NYC Data Science Academy
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NYC Data Science Academy offers hands-on projects and real-world applications to teach students the skills needed for a career in data science. By enrolling, students become part of a supportive network that includes the NYC Open Data Meetup.
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Data Science with Python: Data Analysis & Visualization
NYC Data Science Academy See all classes by this school
Unlock the power of Python for data analysis and visualization with this comprehensive course from NYC Data Science Academy. Gain hands-on experience with popular modules like NumPy, SciPy, pandas, Matplotlib, and Seaborn, and learn how to manipulate and visualize data effectively. Take your programming skills to the next level and explore the world of data science with Python.
Introductory Python
NYC Data Science Academy See all classes by this school
Learn the fundamentals of Python programming in this introductory course at NYC Data Science Academy. Gain the skills to manipulate data and perform basic analysis using Python, with topics such as list and string manipulation, control structures, and data analysis packages. This course is designed for computer-literate individuals with no programming background.
Data Science with Python: Machine Learning
NYC Data Science Academy See all classes by this school
Learn the principles of machine learning algorithms and implement them to analyze complex datasets and make predictions using Python modules like Scikit-Learn. Gain the skills necessary to apply simple and multiple linear regressions, classification methods, cross-validation, feature selection, regularization, principal component analysis (PCA), and clustering algorithms.
Data Science with R: Data Analysis and Visualization
NYC Data Science Academy See all classes by this school @ 500 8th Ave, New York, NY
This course is a 35-hour program designed to provide a comprehensive introduction to R for Data Analysis and Visualization. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with 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 and visualization....
Big Data with Amazon Cloud, Hadoop/Spark and Docker
NYC Data Science Academy See all classes by this school @ Virtual Classroom
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...
Generative AI for Finance
NYC Data Science Academy See all classes by this school
Learn how to leverage generative AI models for the finance industry to gain a competitive edge in this hands-on workshop. Gain familiarity with the concepts and techniques of generative AI and leave with fully functioning code to apply generative AI to your business cases. No background in data science or AI required.
Generative AI for Marketing
NYC Data Science Academy See all classes by this school
Learn how to leverage the power of generative AI to create text, images, video, and music for your marketing needs. Gain a high-level understanding of these cutting-edge technologies and discover how to apply them to various marketing cases. No programming or data science experience required.
Generative AI for Everyone
NYC Data Science Academy See all classes by this school
A class for people with no data science background who wish to learn AI trends. Course Overview This four-hour workshop will cover everything you need to know to understand the current trends in generative AI, how these models work, and how to train them, and you can leverage them for your business. The session will cover how text, images, video, and music can be created by AI, details about the data they need, and considerations for their use....
Designing and Implementing MLOps
NYC Data Science Academy See all classes by this school
Learn how to design and implement scalable machine learning systems in production with this comprehensive course from the NYC Data Science Academy. Gain hands-on experience with Python, Docker, Kubernetes, Google Cloud, and other open-source tools to set up automated infrastructure and bring ML models to life. Take your ML engineering skills to the next level and drive business value with robust MLOps processes.
Reviews of NYC Data Science Academy
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Data Science with Python: Machine Learning
This was a very good introductory class. The instructor was always available to answer questions in and out of class. -
Data Science with Python: Data Analysis & Visualization
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Data Science with R: Machine Learning
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Data Science with Python: Data Analysis & Visualization
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Data Science with R: Data Analysis and Visualization
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Data Science with Python: Data Analysis & Visualization
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Introductory Python
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Deep Learning (with TensorFlow)
John is a great instructor attentive to every student. His class is well structured and he makes a lot of effort to ensure everybody learns well. A highly recommended course to get hands-on experience in deep learning. -
Big Data with Amazon Cloud, Hadoop/Spark and Docker
It is one of my best decisions to attend NYC Data Science Academy. During the bootcamp, I gained more confidence in programming. The coding skills taught are always on trend. Followed by the schedule of the bootcamp, I smoothly transferred my career path into data science. I do not only learned R, Python with corresponding practical, popular libraries in industrial applications but also acquired the ability in quickly learning new skills. NYC Data Science Academy provides students a good platform to communicate computer programming, machine learning algorithms, and its applications. Instructors and TAs are always helpful and patient for students to overcome difficulties in the study and provide supports. At the same time, students could have a blog platform with editing help to present projects. Interview skill development and career advice from Chris and Vivian are powerful to develop students as strong competitors in the job market. I really appreciate the knowledge, skills, and support I acquired from NYC Data Science Academy. I highly recommend NYC Data Science Academy to anyone who is interested in this career. -
Big Data with Amazon Cloud, Hadoop/Spark and Docker
I attended the 12-week boot-camp at NYC Data Science Academy from Sep. 2016 to Dec. 2016. Before that I got my PhD in Chemistry and worked 6 years' as a Post-doc in biochemistry. The curriculum was well organized. 12-week courses covered R and Python programming, statistical analysis and machine learning. During the last few weeks, big data tools like Hadoop and Spark were also covered. For one coming from academic background, the breadth of topics and difficulty level felt just right. The boot-camp courses weren't supposed to teach you everything, but they did prepare me very well if I wanted to explore further data science topics. The boot-camp was intense. I was only sleeping for 4 hours during boot-camp days. It was demanding both physically and mentally, but I wasn't alone in the journey. The instructors, TAs and classmates were all amazing. This boot-camp takes students from very different backgrounds, which I think is a unique advantage. I was able to see people applying data science tools to their own expertise brilliantly, fashion, marketing, IT, health care... It was very helpful for me who was looking to step outside of academia. The job assistance is good. There is networking, resume-editing and mock-interviews. Vivian also personally helps students tracking their job hunting status. I wasn't able to use lots of their services due to my personal situation, but for the one position I applied for I was able to impress the hiring manager with the machine learning knowledge and skills I acquired at NYCDSA and got an offer the same day. -
Big Data with Amazon Cloud, Hadoop/Spark and Docker
I attended the Big Data with Hadoop and Spark course, hosted and led by NYC Data Science Academy. My objective was two-fold: first, to gain a deeper and practical understanding on emerging 'Big Data' technologies, more so than what academic publications or industry white papers currently provide; and, second, to familiarize myself with the skill set and experience to expect from the new generation statisticians, or Data Scientists. With a background in Business Intelligence, Architecture, Risk Management and Governance on Wall Street, I find that foundational skills remain the same: mathematics and statistics. However, with the commoditizing of data storage and massively parallel computing, Data Scientist today are capable of solving problems reserved for an exclusive few in decades past. The course did not cover configuration of the Hadoop environment, but thanks to the engaging and knowledgeable instructor, clues on challenges and potential pitfalls were generously shared. I highly recommend this course not only to professionals or recent graduates looking to hone data analysis skills, but to anyone with an interest or stake in Big Data. -
Data Science with R: Machine Learning
I took Machine Learning with R and Hadoop data engineering classes in 2015. They are all well-structured classes with extensive information coverage and concrete learning process design. All the techniques been told in the class are very practical and can be applied to work very fast. In addition, it is also a great opportunity to build your "data science" fellow network because all your classmates are "Pro" in this domain with a lot of wonderful industry experiences to share. I would definitely recommend NYC Data Science Academy to my friend! -
Data Science with R: Machine Learning
This course covers major R machine learning topics; it is intense, and you will learn a lot if you keep up with the pace. Instructor Shu Yan is great at explaining complicated statistical concepts/formulas and translate them into R coding techniques. Course materials, in-class practices, and homework assignment are helpful regarding learning and future references. I would recommend this course to anyone who is interested in data science/machine learning but doesn't know much about this field. It will be a good start for you if you plan to work in this area. It certainly helped me understand a lot about data science and improved my R coding skills. What I learned from this course is worth the money I paid and the effort I put in. -
Data Science with R: Machine Learning
Took the weekend course for Machine Learning with R. Course was very helpful in helping me understand the basics of Machine Learning, different models. My instructor was Luke. He was very helpful and would spend enough time covering each topic. He even took an additional class because he didn't want to rush through the material. Overall I am quite satisfied with the results. Would recommend Luke to anyone else who is interested to venture into Machine Learning field. -
Data Science with R: Data Analysis and Visualization
This was a great class that I truly enjoyed attending every Saturday for 5 weeks. The class had a pretty steep learning curve but the slides and the homeworks did a good job of teaching the material. Our instructor, Derek, was an R guru and could answer any question we threw at him. I definitely plan to continue learning R and I can attribute my enthusiasm to having taken this class. -
Data Science with R: Data Analysis and Visualization
I attended NYCDSA 5-week course (5 full-time days, one per week) in 4Q16 as part of my preparation to start the same school bootcamp. This was a great introductory start to learn R due to the comprehensive syllabus and dedicated teacher effort. About the syllabus, you will learn Base R syntax and principal data structures identification and manipulation plus a bunch of other packages (e.g. DPLYR) that will make your life easier when treating data sets. The instructor was a Sr. Data Scientist that really gave us two sides: theoretical and hands-on day-to-day professional experience views. This was very helpful. I found that there're lots of courses out there but most of the times taught by recently-graduated teachers that haven't applied a lot of the syllabus to real-life professional situations. This for me was a plus. The only soft point of the course was that I would have liked to go more deeper into web scrapping, yet it's true this course name is 'data analysis and visualization in R' and not 'Web scrapping using R'. One advice only for prospect students: block your agendas during five weeks since you will need a lot of time to review the materials and deliver exercises, which after all it's not a bad thing as it makes you feel good as you feel you have learned a lot. Highly recommended. -
Data Science with R: Data Analysis and Visualization
This course was a masterpiece. Derek Darves the instructor, quickly brought us to competency with the R programming language. Then he expanded the course by introducing the packages used for analysis and visualization, progressing through introductory use to somewhat elegant and sophisticated programming challenges. Ultimately Derek brought us to a self-sufficiency level for continuing our R education. The course was a pleasure as Derek is clearly an R expert and aficionado weaving many practical tips and historical insights into the lectures. His programming experience, statistical insights and extensions of the course materials gave it a graduate level feel, while never ignoring the fundamental skills being taught. I highly recommend it. -
Introductory Python
I took the beginner level Python class with John Downs and really had a great experience. John is very knowledgeable about Python and programming in general, and was able to be helpful to students of all levels in the class. The exercises in class and the homework got our hands dirty with the language and the final project was a great way to create a real result by the end of the course. Overall it was challenging, but a valuable intro to a useful tool that was easier to approach with real-life sessions than self-study demos on my own. I'll definitely take classes with NYC Data Science Academy in the future and would recommend it to my friends. -
Introductory Python
The instructor, John Downs, was very knowledgeable and did an excellent job of providing an overview in the key areas of Python. After the five week class I went from knowing essentially nothing about Python to using it as one of my "go to" tools in which I am able to accomplish tasks at work on a daily basis. -
Data Science with Python: Machine Learning
I took Machine Learning with Python and Data Analysis with Python in the Spring. I found both course useful and informative. The courses have given me a comprehensive and yet in-depth introduction into Machine Learning and Python. And these skills turn out to be invaluable at work. Most importantly, Vivian is an excellent instructor. She is immensely helpful and supportive which makes the learning process quite enjoyable. Definitely recommend NYC Data Science Academy!