, and hands-on.
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Data Science with Python: Machine Learning (Weekend Course)
Data Science, R, Artificial Intelligence, Machine Learning
In PersonPart Time7 Hours/week5 Weeks
Start Date None scheduled
Cost $1,990
Class size 10
Location New York City, Online
This 20-hour Machine Learning with Python course covers all the basic machine learning methods and Python modules (especially Scikit-Learn) for implementing them. This includes linear regression, Naïve Bayes classifiers, logistic regression, linear discriminant analysis, cross-validation, bootstrapping, feature selection, regularization, model selection, SVM, decision trees, random forest, PCA, K-Means, and Hierarchical clustering. In addition, this course teaches the basics of natural language processing. After successfully completing this course, you will be able to explain the principles of machine learning algorithms and implement these methods to analyze complex datasets and make predictions in Python.
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Data Science with R: Data Analysis and Visualization (Weekend Course)
Data Science, R, Data Visualization, Data Analytics , Data Structures
In PersonPart Time7 Hours/week6 Weeks
Start Date None scheduled
Cost $2,190
Class size 15
Location New York City, Online
This course is designed to provide a comprehensive introduction to R. Students will practice programming and analyzing data with R. Students will learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models to data. In addition to a theoretical framework in which to understand the process of data analysis, this course focuses on the practical tools needed in data analysis. This course also covers the creation of dynamic reports with the knitr package in R as well as the creation of dynamic dashboards with R Shiny. By the end of the course, students will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting the code.
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Data Science with R: Machine Learning (Weekend Course)
Data Science, R, Machine Learning
In PersonPart Time7 Hours/week6 Weeks
Start Date None scheduled
Cost $2,990
Class size 40
Location New York City, Online
This 35-hour Machine Learning with R course introduces both the theoretical foundation of machine learning algorithms as well as their practical applications in R. It will introduce you to data mining, performance measures and dimension reduction, regression models, both linear and generalized, KNN and Naïve Bayes models, tree models, and SVMs as well as the Association Rule for analysis. After successfully completing this course, you will be able to break down the mathematics behind major machine learning algorithms, explain the principles of machine learning algorithms, and implement these methods to solve real-world problems. Unit 1: Foundations of Statistics and Simple Linear Regression Unit 2: Multiple Linear Regression and Generalized Linear Model Unit 3: kNN and Naive Bayes, the Curse of Dimensionality Unit 4: Tree Models and SVMs Unit 5: Cluster Analysis and Neural Networks Final Project After 35 hours of structured lectures, students are encouraged to work on an exploratory data analysis project based on their own interests. A project presentation demo will be arranged.
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Deep Learning with Tensorflow (Weekends and In-Person Only)
Data Science, Game Development, Artificial Intelligence, Python, Machine Learning
In PersonPart Time6 Hours/week6 Weeks
Start Date None scheduled
Cost $2,990
Class size 15
Location New York City
Via analogy to biological neurons and human perception, this course is an introduction to artificial neural networks that brings high-level theory to life with interactive labs featuring TensorFlow, the most popular open-source Deep Learning library. Essential theory will be covered in a manner that provides students with an intuitive understanding of Deep Learning’s underlying foundations. Paired with hands-on code run-throughs in Jupyter notebooks as well as strategies for overcoming common pitfalls, this foundational knowledge will empower individuals with no previous understanding of neural networks to build production-ready Deep Learning applications across the major contemporary families: Convolutional Nets for machine vision; Long Short-Term Memory Recurrent Nets for natural language processing and time series analysis; Generative Adversarial Networks for producing realistic images; and Reinforcement Learning for playing video games.
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Full-time Online Data Science Bootcamp
MySQL, Data Science, Git, R, Data Visualization, Hadoop, Spark, Linux, Data Analytics , SQL, Python, Machine Learning
OnlineFull Time28 Hours/week12 Weeks
Start Date None scheduled
Cost $17,600
Class size 25
Location Online
This program was designed for students that have the time to be a full-time student, but can't commute to our school. Students will be placed on a rigorous curriculum that spans from 9:30 AM to 6:00 PM EST as well as have access to prerecorded modules with over 1000 coding challenge questions on online learning platform for additional practice. In addition, they have access to dedicated TA’s as well as the larger network of a shared slack channel between both in-person and remote bootcamp students. Classes: You will learn streamed lectures as well as have access to prerecorded modules and coding questions for additional practice. Personalized Job Support: Students also have access to the full resources of NYC Data Science Academy to help them find their dream job upon graduation. Our curriculum covers the expanse of all the skills required in the data science industry. We cover both R and Python as well as Machine Learning Theory, Big Data, and Deep Learning.
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Introductory Python (Evenings)
MySQL, Data Science, Data Visualization, Data Analytics , Data Structures, Algorithms, Python
In PersonPart Time5 Hours/week2 Weeks
Start Date None scheduled
Cost $1,590
Class size 40
Location New York City
This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web. This Introductory Python class runs over four weeks, with five hours of class per week (split into 2 ½ hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of homework after each class.
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Part-time Online Data Science Bootcamp
Data Science, R, Data Visualization, Spark, Virtualization, Data Analytics , Data Structures, Artificial Intelligence, SQL, Python, Machine Learning
OnlinePart Time28 Hours/week26 Weeks
Start Date None scheduled
Cost $17,600
Class size 25
Location Online
This is an online part-time self-paced program. Students have 4 - 10 months to complete this program. The curriculum is the same as our on-campus program, with full-financing options, career support and with a one on one support from our mentors. This program is designed for students that work full-time and are not able to quit their jobs. Our curriculum is drawn from data science engagement with corporate consulting and training, hiring partners and active industry participation. Our remote bootcamp ensures that students achieve a very high level of proficiency. Students are expected to dedicate themselves fully to this program and fulfill all the requirements, which include completing lecture videos, daily homework, and four projects. The Remote Bootcamp is built as a collaborative environment utilizing online chat and meeting systems. Students also have the opportunity to collaborate on homework, projects, job applications, interview preparation, paired programming, and even further through our extended alumni community. We work closely with hiring partners and recruiting firms to create a pipeline of interests for students. Each student receives one-on-one support with job searching and access to all kinds of job assistance resources, including coding reviews, interview prep, resume workshop, and access to our exclusive hiring partner network.
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NYC Data Science Academy Reviews
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Project-based Learning is a Must for Data Science - 7/8/2020
Kailun Cheng User PhotoKailun Cheng • Graduate • Course: 12-Weeks In-Person Data Science Bootcamp • Campus: New York City • Verified via LinkedIn
Overall Experience:Curriculum:
Instructors:Job Assistance:
I have a biomedical engineering background, and I enjoy solving complex problems using quantitative methods. I had decided to venture into the field of data science and machine learning because I realized that there are many processes that are insufficiently modeled in a deterministic way. When I graduated with a Master's degree in Data Science, I had acquired many tools and methods in disciplines such as computer science and applied math; however, I was lacking some experience actually "doing" data science, especially in working with real-life data. NYCDSA gave me the opportunity to obtain hands-on experience in the model building process. I also had a great time collaborating with other fellows, instructors, and mentors on challenging projects, which further expanded my skill set in proper data collection, data retrieval, and data visualization. Overall, NYCDSA fosters an enriching and inclusive environment for students of all different backgrounds to gain valuable experience that's needed for a data-driven career.

Regarding the job prospects post Bootcamp, I find it challenging in finding a suitable position in this ever-changing career field coupled with the tough economic situation. However, I do think that NYCDSA is a great guide in pointing me in the right direction by providing the appropriate resources. After graduation, a couple of recruiters reached out to me, and I was able to pass rounds of interviews with the knowledge I gathered from the projects I did in the boot camp. Ultimately, I'm able to receive a full-time data scientist position offer about three months post-graduation.

This boot-camp was a waste of time and money. They gave me poor information and wasted my time. I am quiet angry with them for this. Don't register with them. Also there representatives are the ones which promise things they cannot finish. In a sense... Read More the instruction was good but they wasted my time and would not refund anything.

NYCDSA bootcamp curriculum is intensive, deep, and diversified. It covers both the math behind the data science and the practical platforms/languages/tools (Python, R, SQL) most widely used in the industry. Their career services are focused and efficient,... Read More leveraging a large community of alumni and partners. Highly recommend!

I recently graduated from NYC Data Science Academy in March of 2020. Before I began my cohort, my background was in finance and was a novice in the data science/coding world. Though challenging and difficult at times the staff, instructors, and the TA's... Read More really helped me to push myself and assisted me to complete the program.

The curriculum not only covers coding and data science but the individual & group projects, presentations, and the helpful feedback is very advantageous in the real world. Also, I really appreciated how NYCDCA went what of their way in little things that can make a big difference such as: head shots, resume reviews, interview preps, strategy in job hunting etc...They did an excellent job of covering all topics and encompassing everything that comes with either career change or building up your current career.

From my experience, I only have positive things to say about the staff, instructors, curriculum, job support, and the community at NYC Data Science Academy and highly recommend NYCDSA to anyone who is interested in data science.

This bootcamp helped me go from code illiterate to code proficient. The curriculum at NYCDSA is amazing. Trying to become an expert at anything in 3-months is nearly impossible, but NYCDSA does a pretty dang good job of presenting all salient data science... Read More topics and pairing these with four major projects that help to solidify your understanding. I was incredibly pleased with the quality of instruction and the expertise of the teachers. It felt like the instructors truly cared about my development and digestion of the material. The career services team has been very very helpful as well. Like many things, you get out what you put in. I highly recommend this bootcamp, but if you do decide to attend make sure to complete the prework, devote 100% of your time to it (i.e. don't work at the same time), and put your all into each project. The four major projects (R Shiny, Python Web Scraping, Machine Learning, and Capstone) are important in how you market yourself post-bootcamp and were fundamental in giving me the confidence to say that "I am on my way towards becoming a great data scientist". Listening to lectures and understanding concepts can only take you so far, so make sure to befriend stack overflow, your instructors, and your keyboard as much as possible. Best of luck in your studies!

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... Read More 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 graduated from the NYC Data Science Academy in September 2019. Though I lived in Austin, TX - home of many data science schools -, after vetting the success of past graduates and the credentials of the instructors at the Academy, I made the decision... Read More to temporarily move to New York to attend this school.
The requirements and coursework was very intimidating, but certainly appropriate given the requirements to be an effective data scientist. The typical student spent at least 12 hours a day at the classroom to meet homework and project deadlines, but those hours were well-spent. Even though the difficulty in the material ramped up, the quality of the students' projects and in-class discussions definitely became much more substantive and impressive. The devotion of the students definitely rubbed off on each other, but the expertise of the instructors definitely helped foster that growth as well. It is also worth mentioning that the close alumni network also played a part in student growth.
Beyond the hard skills learned (Git, Docker, SQL, Python, R, ML, etc ), the program required a lot of soft-skill development as well. Between developing effective presentation skills for our projects, and collaborating with our peers, teaching assistants and instructors, you truly learn what it means to become a data scientist amongst data scientists.
It is also worth mentioning that they play a big role in your professional development as well. They devote a lot of time to your resume building, interview preparation, and student networking, and, personally, I found the alumni presentations they prepared were some of the most insightful presentations I've had.
If you are serious about becoming a data scientist, you go to this school.