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Why choose UMass Global’s Data Science Bootcamp?

When you enroll in the University of Massachusetts Global online Data Science Bootcamp, you set yourself up for future success in this growing career space. According to CloudTweaks, over 2.5 quintillion bytes of data are generated each day. This truly impressive sum is fueled by many constantly expanding digital markets and applications, including those that employ cloud computing such as social media. 

Modern businesses are working constantly to stay ahead of market demands, which means they are looking to hire experts in data-driven fields - especially data scientists. Such professionals help to uncover actionable insights from data sets, which means they are increasingly in demand. In fact, in 2021, Glassdoor placed data scientist as one of the most in-demand jobs on the market; beaten only by Java Developers as one of the best jobs in the U.S. 

This status is due to data science being an incredibly flexible enterprise. Data scientists can find work in nearly any industry, ranging from entertainment to the financial and healthcare spheres. Data scientists employ statistics, math, computer science, and engineering skills to help these industries work with Big Data to craft actionable business models. This includes crafting new products and services that are designed to meet the demands of modern users. In many respects, this kind of work can be entirely novel and even world-changing, such as helping the healthcare industry develop better applications designed to detect signs of illness - ultimately saving lives. 

During UMass Global’s Data Science Bootcamp, you will be tasked to work through a wide range of technical units designed to help you establish many industry-relevant skills. These skills will help you begin down your career path as a data scientist, including learning all the elements involved in the Data Science Method, or DSM. Our curriculum is carefully crafted by subject matter experts, and it is chiefly designed to give students a full, hands-on experience. Our comprehensive tracks and capstone projects will ultimately allow you to showcase your knowledge to potential employers. In our bootcamp, you do more than just learn, you get an understanding of real-world business concerns and how to tackle them. 

In addition, you’ll have the option to experience career units that will help guide you towards career success. From learning interview strategies to building up your resume, we do all we can to help you pursue a career that’s perfect for you. Read on to learn more about the promising world of data science and get details about our bootcamp.

Data scientist careers

Upon completion of this course, you’ll potentially be able to join the data science industry in a number of roles. The following are just some of the options you may be able to enjoy:

Data Science Bootcamp curriculum

In our Data Science Bootcamp, we cover key data science concepts and skills that are designed to prepare you for a career in the industry. Each unit features a range of materials, including lectures, projects, coding practice, and assorted exercises. All of this career-related coursework will serve to prepare you for the rigors of working as a data scientist.

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.

Specialization tracks

After the core units are completed, you’ll then have the option to choose a specialization track, which will teach you unique skills that are intended to help you stand out from other data scientists. Choose from one of the following:

  • The Business Insider track focuses on developing your data visualization and business analytics skills.

  • The Generalist track offers a mix of technical skills, business skills, and mathematical knowledge.

  • The Advanced Machine Learning track focuses on the deployment of machine learning models.

Career units

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

Choose a track that's right for you

Generalist Track

When working on the generalist track, you will learn how to take on versatile data science roles. Building on the foundational skills you’ve developed in the core curriculum, you’ll dive further into more advanced topics, like advanced time series analysis, machine learning topics, machine learning in the cloud, software engineering for data scientists, and data science at scale, including neural networks, Spark, Pyspark, and Hadoop.

Business Insider Track

This track ultimately aims to provide students with advanced data visualization and analytical skills. This will better help you present actionable data to business stakeholders, taking information from machine learning models and offering that knowledge directly to the organization. Topics include structured thinking, business analytics, advanced data visualization, and advanced SQL.

Advanced Machine Learning

In this track, you’ll learn advanced machine learning techniques. This includes elements like deep learning and the best way to deploy machine learning models. This unit will help you broaden your machine learning skills overall while learning about industry standards. Master advanced time series analysis, deep learning, production machine learning methods, advanced machine learning topics, and data science at scale, including Hadoop, Spark, and Python.

Portfolio projects

Alongside several smaller projects that reinforce learned concepts, you’ll be building two hands-on capstone projects. These projects are designed to serve as portfolio centerpieces that hiring managers will love to see.

Guided Capstone

The first capstone project is a fully guided endeavor that walks you through every step of the Data Science Method. This first capstone will help you establish your foundational understanding of each step, learning how to apply this knowledge piece by piece before you approach your second capstone project.

Final Capstone

Your second, final capstone project also follows the DSM steps but does so with much less guidance. You will be tasked with following the steps yourself, and submitting individual pieces of this capstone as you progress throughout the course.

Student support systems

This 100% online bootcamp is designed to be completed on your own time. However, you’ll have constant support from our team throughout the process, including access to all the following:

  • A student advisor who you’ll work with throughout the program. They are here to help you get over any hurdles and answer questions.

  • A personal 1-on-1 industry mentor who you’ll meet with on regular basis to discuss your projects and receive feedback. 

  • A career coach who will help you develop your job search skills and more.

  • A student community that will provide constructive feedback.

UMass Global

Meet your mentors: Learn with industry experts

Having access to a personal mentor will allow you to build your skills quickly. Mentorship is a critical part of our Data Science Bootcamp. Every one of our experienced mentors is an expert in the field, and will provide you with the following: 

  • Regular 1:1 video calls: Get feedback, discuss roadblocks, and refine your career strategy. 

  • Accountability: Your mentor will help you stay accountable, ensuring that you achieve your professional goals.

  • Dedicated mentor calls: At no extra cost, enjoy additional help from mentors in our community.

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

Is this data science bootcamp right for you?

If any of the above is of interest to you, you don’t need to stop and ask, “Is a data science bootcamp worth it?” Our bootcamp will provide you with everything you need to start a career as a data scientist. No prior coding experience is required, however, it is recommended that you have some proficiency in statistics and programming. In general, anyone who is eager to learn is welcome, as long as you meet the following prerequisites:

  • English fluency (spoken and written), as determined by interactions with the enrollment team

  • Proficiency in math and statistics

During the application process, you’ll also take a technical skills survey to determine where you’ll start in the program. 

  • Students without prior coding experience, mathematical proficiency, or an understanding of statistics will be provided with units that cover essential concepts needed to succeed.

  • Students with prior experience in these concepts, such as professional software developers, will have access to this introductory information but it will instead be optional, allowing them to jump right into the core 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 UMass Global Data Science Bootcamp provides access to a 1-on-1 industry mentor, an optional career curriculum, and a career coach to help prepare you for the next step in your career. 

Is data science a good career in Massachusetts?

Yes, data science is an excellent career choice in Massachusetts. The state is known as a tech innovation hub, home to a wide range of industries such as technology, healthcare, finance, and biotechnology, all of which heavily utilize data science. Massachusetts hosts numerous renowned companies and startups that are continually in search of skilled data scientists to help them turn complex data into actionable insights. Notably, Massachusetts consistently offers competitive salaries for data scientists, often exceeding the national average. The rich, diverse business ecosystem and substantial tech community provide ample networking and professional development opportunities, making the state an attractive destination for data science professionals.

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 type of jobs can you do after a data science bootcamp?
What is the salary of a data scientist?

Forbes reports that the median base salary for a top-level data science manager is $250,000, and for experienced individual contributors, it’s $160,000.

The salary range for a data scientist can vary based on experience, location, and company, but Salary.com reports a range of $121,443 - $150,223.

Are data scientists in high demand?

Data scientists are in high demand. The U.S. Bureau of Labor and Statistics (BLS) reports an expected change in employment of 22% between 2020 and 2030, which significantly outpaces the average of all occupations: 8%. 

How much does a data science bootcamp cost?

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

Is this program really offered by UMass Global?

Yes, University of Massachusetts Global's School of Extended Education has partnered with Springboard to offer online tech bootcamps. Springboard developed the curriculum in partnership with industry experts and hiring managers, and administers and leads the courses. This partnership allows students like you to build technical skills while earning a certificate of completion from UMass Global.

More questions about the program?

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

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