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Why Choose the Stony Brook University Data Science Bootcamp?

If you want to learn the skills needed to become a professional data scientist, then the Stony Brook University Data Science Bootcamp is a great place to start. Offered by the #1 public university in New York, this 100% online Data Science Bootcamp will get you job-ready in nine months through an immersive learning experience, 1:1 mentorship with industry professionals and the opportunity to build a portfolio of real-world projects to showcase your skills to future employers. 

Nearly 94 zettabytes of data is produced yearly. Data scientists extract, clean, analyze and organize that data to help executives make decisions based on their discoveries. Most jobs grow an average of 5% over a decade, but the Bureau of Labor Statistics predicts a whopping 36% job growth for data scientists through 2031. 

The online Stony Brook University Data Science Bootcamp provides a solid foundation in programming, statistics, the Data Science Method (DSM) and machine learning. Designed by industry experts, our specialized curriculum teaches students Python data science stack, SQL and databases, statistical inference and machine learning. You’ll be able to execute the DSM for companies, healthcare facilities and other industries. 

Find a job after bootcamp completion with optional career-focused units and 1:1 career coaching. You’ll learn interview strategies, resume building and goal setting to help you become a professional data scientist.

Data Science Career Potential

Data science jobs are considered one of the best jobs in the world. Most roles can command six-figure salaries, with plenty of room for job growth. The Stony Brook University Data Science Online Bootcamp provides a stepping stone to several specialized data science roles with the following annual median advertised salary in New York:

  • Data Scientist: $129,792

  • Data Science Manager: $159,232

  • Data Engineer: $126,848

  • Big Data Architect: $126,521

  • Machine Learning Engineer: $126,521

Annual Median Advertised Salary. Source: Lightcast; Oct 2022 - Sep 2023; 0-3 years minimum experience required. New York.

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Immersive Data Science Bootcamp Curriculum

Our curriculum is designed to fast-track your skills and prepare you for a data science career by teaching you core concepts and execution of the data science method. Job-related coursework includes lectures, projects, theory, coding practices and hands-on learning opportunities.

The Data Science Method

The units center around the Data Science Method. This method involves six steps:

  1. Problem identification.

  2. Data wrangling.

  3. Exploratory data analysis.

  4. Pre-processing and training data development.

  5. Modeling.

  6. Documentation.

The Python Data Science Stack

Python has become the lingua franca of data science. In this section of the course, you'll learn how to program in Python, follow best coding practices, and start using an ecosystem of useful and powerful Python-based tools.

SQL and Databases

In this section of the Core material, you’ll learn how to leverage Structured Query Language (SQL) to query relational database management systems. In other words, you'll use queries to understand the data contained in databases.

Data Storytelling

A data story is a powerful way to present insights to your clients, combining visualizations and text into a narrative. Storytelling is an art and needs creativity. This section will try to get your creative juices flowing by suggesting some interesting questions you can ask of your dataset. It will also cover a few plotting techniques you can use to reveal insights.

Statistical Inference

Statistics is the mathematical foundation of data science. Inferential statistics are techniques that help us identify significant trends and characteristics of a dataset. They’re not only useful for exploring the data and telling a good story but for paving the way for deeper analysis and actual predictive modeling. In this module, you’ll learn several critical inferential statistics techniques in detail.

Machine Learning

Machine learning combines both computer science and statistics to extract useful insights and predictions from data. Machine learning lets us make valuable predictions and recommendations and automatically finds groups and categories in complex datasets.

You'll learn and use the major supervised and unsupervised machine learning algorithms. You'll learn when to use these algorithms, the assumptions they incorporate, their tradeoffs, and the various metrics you can use to evaluate how well your algorithm performs.

Career units (Optional)

Each career unit is interspersed between the technical units and follows the progression of a job search. You’ll learn how to:

  • Create a job search strategy.

  • Create an elevator pitch and LinkedIn profile.

  • Conduct an informational interview.

  • Find the right job titles and companies.

  • Prepare for and get interviews.

  • Interview Effectively.

  • Negotiate Salary.

Specialization Option

Stony Brook University Data Science Bootcamp offers additional units that focus on specific career paths in Data Science. You’ll learn advanced skills that you can showcase to hiring managers.

The Generalist Track

Building on your foundational skills, you’ll be introduced to advanced data science concepts like advanced time series analysis, machine learning topics, software engineering for data scientists and more. These can help you decide future studies and data science roles.

The Business Insider Track

Explore the business analytical and advanced data visualization side of data science. You’ll learn to build predictive machine learning models, identify insights, advanced SQL and more. All of these topics will help you prepare to present findings to stakeholders and executives.

The Advanced Machine Learning Track

Career opportunities in machine learning and artificial intelligence are booming. Learn advanced machine learning skills and concepts, including deep learning. You’ll master machine learning methods, advanced time series analysis, data science at scale, as well as Hadoop, Spark and Python.

Real-World Capstones & Hands-On Projects

Hands-on projects are the best way to learn how to quickly become a data scientist. Along with curriculum-based smaller projects, you’ll build two capstone projects— allowing you to apply the theories you have learned in a real-world context. Your capstone projects are prime portfolio opportunities to showcase your job-ready skills.

Guided Capstone

Your first guided capstone project provides an introduction to the Data Science Method. Your mentors and professors help guide you through the steps of obtaining, cleaning, exploring, modeling and interpreting data. This helps build a foundational understanding early in the program and prepares you for your second capstone project.

Final Capstone

For the final capstone project, you’ll execute the Data Science Method on your own, though you can ask your mentor for advice. You’ll develop a project idea and proposal for a real-world problem, go through the DSM steps, including building a working model and then document and present your work.

Personalized Student Support

The Stony Brook University Data Science Bootcamp combines the convenience of an online format with the personalization of a human support system to ensure you’re never alone during your bootcamp experience. 

Support options include:

  • A student advisor who can help you overcome obstacles.

  • A regular on-going meeting with your personal mentor for project help and feedback.

  • A career coach, depending on your units, to help you decide career goals and a potential trajectory.

  • Access to a Slack community with current and former students.

Online student support

Meet Your Mentors: Learn 1:1 With Industry Experts

One thing that sets the Stony Brook University Data Science Bootcamp apart from other online programs is the opportunity to be mentored by industry experts. You’ll regularly meet with your mentor individually to discuss your progress and upcoming projects and get career advice. We are selective with our mentors, choosing one in 12 applicants.

Rahul Sagrolikar
Data Science Lead
Kenneth Gil-Pasquel
Data Scientist
Dipanjan (DJ) Sarkar
Lead Data Scientist
Eleanor Thomas
Senior Data Analyst

Data Science Bootcamp Prerequisites

The Stony Brook University Data Science Bootcamp is a great data science career starting point, with an immersive, skills-driven curriculum to help you become job ready in a short period of time. Our program is designed for those who are:

  • Fluent in English, both spoken and written.

  • Proficient in math and statistics.

If you have limited coding experience or are well past basics, there are two options. A mandatory technical skills survey will help us determine your starting point.

  • Those with a math and statistical background but no coding experience will be enrolled into foundational units that teach core data science concepts, including Python and other programming languages necessary to succeed in the bootcamp.

  • Students with prior experience in coding, statistics and programming can access the foundational units but will start with the main curriculum. 

Data Science Bootcamp FAQs

Is a data science bootcamp worth it?

Data science bootcamps are worth it if you are looking to switch careers or learn new programming languages and tools. The fast-paced environment of a bootcamp can be beneficial if you have the motivation to learn and apply yourself. 

The Stony Brook University's Data Science Bootcamps provides access to a 1-on-1 industry mentor, optional career curriculum, and a career coach to help prepare you for the next step in your career. 

What is data science?

Data science is the process of extracting knowledge from structured and unstructured data. It involves using mathematical, statistical and computer science techniques to analyze data, identify patterns and relationships and propose insights that can help organizations make better decisions.

Data science is used in a wide range of industries, including finance, healthcare, manufacturing, marketing and retail. It's an important tool for making informed decisions about everything from product pricing to inventory management to customer segmentation.

What does a data scientist do?

A data scientist uses their knowledge of statistics and computer programming to clean data, create algorithms and models and analyze large data sets, looking for patterns and correlations that can help them understand what's happening within the business.

Once they have identified any trends, a data scientist will then create reports and presentations that explain their findings in a way that is easy for non-technical people to understand. This allows business decision makers to make informed choices about how to improve their business based on the data that has been collected.

How long does it take to become a data scientist?

How long it takes to become a data scientist depends on your background and prior experience. A data scientist typically has a mathematics, statistics, computer science, or engineering degree. However, there are many self-taught data scientists who have no formal education in these areas.

A data scientist can get up to speed fairly quickly if they are familiar with Python and have some basic knowledge of machine learning algorithms. But it would probably take someone several months to a year to become a data scientist if they had no prior background in this field.

Our bootcamp can help you prepare to become a data scientist in less than nine months.

What is the salary of a data scientist?

The salary range for a data scientist can vary based on experience, location and company.

For data scientists in the beginning of their career (0-3 years experience), the annual median advertised salary in New York is $129,792.

(Source: Lightcast; Oct 2022 - Sep 2023; 0-3 years minimum experience required. New York.)

How much does a data science bootcamp cost?

Data science bootcamp costs vary, but can be anywhere between $10,000 and $20,000. The Stony Brook University's Data Science Bootcamp is $9,900 when paid upfront, and is much more affordable than a traditional degree program.

More Questions About the Program?

Speak to our enrollment team by completing an application, email Carolina, our enrollment advisor, or explore more frequently asked questions

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