Online Data Science Bootcamp with USF CTPE

Learn the Data Science Method, choose from one of three specializations, and build a portfolio-worthy capstone project.

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About this Data Science Bootcamp with USF CTPE

Data science is one of the fastest-growing fields of this decade. The amount of data created each day has surged thanks to the ubiquitous storage of everything from health records to the millions of actions taken on websites and mobile devices. Being able to make sense of all this data — and thus drive intelligent, outcomes-focused decisions — is a vital skill and one that is at the heart of being a data scientist. Learning data science is one of the best career investments you can make. In fact, according to LinkedIn, data science hiring has increased by 46% since 2019.

Our 100% online, Florida-based USF CTPE Data Science Bootcamp consists of a 400+ hour curriculum designed around two hands-on capstone projects. You’ll learn the Data Science Method, the process that leads to successful data science projects. You’ll also have access to a 1-on-1 industry mentor to discuss your projects with regularly, a dedicated student advisor and career coaches to help you succeed. 

The curriculum is divided into a two-part structure. During your application, you’ll take a technical skills survey to determine your starting line:

  1. Foundations: Provides prep materials and covers essential data science concepts, including Python, that you’ll need to succeed in the program core.

  2. Core: This section contains the bulk of the coursework, and prepares you for a data science career. 

Within the core curriculum, you’ll be able to choose from one of three specialization tracks, where you can learn specialized skills to help you stand out from other data scientists. 

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Data science careers

The Data Science Bootcamp can prepare you for a variety of related roles and specializations. 

Data Science Bootcamp curriculum

Each unit of the Core material will cover a key data science concept and the skills associated with that concept. The units feature a mix of materials: projects, lectures, theory, coding exercises, reading/viewing exercises, and career-related coursework.

The Data Science Method

The Python Data Science Stack

SQL and Databases

Data Storytelling

Statistical Inference

Machine Learning

Career Units

The Data Science Method

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

  • Problem identification

  • Data wrangling

  • Exploratory data analysis

  • Pre-processing and training data development

  • Modeling

  • 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

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

Within the core curriculum, you’ll be able to choose from one of three specialization tracks, where you can learn specialized skills to help you stand out from other data scientists.

  • 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.

  • Capstone 1: 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 2

    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

  • Get unlimited 1:1 mentor support

    Meet regularly with your personal mentor to receive feedback on projects, discuss blockers, and refine your career strategy.

  • Build study plans that work for you

    Complete the course sooner by putting in more hours per week.

  • Plan ahead with 1:1 career coach calls

    Craft your design job search, practice interviews, and negotiate offers.

  • Connect with our community

    Get extra help from other mentors in our community, at no extra cost.

Meet our mentors

Build your skills faster and advance your personal growth with 1:1 mentorship.

Rahul Sagrolikar

Data Science Lead

Kenneth Gil-Pasquel

Data Scientist

Dipanjan (DJ) Sarkar

Lead Data Scientist

Eleanor Thomas

Senior Data Analyst

During the application process, you’ll take a technical skills survey to determine your starting line.

  • Students without prior coding experience with proficiency in math and statistics will be provided units that cover essential data science concepts, including Python, which you’ll need to succeed in the core curriculum.

  • Students with prior experience in statistics and programming, such as software developers, analysts, and finance professionals, will have access to the same introductory units, but they will be optional. You’ll be able to move right into the core curriculum. 


More questions about the program?

Schedule a call with our Enrollment Team by applying now or email Carolina, our Enrollment Advisor, to aid in your decision.

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