Data Analytics Foundations to Core Bootcamp

Become a data analyst from scratch. Land a job or your money back.

Become a data analyst from scratch. Learn on your schedule with 1-on-1 support at every step. Land a job or your money back.


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Go from beginner to job-ready in as little as 7 months

This program was built to give beginners a pathway to a data analytics career. You’ll start with the Foundations curriculum — learning the skills you need to pass the Data Analytics Career Track Technical Skills Survey. Then you’ll transition to the Core curriculum. All at no extra cost.

By the end of Foundations you will:

  • Build your Excel skills using key functions to analyze a dataset

  • Solve problems with frameworks used by actual analysts

  • Improve your structured thinking foundations

  • Confidently tackle the Data Analytics Career Track Technical Skills Survey — what you’ll need to pass to start the Core curriculum


Data Analytics Foundations to Core vs. Career Track

Get everything in the Data Analytics Career Track and more, all for the same cost when you enroll in Data Analytics Foundations to Core.

Data Analytics Foundations to Core bootcamp

Data Analytics Career Track bootcamp

Prior data experience required

No, you’ll learn basic analysis and more in Foundations


Course length (part-time)

7 months

6 months

Award winning data analytics curriculum



Springboard Job Guarantee*



1:1 expert mentorship



1:1 career coaching



Lifetime access to your Springboard account



Upfront tuition with discount**



What you’ll learn in this data analytics bootcamp

Over 7 months, you’ll learn the core skills needed to succeed as a data analyst.You’ll start work covering basic mathematical constructs and logical inferences. Once you pass the Technical Skills Survey, you’ll enter the Core curriculm and unlock technical units where you'll build a solid foundation for structured thinking, visualization, and data storytelling.

1: Basic Mathematical Constructs as a Data Professional

2: Visualizing Numerical Data

3: Logical Inferences

4: Pre-TSS

5: Technical Skills Survey

6: Structured Foundations

7: Microsoft Excel for Business Analytics

8: Financial Analysis

9: Economics for Data Analysis

10: Statistics for Data Analysis

11: Visualization Tools

12: The Art of Storytelling

13: Data Connectivity

14: Data Analysis in Python

15: Projects

16: Career Support

Topic 1: Basic Mathematical Constructs as a Data Professional

In this unit, you’ll learn about the most common business metrics that will lay the foundation for the rest of your career.

  • Calculate ratios and percentages for common business metrics

  • Apply basic algebra to calculate particular business KPIs

  • Define financial terminologies such as revenue, profitability, and expense ratios

Topic 2: Visualizing Numerical Data

Understanding and interpreting visual graphics are some of the key skills needed to become a data professional. This unit will explore how to put mathematical concepts into a visual format for consumption by a variety of audiences.

  • Interpret mathematical visualizations, such as bar charts, stacked bar charts, and line charts to make inferences

  • Interpret complex visualizations, such as combo charts, scatter plots, and histograms to understand underlying trends

  • Examine data visualizations while applying algebra to produce data insights

Topic 3: Logical Inferences

In this unit, you’ll begin to wrap your brain around the basics of issues trees, which will give a primer on what to expect in the Core section of the bootcamp. 

  • Apply logical thinking frameworks to solve problems with data using a macro-to-micro framework

  • Construct issue trees to visualize data insights and solve problems

  • Use abstract reasoning to solve problems

  • Prioritize parts of the issue tree in your problem-solving approach

Topic 4: Pre-TSS

At this point in the program, you’ll reach the end of Foundations. Before you take the Technical Skills Survey, you’ll take a mini-quiz encompassing the core skills you’ve learned so far.  

Topic 5: Technical Skills Survey

The Technical Skills Survey (TSS)  is designed to test both your ability to draw insights from data and your basic math skills. You'll work your way through a series of 12 multiple-choice questions mapped to these specific skill sets:

  • Quantitative reasoning (math skills)

  • Percentage

  • Algebra

  • Visual chart (pie chart)

  • Visual chart (line chart)

  • Deductive reasoning/quantitative

  • Ratios

Topic 6: Structured Foundations

In this unit, you'll learn to break down problems into bite-sized chunks, which can be tested via hypothesis trees. This type of thinking will guide your analysis and prevent you from analyzing data for the sake of analysis. 

  • Learn structured thinking through case studies and problem statement worksheets

  • Work through problem-solving frameworks and processes, such as the HDEIP Framework, Seven-Step Problem Solving Framework, and others

  • Break down problems to find a solution using Issue trees, hypothesis trees, and value driver trees

Topic 7: Microsoft Excel for Business Analytics

Excel is an essential tool for day-to-day tasks, from creating detailed dashboards and putting together simple investigations. In this unit, you’ll practice key areas and functions of Excel.  You’ll also work on the first phase of your Capstone project by generating ideas and finding a dataset.

  • Use logical operands and advanced Excel formulas and functions

  • Use Pivot Tables for well-structured data

  • Apply statistical functions

  • Create basic visualizations using tools like bar charts, waterfall charts, and column charts

Topic 8: Financial Analysis

As a data analyst, you’ll have to understand the data in front of you and translate it into a business mindset. In this unit, you’ll learn how to become more fluent in financial concepts.  

  • Apply problem-solving and analytical skills to real-life data sets to derive business insights

  • Define financial terminologies such as revenue, cost of goods sold, earnings before interest, assets, liabilities, and profitability

  • Work on a case study covering creating a problem statement, value driver trees, revenue analysis, total operating expenses, EBIT calculations, and presenting your visualized data

Topic 9: Economics for Data Analysis

In this unit, you’ll begin to unpack economic principles that will drive your data analysis. You’ll understand how the larger economic environment will inform business questions and decisions.

  • Study high-level economic principles like demand, supply, elastic goods, inelastic goods, monopolies, market supply, and cost curves

  • Develop business insights based on data analysis and economic principles

  • Complete a case study on cost-effectiveness and present it

Topic 10: Statistics for Data Analysis

Following a unit on economics, you’ll focus on understanding how statistics make up decision-making. You’ll learn two kinds of statistics — descriptive and inferential. 

  • Descriptive statistics concepts like mean, median, mode, spread, histograms, and box plots

  • Inferential statistics concepts like correlation, confidence intervals, margins of error, and regression

  • Continue with the case study and provide descriptive and inferential stats

Topic 11: Visualization Tools

In this unit, you’ll move away from upfront analysis and work on making your data more accessible to all audiences through visualization tools. Knowing how and when to display trends and patterns in data can make a difference between having your insights and decisions sink or swim.

  • Develop an advanced ability to use two visualization tools: Tableau and Power BI

  • Learn to prepare data, such as reshaping and removing bad data

  • Learn the basics of Data Analysis Expressions (DAX)

  • Work on a case study using the visualization tools you’ve learned

Topic 12: The Art of Storytelling

You’ve prepared your data and developed visualization tools. Now it’s time to craft a cohesive presentation that you will communicate to various stakeholders. When you master the art of effective storytelling through visuals, executives won’t just adopt your analysis — they’ll promote adoption and grow the business based on those key insights. 

  • Learn effective communication strategies, formats, and templates

  • Make effective presentations to technical and non-technical stakeholders, including C-suite executives, through case studies

Topic 13: Data Connectivity

In this unit, you’ll develop a high-level understanding of what databases are, learn about the databases you can use in your work, and how to communicate with databases.

  • Learn SQL best practices in writing queries (including common table expressions)

  • Learn about structured and unstructured databases

  • Complete a mini-project focusing on extracting data from a database via SQL, analyze it, and present your insights

Topic 14: Data Analysis in Python

This last technical unit concentrates on coding skills you’ll need to set yourself apart from your peers in the job market. 

  • Learn basic Python syntax

  • Learn to use Git, GitHub, and Juptyer
    Notebooks to share your code and projects

  • Learn to import and wrangle data

  • Work through practical exercises in Python with real data to extra insights

Topic 15: Projects

You’ll work on two capstone projects to give you the hands-on knowledge of working like a data analyst.

Capstone 1:
Executed in three phases throughout the curriculum, you’ll conduct an end-to-end analysis. Find a data set, structure relevant and valuable problems, perform analysis, create visualizations, and present your findings and recommendations.

Capstone 2:
A more in-depth and technical capstone that enhances your learning of the five steps of the HDEIP framework. You’ll find your dataset, create a problem statement and issue tree, analyze and visualize your data, create visualizations with Tableau or PowerBI, and present your findings. You’ll also extract data from a relational database using SQL and clean data using Python.

Topic 16: Career Support

Career units throughout the bootcamp will help you create a tailored job search strategy based on your background and goals. Topics include:

  • Types of industry roles 

  • Job search strategies

  • Building a network and using it to land interviews

  • Creating a high-quality resume, LinkedIn profile, and cover letter

  • Preparing for technical and non-technical interviews

  • Successful negotiation

NEW: Learn AI from humans in the know

Boost your job search. Improve your ideas. Stand out from the crowd. All with AI as your collaboration partner. Our NEW AI interactive learning series gives you access to experts putting AI to work for their businesses, so you can too. All free when you become a student.

NEW exclusive AI learning series includes:

  • Interactive workshops on AI topics, like prompt engineering

  • Exclusive LIVE lectures and AMAs from industry experts

  • Short courses to hone your AI collaboration skills

  • Access to AI-specific peer communities

Build a portfolio that proves your skills to hiring managers

The best way to learn data analytics is to get hands-on experience using real data. In this course you will complete 29 mini projects and two capstone projects and build an interview-ready portfolio you can show to future employers.

While working on the project, you will:

  • Choose a data set and conduct end-to-end analysis

  • Synthesize insights

  • Create a presentation and share your findings

Past projects from Springboard students
Tyler Hartshorn

Capstone project: Equitability of solar panels

Jorge Marin

Capstone project: Impact of service in professional tennis

Springboard data analytics graduates have achieved life-changing growth. You can too.


Average salary increase of data analytics students who provided pre- and post-course salaries.

September 2022


Of job-qualified individuals who reported an offer, received it within 12 months of graduation.

September 2022


Enrolled students in the data analytics bootcamp since 2019.

September 2022

A data analytics bootcamp with a job guarantee

Invest in yourself with confidence with the Springboard Job Guarantee. If you put in the work and don't land a job, we'll give you a refund. Terms apply.

Eligibility for the Springboard Job Guarantee:

  • Bachelor’s Degree

  • 2 years of relevant work experience 

  • Successful completion of all mandatory coursework, core projects and career development tasks

  • Fulfill all post-completion job search requirements — regular networking, job applications and interviewing

Apply to the next data analytics bootcamp

The data analytics Foundations to Core bootcamp is a seven-month program. Most students devote 15-20 hours a week to complete the course.

4 ways to fund your future

Everyone should have the opportunity for growth. That’s why we offer a range of payment options.

What are data analysts earning?

These are the average salaries of data analysts in the US.


Data as of November 2022; cross-referenced with Glassdoor, LinkedIn, Indeed, Payscale,, BuiltIn, and Comparably.

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