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Data Science Bootcamp with University of Maryland Global Campus

Few fields have seen the sustained growth that Data Science has seen in the past decade. We are creating data at staggering rates. In fact, according to SeedScientific, there are 40 times more bytes in existence than stars in the observable universe. Understanding this data and drawing conclusions from it is a skill that continues to grow in importance. 

The 100% online Data Science Bootcamp at UMGC, in the DMV, contains more than 400 hours of curriculum. Our materials are hand-selected to help you learn the data science method, build a compelling portfolio, and learn the skills that will get you hired in the industry. While you work through the program, we will pair you with a 1-on-1 industry mentor who will work with you regularly by discussing your projects.

Our curriculum consists of two parts. First, when you apply, you will take a technical skills survey to determine your starting place in the curriculum. The two paths are:

  1. Foundations: This path provides you with the skills and knowledge you will need to succeed when you move on to the core program. You will learn essential data science concepts, such as Python.

  2. Core: This path is where most of your coursework will be done and will prepare you for a rewarding career in the data science field.

Once on the Core Curriculum path, you can choose one of three specialization tracks shown further down the page. These tracks will teach you the unique skills you need to excel in specific roles related to the data science field.

Your Path to a Rewarding Data Science Career in the DMV Area

As the need for data science grows, so do the roles available for a skilled data scientist. Here are just a few of the specializations that our Data Science Bootcamp can prepare you for:

  • Data Scientist

  • Data Science Manager

  • Data Engineer

  • Data Architect Manager

  • Machine Learning Engineer

Data Science Bootcamp curriculum

Students who have finished the foundations' path or tested out of it during the initial skills survey will spend their time working on Core material that covers vital data science concepts and the skills associated with those core concepts. These units combine projects, lecture theory, coding, reading/viewing, and career-related coursework. We designed all parts of the curriculum with the ultimate goal of getting you hired in mind.

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

Specialization areas

Our three specialization tracks allow you to dial into an area of expertise you want to excel at and gain the additional knowledge and experience you will need to land a job in that chosen area.

The Generalist Track

This track will prepare you to take on versatile data science roles across a wide variety of business domains and geographical locations. You’ll build on the foundational skills you learned in the core units and tackle more advanced topics like working with Big Data and software engineering best practices.

The Business Insider Track

This track aims to teach you advanced data visualization and business analytics skills to extract actionable business insights. While you will have the ability to build predictive machine learning models, you'll primarily focus on learning how to identify insights and effectively communicate recommendations.

The Advanced Machine Learning Track

This track aims to teach you advanced machine learning skills and concepts, including deep learning and the deployment of machine learning models on standard industry platforms. If you want to broaden your machine learning skills, this track may be the right one for you.

Projects worthy of your portfolio

We never forget that an investment in your education is an investment in your future, which is why we built our bootcamp around preparing you for your future career every step of the way. During your time in the program, you will have two capstone projects that are perfect additions to your portfolio.

Guided capstone

Your first capstone project comes up fairly early in the course. For this project, you’ll be given a lightweight introduction to each step of the Data Science Method. You’ll then be guided through each of those steps with helpful tips and instructions. This first capstone builds your foundational understanding of each of these critical steps while also allowing you to practice each step before applying your knowledge to your second capstone.

Capstone two

This capstone takes place later in the bootcamp and has less guidance. You’ll be asked to:

  • Come up with a project idea and proposal

  • Find and wrangle data

  • Use exploratory data analysis techniques to understand that data

  • Pre-process and create a training dataset

  • Build a working model

  • Document and present your work

Student support

While you can complete our 100% online Data Science Bootcamp on your own time, we make sure that you always have the support you need. Throughout the program, you will have access to a:

  • 1-on-1 mentor: our mentors are matched to you and are experts in the industry. You will regularly meet the mentor and be able to discuss your current projects and industry advice and even get tips on how to develop your career.

  • Student advisor: throughout the program, you will be able to work with a student advisor who can answer any questions and help you overcome challenges you face along the way.

  • Community of your peers: connect with a community of fellow students and talk about your projects, insights, problems, etc. Your community can be a valuable asset throughout your program and for many years to come.

  • Career coach: At the end of the day, we want you to land a job in your dream field, which is why our career coaches are here to help you develop the job search skills you need to find the right company for you.

University of Maryland Global Campus

Meet our 1-on-1 mentors

One of the things that make our bootcamps stand out is the mentorship model. By meeting regularly with your mentor, you will stay accountable, be able to discuss current progress, and gain real-world wisdom. Our mentors are experienced data scientists, and we only accept 1 out of 12 applicants for the mentorship role.

Meet some of our current Data Science Bootcamp mentors:

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

To be accepted into this bootcamp you must possess the following:

  • English fluency (spoken and written), as determined by our enrollment team.

  • Proficiency in math and statistics

During your application, you will have to take a technical skills survey which will determine your starting point in the program:

  • We place students with no prior experience or proficiency in math and statistics on the foundations' path. You will be provided units covering essential data science concepts, such as Python, and can move into the core path after completing foundations.

  • Students with prior statistics and programming experience, such as software developers, analysts, and finance professionals, will still have access to the foundations' units but are not required to complete them. You will be able to delve into the core curriculum immediately.

Data Science Bootcamp FAQs

Is data science a good career in the Washington metropolitan area?

Absolutely! Data science is a rapidly growing field, and the Washington metropolitan area is no exception. With numerous industries, government agencies, and non-profit organizations located in the region, there is a high demand for skilled data scientists who can analyze, interpret, and communicate complex data insights. Additionally, the average salary for data scientists in the D.C. area is well above the national average, making it an attractive career choice for those interested in both the field and the region.

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 Data Science Bootcamp at University of Maryland Global Campus 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. 

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 reports a range of $122,904 - $152,027.

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 Data Science Bootcamp at University of Maryland Global Campus is $9,900 when paid upfront, and is much more affordable than a traditional degree program.

More questions about the program?

Schedule a call with our Enrollment team by completing the 'Apply Now' form or email Carolina, our Enrollment Advisor, who will help you think through the decision.

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