Data Science Bootcamp

Applications for this bootcamp are closed.

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Prepare For A Data Science Career

What You Will Learn

  • Python and R

    You will learn to create data analytic workflows in the two most widely used programming languages in data science. You will learn the editors, IDEs, source code control systems, etc. used by Data Scientists.
  • Data Science Toolkit

    You will gain facility in using the most popular libraries and packages associated with Python and R, e.g. pandas, scikit-learn, the tidyverse. You’ll learn to use RStudio and Jupyter Notebooks for writing code and documenting workflow.
  • Data Science Process

    You’ll learn the project life-cycle of a typical data science project. You’ll learn how to identify the business question, how to create and refine your hypothesis, build models, test and iterate the analysis, and ultimately deploy the resulting data product and communicate the results.
  • Managing and Curating Data

    You’ll learn the process of collecting, extracting, querying, cleaning, and aggregating data for analysis. You will apply the tools in both the Python and R toolkits to this process in multiple projects. You’ll spend time wrangling data, understanding data quality issues, and learning how to clean data. You will work with a variety of data sources from unstructured/semi-structured text files to delimited/structured file formats such excel, csv, json, xml etc. You’ll also learn about web scraping and working with APIs.
  • Exploratory Data Analysis

    You will learn exploratory techniques for visualizing & summarizing data. These techniques are typically applied before formal modeling. Exploratory techniques are important for eliminating or sharpening potential hypotheses as well as identifying problems with the data that need to be addressed before modeling. We will cover plotting libraries (matplotlib, seaborn, ggplot2, etc.) as well as some of the basic principles of constructing data visualizations.
  • SQL, Data Management & Big Data

    You’ll master the use of SQL to query relational databases. You’ll also be introduced to the 4 main types of NoSQL systems and understand the tradeoffs of using each one.

    You’ll be introduced to techniques for working with Big Data in a cloud environment.
  • Machine Learning: Supervised Learning

    You’ll learn to use training data to develop supervised machine learning models and apply them to a range of different problems. Some of the concepts you’ll learn about include:
    • Cost Function
    • Overfitting/underfitting
    • Optimization techniques
    • Linear and logistic regression
    • Decision trees
    • Classification models
    • Recommender systems
  • Machine Learning: Unsupervised Learning

    You’ll learn to apply unsupervised machine learning algorithms to uncover trends and patterns in data. You'll get familiar with:
    • Clustering methods, including K-Means and Affinity Propagation
    • PCA & Dimension Reduction
    • Anomaly Detection
  • Natural Language Processing

    You will learn to extract meaning from text by applying techniques such as:
    • Tokenization
    • Topic identification
    • Named Entity Recognition
    • Text classification
  • Data Visualization and Communication

    A key skill for data scientists is presenting the results of their projects to business decision makers and other stakeholders. You’ll learn common tools and techniques of data visualization and how to use them for effectively communicating the story of your data and your analysis.
  • Real-World Projects

    You will be able to apply the skills you are learning to real-world datasets and problems from various domains, such as healthcare, financial services, entertainment, consumer marketing/retail, and government. Projects will be executed primarily in a team environment so you’ll get experience working with others in a multi-disciplinary project team.

    Your capstone project will be an individual effort that demonstrates your ability to take a data science project through the entire data science process. This project will demonstrate to potential employers your ability to apply the skills learned in this class to a real-world problem and present your findings.
  • Career Preparation

    Throughout the bootcamp you will also be preparing to move into a data science job. You’ll meet working data scientists from several industries. We’ll hold workshops on resume preparation/marketing yourself, interview preparation, negotiating, and more. And we’ll introduce you to prospective employers at your class Demo Day and support you after graduation during your job search.
  • Learn To Work On A Remote Team

    NSS’s live online experience prepares you to work with teams remotely. You’ll learn to communicate in a remote environment through virtual interactions with your instructors and classmates on Zoom, asynchronous communication tools like Slack, and written code reviews with Git and GitHub.
  • Post-graduation Support

    Our support doesn’t stop at graduation. Our career development team will continue to work closely with you during your search for your first job in tech. We’ll share job postings that we receive from employers looking to hire NSS graduates. You’ll be invited to weekly job search support sessions that cover everything from technical refreshers to interview prep and peer connection. We’ll connect you with community resources like Code Campfire and meetup groups. And you will have access to available seats in our continuing education courses to keep building skills while you search.

Student Experience

  • Asha Maheshwari

    Graduated 2023

  • Michial Miller

    Graduated 2023

  • Tomo Umer

    Graduated 2023

Requirements

Student requirements

  • At least 18 years of age

  • American citizen or legally able to work in the U.S.

  • Due to regulatory constraints, we are unable to accept students residing in the state of California at this time.

  • Ideal applicants will have experience in quantitative science or programming. Students will be expected to demonstrate prior training in and/or experience applying the math skills relevant to data science. In particular we will be looking for students with training in statistics/probability. This prior knowledge can be gained through classes, research project experience, work experience, and/or our Statistics for Data Science course.

Hardware/Software requirements

  • Personal laptop meeting our hardware requirements. See this blog post for full details of our laptop specs.

  • Accepted students will be given requirements for software to be downloaded prior to the start of class. It is not expected that any such software will have a cost as the class will focus on teaching data science using open source technologies.

Tuition Details

There are two tuition plans: Regular Tuition or Nashville Tech Opportunity Tuition. A limited number of grants and scholarships are also available for students from underrepresented groups.

Regular Tuition

Regular tuition for the Data Science Bootcamp is $13,125.

We request a $5,000 deposit on acceptance of our offer of admission. The balance is due at enrollment on the first day of class. You may also elect to pay the balance during the nine months of the program through an approved payment plan, as discussed below. See below for other financing and payment options.

Nashville Tech Opportunity Tuition

The NSS Nashville Tech Opportunity Tuition allows you to defer most of the cost of your training until you graduate and go to work. You will pay us $2,000 as a tuition deposit on acceptance to the program and then nothing more until after graduation.

This program is a mutual risk-sharing program between NSS and the Student. NSS invests in the student through a scholarship and through deferring the balance of the student's tuition until the student a) graduates and b) becomes employed as a developer. Until those conditions are met, the student does not owe NSS the tuition balance.

Once you go to work using the skills you learned at NSS, we'll work out a payment plan for you to reimburse NSS. We also have a limited number of partner companies that are willing to reimburse part or all of your tuition.

  • Initial tuition deposit of $2,000, due on acceptance of our offer of admission
  • $2,500 scholarship
  • $8,625 tuition balance to be repaid on employment as outlined above
Selection criteria for the Nashville Tech Opportunity Tuition includes:
  • Limited to Nashville area residents or individuals who grew up in Nashville/Middle Tennessee and have strong family and personal connections to the area
  • Limited to students that are committed to staying in Middle Tennessee post-graduation
  • Priority is given to students whose economic circumstances would otherwise prevent them attending Nashville Software School
  • Priority is also given to individuals from groups that are underrepresented in tech careers (e.g. women, Veterans, Black individuals, etc.)

Scholarships

We have available a limited number of scholarships between $2,000 and $5,000 for high potential students with economically disadvantaged backgrounds or from groups that are underrepresented in technology careers.


Financing/Payment Plans

Payment Plans

If you are paying for regular tuition out-of-pocket, there are three payment options:

Payment 1 Payment 2 Payment 3+ Total Cost
Option 1: Early-bird Discount $5,000 deposit due after admission. $7,500 due before the first day of class (reflects $625 early-bird discount). N/A Total cost: $12,500
Scholarship and student loan recipients are not eligible for the early bird discount.
Option 2: Deposit + 2 Additional Payments $5,000 deposit due after admission. $4,062.50 due before the first day of class. $4,062.50 due on or before the first day of the second half of the course. (i.e. 4 and a half months after start date). Total cost: $13,125
Option 3: Deposit + Monthly Payments $5,000 deposit due after admission. $1000 due before the first day of class. Eight monthly installments of $921.88 due on the 1st of each month. Total cost: $13,375

Student Loans

To provide additional financing options and support for our students, we've teamed up with Sallie Mae® and Climb Credit who specialize in loans for bootcamp students and only partner with the most reputable code schools in the country. We encourage you to consider all the options and choose the one right for you. All are free to apply!

*Loans are only available to regular tuition students to cover tuition. They will not cover additional funds for living expenses, like housing and transportation.

  • Sallie Mae®

    Sallie Mae® Student Loans

    The Smart Option Student Loan* can help you cover tuition costs. You can choose from multiple repayment options that help you while you're in school and in repayment. Loans are on a 10 year tenor, with no prepayment penalty. To apply, click here.

    Details for Data Science:
    • Deposit due to NSS: $0 to $1,500 (You may include your deposit in your loan for the Data Science Bootcamp.)
    • Maximum amount you can borrow for the Data Science Bootcamp: $13,125
    • Length of Loan: 10 year tenor, no prepayment penalty
    • No loan origination fee.
    Loan Application


    Applicants should reference the administrative processing code 609570-00 when contacting Sallie Mae®.

  • Climb Credit Financing Student Loans Climb Credit Verified Partner School

    Climb Credit

    Climb Credit provides simple, fast, and affordable loans to help you meet your career and financial goals. Climb Credit offers fixed interest rates on 36-month terms (subject to approval). To learn more and apply, click here.

    Details for Data Science:
    • Deposit due to NSS: $1,500
    • Maximum amount you can borrow for the Data Science Bootcamp: $11,625
    • Length of Loan: 36 months
    Loan Application
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