nyc-data-science-academy-logo

NYC Data Science Academy

New York City, Online

NYC Data Science Academy

Avg Rating:4.85 ( 300 reviews )

NYC Data Science Academy offers 12-week data science bootcamps in New York City. In these 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 4.85

all (300) reviews for NYC Data Science Academy →

Recent NYC Data Science Academy News

Read all (22) articles about NYC Data Science Academy →
  • 12-Weeks In-Person Data Science Bootcamp

    Apply
    Start Date None scheduled
    Cost$17,600
    Class size50
    LocationNew 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.
    Financing
    Deposit$5,000
    Financing
    $397.88 pm for 60 months
    Tuition PlansWe have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    ScholarshipLimited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill LevelIdeal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Workhttp://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement TestNo
    InterviewYes
  • Big Data with Amazon Cloud, Hadoop/Spark and Docker

    Apply
    Data Science, Hadoop, Spark, Data Structures, Python, Cloud Computing
    In PersonPart Time5 Hours/week2 Weeks
    Start Date None scheduled
    Cost$2,990
    Class size10
    LocationNew 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.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelStudents are expected to be familiar with using an operating system from the command line; knowledge of Python is helpful.
    Placement TestNo
    InterviewNo
  • Data Science with Python: Data Analysis and Visualization (Weekend Course)

    Apply
    Start Date None scheduled
    Cost$1,590
    Class size20
    LocationNew 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.
    Financing
    DepositN/A
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelKnowledge of basic data types (e.g. string, numeric), data structures (e.g. list, tuple, dictionary) Familiarity with concepts of list comprehension and for/while loop
    Placement TestNo
    InterviewNo
  • Data Science with Python: Machine Learning (Weekend Course)

    Apply
    Data Science, R, Artificial Intelligence, Machine Learning
    In PersonPart Time7 Hours/week5 Weeks
    Start Date None scheduled
    Cost$1,990
    Class size10
    LocationNew 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.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelCompletion of Data Science with Python: Data Analysis; Data Science with R: Machine Learning
    Placement TestNo
    InterviewNo
  • Data Science with R: Data Analysis and Visualization (Weekend Course)

    Apply
    Data Science, R, Data Visualization, Data Analytics , Data Structures
    In PersonPart Time7 Hours/week6 Weeks
    Start Date None scheduled
    Cost$2,190
    Class size15
    LocationNew 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.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelBasic knowledge about computer components Basic knowledge about programming
    Prep WorkNone
    Placement TestNo
    InterviewNo
  • Data Science with R: Machine Learning (Weekend Course)

    Apply
    Data Science, R, Machine Learning
    In PersonPart Time7 Hours/week6 Weeks
    Start Date None scheduled
    Cost$2,990
    Class size40
    LocationNew 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.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelKnowledge of Python programming Able to munge, analyze, and visualize data in Python
    Prep WorkKnowledge of R programming Able to munge, analyze, and visualize data in R
    Placement TestNo
    InterviewNo
  • Deep Learning with Tensorflow (Weekends and In-Person Only)

    Apply
    Start Date None scheduled
    Cost$2,990
    Class size15
    LocationNew 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.
    Financing
    DepositN/A
    Getting in
    Minimum Skill LevelObject-oriented programming, ideally Python (introductory course: https://nycdatascience.com/courses/introductory-python/) Simple shell commands, e.g., in Bash (tutorial of the fundamentals: https://learnpythonthehardway.org/book/appendixa.html)
    Placement TestNo
    InterviewNo
  • Full-time Online Data Science Bootcamp

    Apply
    Start Date None scheduled
    Cost$17,600
    Class size25
    LocationOnline
    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.
    Financing
    Deposit5000
    Financing
    • Full Tuition Total $17,600
    • Climb Credit Loan $400* pm for 60 months
    • SkillsFund Student Loan $397.88 pm for 60 months

    Tuition PlansWe have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    ScholarshipLimited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill LevelIdeal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Workhttp://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement TestNo
    InterviewYes
  • Introductory Python (Evenings)

    Apply
    Start Date None scheduled
    Cost$1,590
    Class size40
    LocationNew 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.
    Financing
    Deposit$1590
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    Getting in
    Minimum Skill LevelThis Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming.
    Prep WorkIn the class, we will use Python 3. If you are following this video to set up Python environment, please make sure you download the Python 3.X version starting from 1 min 23 s in the video. Link: https://vimeo.com/160172414
    Placement TestNo
    InterviewNo
  • Part-time Online Data Science Bootcamp

    Apply
    Start Date None scheduled
    Cost$17,600
    Class size25
    LocationOnline
    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.
    Financing
    Deposit17600
    Financing
    • Full Tuition Total $17,600
    • Climb Credit Loan $400* pm for 60 months
    • SkillsFund Student Loan $397.88 pm for 60 months

    Tuition PlansWe have full-financing available through SkillsFund and ClimbCredit financial loan. It is approximately 400/per month for 60 months.
    Refund / GuaranteeNYC Data Science Academy’s refund policy adheres to both ACCET and NYS Education Department guidelines. Visit https://nycdatascience.com/refund-and-regulations/ for more details.
    ScholarshipLimited number of scholarships available to qualified candidates.
    Getting in
    Minimum Skill LevelIdeal applicants should have a Masters or Ph.D. degree in Science, Technology, Engineering or Math or equivalent experience of quantitative science or programming.
    Prep Workhttp://blog.nycdatascience.com/faculty/data-science-bootcamp-pre-work/
    Placement TestNo
    InterviewYes
  • Weijie Deng  User Photo
    Weijie Deng • Graduate Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    I was recommended by one of my friend, who almost had the same background as me and had a job after graduation <from the NYC data science academy Bootcamp>. I came from a business background, and I knew nothing about python until I started the Bootcamp. After 3-month intensive training, I started from zero knowledge in coding to someone can really use machine learning to solve some business questions, and guided me into the world of data science. The instructors are very knowledgeable and very willing to answer all my stupid questions. The curriculums are well-designed and taught the machine learning theories twice, very helpful to me. I enjoyed my time in the NYC Data Science Bootcamp and learned a lot from this onsite Bootcamp.
     
  • Chuanhao Nie  User Photo
    Chuanhao Nie • Graduate Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I attend NYCDSA because one of my friends' recommendation that the bootcamp offers hands on experience of data science. Actually, the bootcamp is as good as I expect. I will never forget the 3 month learning experience. I study very hard but at the same time I feel like I grow a lot. 

    The bootcamp's courses cover everything related to data science, not only the advanced parts such as machine learning and deep learning, but also fundamental skills such as Python, R, SQL. My background is finance. But after studying in the bootcamp, I feel like I am prepared for a data science job. 

    The teachers and teaching assistants here are very knowledgeble. In addition, the classmates you study with have strong academic/working experience. Most of the students here have master or phd degree with 2-10 years' working experience. I would highly recommend NYCDSA.

     

  • Good Starter
    - 10/19/2018
    Anthony Romano  User Photo
    Anthony Romano • Research Scientist • Student Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    N/A

    In the past I've used a lot of online courses to try and learn how to use python in my day to day work but I never felt like I "got it." This in person experience was well organized, provided relevant material and challenging homework. The first day of the class really scared me and had me thinking I bit off more than I can chew, but by the end I felt like I'd learned a lot and am thankful to the instructor Tony for his in class comments and examples. I would recommend this course to anyone who is already conducting data analytics but is looking to branch out to python. The course provides a lot of food for thought and made me feel like I have a solid foundation in python now.

  • Nacho Moreno  User Photo
    Nacho Moreno • Senior Location Analyst at JLL • Student Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:
    N/A

    I attended the 2018 Summer bootcamp and was a great experience! Not only academically but also from a personal perspective. I am currently living in Spain so travelled and relocated all the way from Barcelona to join the NYC Data Science Academy. NYCDSA curriculum is really comprehensive  and the information and assistance you get prior to joining the bootcamp from the acadmy’s staff is really good. It’s assuring coming from that far to know what to expect from the bootcamp and to see how responsive the staff was to any queries I had.

    I have a background in Location Intelligence with no coding experience (just a bit of SQL) and managed to follow the lessons well enough! Not without effort though. The curriculum is gradual and comprehensive, from mainly coding practice and basic statistics to Machine Learning and then more advanced topics like Deep Learning and Big Data.

    Personally I also think is a great experience, the bootcamp allows you to connect and create a Data Science network at the same time you interact with your cohort mates which will be like your family during the 12 weeks that lasts the bootcamp.

    Just one warning! Prepare yourself for working hard during the bootcamp, the more you work the more you will get out of it!

  • Samuel Mao  User Photo
    Samuel Mao • Graduate Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    For anyone who is seriously considering a career in data science, I strongly recommend this bootcamp. My background in MS business analytics has nothing to compare with this bootcamp in terms of Machine Learning and Data Engineering. If you only check out 5/10 of a data science job requirement, this bootcamp will make you 10/10, if you put in the work and time. On top of this, every cohort will allow you to meet people who share the same ambition from diverse backgrounds (profession, educational degree, country). One more thing that must be emphasized is that the faculty and staff here are extremely helpful and instructive. Again, I strongly recommend this place if what I have described above are what you are looking for.

  • Alexey Malafeyev  User Photo
    Alexey Malafeyev • BI developer • Graduate Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    Thank you to Jon Krohn for his approach to teach the lectures and for all his systematic organization of all his materials. Also, for being very attentive to the questions and trying to get back with the constructive help ASAP. And a bit of a personal impression: the mashine vision part of the course was better prepared with the interesting and easy to get examples whereas the NLP part could have been more elaborated, but it is by default the case if you compare these two areas. But, knowing how easy Jon was able to organize the steps for the forst noticed I trully believe it is just a matter of a few more thought on that for him and his Co. It may be also true that one more day of classes would be very nice addition to cover the materials better. The other missing thing was a simple example on how you would deploy the network in any environment to be ised in production.

  • Gurminder Kaur  User Photo
    Gurminder Kaur • Data Scientist • Graduate Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I am very glad that I took the decision of joining NYC Data Science Academy to pursue the field of Data Science. The 12-weeks intensive program equips you with a strong and solid foundation for Data Science, even if you come with no background in data at all. The staff is easily approachable and highly knowledgeable. The academy makes sure that you have a good experience to showcase at the job interviews through four different projects (one of them being a live project, solving a real-world business problem for a company). The academic setup, which includes instructors as well as Tas, is excellent and ensures that you have required support and guidance at each and every step throughout the program.

    They have a strong professional network and even hold a hiring event towards the end of the bootcamp, where you have the opportunity to interact with various companies (across different industries) looking for potential Data Scientists. The academy supports you throughout the process of finding the right job, even after graduating from the bootcamp. Vivian was very helpful with my interview process and providing the right feedback so I can be better prepared and get the job I desired.

    Of course, as with any learning process, the real onus of making sure that you get the most out of the bootcamp lies with you. This is a very intensive 12 weeks program and you need to make sure that you dedicate this period fully to Data Science.

    I thoroughly enjoyed the learning process at the bootcamp. It helps you grow not only as a Data Scientist but also as professional through the diverse mix of students coming from different academic and professional backgrounds. I highly recommend NYCDSA to anyone who is seeking to make a career in Data Science.

  • Igor Gitlevich  User Photo
    Igor Gitlevich • Data Scientist • Graduate Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    The bootcamp program of NYCDSA is designed to take the skillset of every student to the next level regardless of the preliminary expertise.  Covering basics of R and Python during the pre-work and first month of the bootcamp follows by a deep dive into the essence of every popular machine learning algorithm, as well as implementation details and caveats in both, R and Python.  The understanding of these caveats combined with more common knowledge will facilitate and ease the continuous learning and career advancement for years to come.  It is important to note that to get most out of this bootcamp, full dedication is required.

    Anyone who is serious about having career in data science and willing to do the hard work to make it happen should seriously consider this 3-month program. The materials of the courses are superb, and the instructors are world-class, willing to take the time to answer every question with enough attention to ensure that understanding of students progresses.  Finally, the academy’s professional networking events and job search-related workshops give a great boost to the job finding opportunities.  I enjoyed my time at the academy and I wholeheartedly recommend it.

  • Yun Wang  User Photo
    Yun Wang • Research Scientist Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I highly recommended the deep learning course for anyone. Jon is the best teacher. He actively responses to your questions and teaches you in a easy-understainding way. I am very happy that I made the right decision. Starting from zero to having an application idea for my research. 

    Thanks Jon! 

     

  • Daniel Bubb  User Photo
    Daniel Bubb • Principal Software Engineer • Graduate • Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    NYC Data Science Academy was essential in helping me to make the transition from a career in academia to the field of data science.  It is a very intensive course that is filled with statistics, coding, machine learning, natural language processing, big data, and other topics.  Frankly, there were too many topics for me to apprehend while the bootcamp was running, but one of the great features of the course is that you are able to go back and review key lectures - which I periodically do as my understanding of the field deepens.  Another great strength of the curriculum is that you are exposed to a variety of instructors who have different backgrounds and approaches.  I can think of distinctive strengths for Drace, Aiko, Luke, and Zeyu in their presentation and shared perspective.  Vivian and Chris gave terrific seminars on seeking employment and how to interview.  Finally outside lecturers such as Bernard Ong held court and imparted their wisdom and that comes from a wealth of experience in the field.  

        One other strength of the program is in the variety of lecturing styles and the mix of labs, guided activities, and more conventional lectures. I think this allows people with a variety of learning styles to flourish and speaks to the thoughtfulness in constructing the curriculum. The projects are essential to applying the concepts and give you an opportunity to sharpen your coding and analysis skills.

        In the end, as I said previously, it was all a bit much for me to take in during the bootcamp, but there are a series of materials - such as Jupyter notebooks, pdf slides, and videos that I continue to refer back to as I progress in the field.  For me, the challenge was less about the difficulty of the material but the sheer volume.  I tend to get interested in something and don’t want to hear much else until I feel like I have a deeper understanding.  Only then do I like to move on. Were I to do it over, I would be a little more disciplined about indulging my curiosity and pay a little more attention to the flow of material and presentation because they really know what they’re doing and what you need as you progress.

     

    tl,dr:

        I highly recommend this Bootcamp, it was of tremendous value to me.  12 weeks of instruction from deeply knowledgeable instructors who possess keen business acumen and know how to help people get jobs. It was a very enjoyable experience for me to be surrounded by interesting and smart people from all types of backgrounds and each with something unique to contribute to the cohort.

  • Fellow
    - 8/23/2018
    Sam Marks  User Photo
    Sam Marks • Graduate Verified via LinkedIn
    Overall Experience:
    Curriculum:
    Instructors:
    Job Assistance:

    I had a truly rewarding experience at NYCDSA. The staff is approachable and friendly, and the material is relevant for a wide range of data professions.

    The program opened doors to several opportunities for me and the staff sets time aside to help you position and present yourself well for job interviews. I accepted a job from one of NYCDSA's hiring partners, and felt very well prepared for the interview process. Five stars!

    Side note: One recommendation I have for those less familiar with coding (which I was), is to embrace the "have you tried googling that?" culture within Data Science and programming as a whole. While the tendency at a supportive bootcamp is to ask your instructors how to debug a line of code or build an ML template, more often than not the answer is a google search away, and there are TONS of excellent resources out there. Patience and getting comfortable with the process of finding the answers to your questions online is absolutely essential.

Thanks!