Data Analytics Program

Become a data analyst
in under 10 months
Learn flexibly online
without having to quit your job
Work with expert mentors
and build your portfolio

Get a free
Data Analytics short course

Get a free
Data Analytics short course

Curious about this program?

Contact us to find out if it’s right for you

Career Advisor

“How would you like to get in touch?”

“I’m here to help you become a data analyst”

Alana, Senior Program Advisor

Curious about this program?

Contact us to find out if it’s right for you

Career Advisor

“How would you like to get in touch?”

“I’m here to help you become a data analyst”

Alana, Senior Program Advisor

Our graduates now have tech jobs all over the world

Apply for one of our 100 partial scholarships this month and get up to 18% off the career change program of your choice! Speak with one of our advisors to learn more 🙌

The Data Analytics Program

Your launchpad into a career in data analytics

Gain a rigorous education in data analysis, testing, visualization, dashboarding, querying, and how you can solve real customer problems—all with lifetime curriculum access after graduation

Build the technical skillset of every great analyst, adopting tools for statistical evaluations, data analysis, and visualization such as Excel, Python, libraries like Pandas, Tableau, and more

Work with a team of active industry experts offering 1:1 mentorship on every assignment and project review, including a capstone project you’ll use to conquer your local job market

Find your industry passion through a specialization course, deciding between the AI-trending Machine Learning with Python or the industry staple of Data Visualizations with Python

Earn real-world work experience with a stand-out portfolio and the chance to gain hands-on apprenticeship training with our partners: TechFleet, Democracylab & Digital Product School

Launch into the world of data analytics and land the role you want with 1:1 career specialist guidance to build a competitive application package and job search strategy, all on our Career Support Center

 

Starting every two weeks

Learn online 30–40 hours/week for 5 months or 15–20 hours/week for up to 10 months

Top-quality mentorship

Our data analytics mentors are seasoned industry experts with a 4.94/5 rating

Support from start to finish

Enjoy the Job Preparation Course with career coaching included

What makes data analytics the right career?

Storytelling is at the heart of data

Data analysts work at an exciting crossroads. They dive into understanding and translating the complex stories behind data sets to solve customer challenges. They combine the hard skills of analysis and interpretation with the soft skills of teamwork and detail-oriented communication.

Analysts are a permanent staple of tech

Despite AI’s arrival and Big Tech layoffs, data analyst positions continue to surge. The average junior data analyst salary in the United States is $59,679 per year, while senior analysts can earn as much as $108,000, according to PayScale, meaning demand is only on the rise.

Work-life balance is baked in

Working remotely or hybrid is a top benefit of working in tech. Data analytics offers a career that is creative, flexible, and yes, cost-saving. Graduates go on to earn more, work on rewarding projects that solve real problems—and enjoy more time for loved ones and hobbies at home.

What makes CareerFoundry the right school?

We’re the proven path to professional success

Since 2013 we’ve helped 7000+ career changers move from diverse backgrounds like teaching, taxi driving, or opera singing to tech professionals. Our model of industry-driven curriculum, flexibly-paced learning, and expert mentorship ensure graduates land careers they love.

Learn on your schedule, backed by our Job Guarantee

Study flexibly by choosing your own timeline. Immerse yourself in the curriculum, and build your portfolio around your other commitments. Work with your advisor on job coaching and land your first role within six months of graduation or your money back—that’s the Job Guarantee.

Successful, satisfied graduates

We’re constantly evolving our curriculum to be industry relevant. That includes AI specialization courses, like Machine Learning for Python. Through research and working with industry experts, we ensure success—and our 90% graduate placement rate reflects that.

Data Analytics Program Curriculum

A rigorous and industry-relevant education built with beginners and upskillers in mind

Curriculum overview

Part-time
Flexible
Full-time
Intro to Data Analytics
approx.
1 month
Data Analytics Immersion
approx.
7 months
Specialization
approx.
2 months
Intro to Data Analytics
approx.
0.5 months - 1 month
Data Analytics Immersion
approx.
3.5 - 7 months
Specialization
approx.
1 - 2 months
Intro to Data Analytics
approx.
0.5 months
Data Analytics Immersion
approx.
3.5 months
Specialization
approx.
1 month
info-icon

Completion times are approximations based on the progress of our current students and graduates

Intro to Data Analytics
Data Immersion
Specialization

This course will take you through ten tasks leading up to one main project: a descriptive analysis of a video game data set to inform product development and sale strategies.

curriculum curriculum-box heading image
1.1 Data Analytics in Practice

Learn what data analysts do and get ready to kick off your own analysis.

1.2 Introduction to Excel

Get to know Excel and learn how to sort, filter, format, organize, and visualize data.

1.3 Understanding Your Data Set

Analyze and describe your data set, then identify sources of bias.

1.4 Cleaning Your Data

Identify errors in your data and learn how to clean your data and minimize issues.

1.5 Grouping & Summarizing Your Data

Create and manipulate pivot tables and learn more advanced Excel skills.

1.6 Introduction to Analytical Methods

Explore different approaches to data analytics and the role of statistics.

1.7 Conducting a Descriptive Analysis

Conduct a descriptive analysis by applying statistical methods in Excel.

1.8 Developing Insights

Learn how to form hypotheses about data sets, and to generate useful insights.

1.9 Visualizing Data Insights

Build helpful visualizations of your data to present findings to stakeholders.

1.10 Storytelling with Data

Learn to present the results of your analysis in compelling ways.

Immerse yourself into the mindset, processes, and tools that data professionals use every day. You’ll complete a total of six projects (achievements) consisting of several tasks each.

curriculum curriculum-box heading image
Achievement 1
Achievement 2
Achievement 3
Achievement 4
Achievement 5
Achievement 6
Preparing & Analyzing Data

Learn how to interpret business requirements to guide your data analysis and begin developing and designing your data project. Here’s what you’ll learn:

A Brief History of Data Analytics

Starting with Requirements

Designing a Data Research Project

Sourcing the Right Data

Data Profiling & Integrity

Data Quality Measures

Data Transformation & Integration

Conducting Statistical Analyses

Statistical Hypothesis Testing

Consolidating Analytical Insights

Data Visualization & Storytelling

Explore the different types of data visualization and what they can be used for, as well as some best practices to keep your visualizations accessible and easily interpretable.

Intro to Data Visualization

Visual Design Basics & Tableau

Comparison & Composition Charts

Temporal Visualizations & Forecasting

Statistical Visualizations: Histograms & Box Plots

Statistical Visualizations: Scatterplots & Bubble Charts

Spatial Analysis

Textual Analysis

Storytelling with Data Presentations

Presenting Findings to Stakeholders

Databases & SQL for Analysts

Develop database-querying skills while mastering SQL, the industry-standard language for performing these tasks in the real world.

Intro to Relational Databases

Data Storage & Structure

SQL for Data Analysts

Database Querying in SQL

Filtering Data

Summarizing & Cleaning Data in SQL

Joining Tables of Data

Performing Subqueries

Common Table Expressions

Presenting SQL Results

Python Fundamentals for Data Analysts

Get hands-on with Python—the go-to language used by data analysts to conduct advanced analyses. Here’s what you’ll learn:

Introduction to Programming for Data Analysts

Jupyter Fundamentals & Python Data Types

Introduction to Pandas

Data Wrangling & Subsetting

Data Consistency Checks

Combining & Exporting Data

Deriving New Variables

Grouping Data & Aggregating Variables

Intro to Data Visualization with Python

Coding Etiquette & Excel Reporting

Data Ethics & Applied Analytics

Learn how to identify and address data bias, data privacy, and data security. You’ll also explore big data analysis, machine learning, and data mining.

Intro to Big Data

Data Ethics: Data Bias

Data Ethics: Security & Privacy

Intro to Data Mining

Intro to Predictive Analysis

Time Series Analysis & Forecasting

Using GitHub as an Analyst

Preparing a Data Analytics Portfolio

Advanced Analytics & Dashboard Design

Complete an analysis project using data of your choosing, and build on your advanced analytics skills by taking a dive into machine learning and regression analysis.

Sourcing Open Data

Exploring Relationships

Geographical Visualizations with Python

Supervised Machine Learning: Regression

Unsupervised Machine Learning: Clustering

Sourcing & Analyzing Time Series Data

Creating Data Dashboards

To further develop your expertise, you’ll choose one of two specialization course options: Machine Learning with Python or Data Visualizations with Python.

curriculum curriculum-box heading image
Data Visualizations with Python

Achievement 1

Achievement 2

Machine Learning with Python

Achievement 1

Achievement 2

Network Visualizations and Natural Language Processing with Python

Learn how to create network visualizations and identify the relationships between different elements of data.

Intro to Freelance and Python Tools

Setting Up the Python Workspace

Virtual Environment in Python

Accessing Web Data with Data Scraping

Text Mining

Intro to NLP and Network Analysis

Creating Network Visualizations

Dashboards with Python

Learn about the intricate functionalities and settings of Python’s core visualization libraries.

Tools for Creating Dashboards

Project Planning and Sourcing Web Data with an API

Fundamentals of Visualization Libraries Part 1

Fundamentals of Visualization Libraries Part 2

Advanced Geospatial Plotting

Creating a Python Dashboard

Refining and Presenting a Dashboard

Basics of Machine Learning for Analysts

Dive into ethics, start preparing your data for supervised and unsupervised learning, and look into optimization algorithms.

The History and Tools of Machine Learning

Ethics and Direction of Machine Learning Programs

Optimization in Relation to Problem-Solving

Supervised Learning Algorithms Part 1

Supervised Learning Algorithms Part 2

Presenting Machine Learning Results

Real-World Applications of Machine Learning

Look into more complex machine learning concepts, as well as unsupervised learning, deep learning, and visual data.

Unsupervised Learning Algorithms

Complex Machine Learning Models and Keras Part 1

Complex Machine Learning Models and Keras Part 2

Evaluating Hyperparameters

Visual Applications of Machine Learning

Presenting Your Final Results

Intro to Data Analytics

This course will take you through ten tasks leading up to one main project: a descriptive analysis of a video game data set to inform product development and sale strategies.

1.1 Data Analytics in Practice

1.2 Introduction to Excel

1.3 Understanding Your Data Set

1.4 Cleaning Your Data

1.5 Grouping & Summarizing Your Data

1.6 Introduction to Analytical Methods

1.7 Conducting a Descriptive Analysis

1.8 Developing Insights

1.9 Visualizing Data Insights

1.10 Storytelling with Data

Data Immersion

Immerse yourself into the mindset, processes, and tools that data professionals use every day. You’ll complete a total of six projects (achievements) consisting of several tasks each.

Specialization

To further develop your expertise, you’ll choose one of two specialization course options: Machine Learning with Python or Data Visualizations with Python.

Data Visualizations with Python

You’ll process data, and build polished visualizations and dashboards with Python for an academic research organization and a bike-sharing company

Machine Learning with Python

You’ll use machine learning to make long-term predictions about climate change for certain types of populations around the globe.

The Future of Data and AI

It’s no secret that the tech industry evolves quickly. Data analysts—like all professionals—need to stay up-to-date with automation, AI, and relevant new tooling. At CareerFoundry, it’s our job to ensure you’re a top hire with industry-relevant experience.

Not only are we expanding our curriculum to help you supercharge your career and explore the power of AI—but we’re also offering regular, live events hosted by expert mentors on utilizing automation to maximize productivity.

And for those who can’t get enough, we’re releasing our specialization course, Machine Learning for Python, included in program costs and uniquely built for graduates to stay one step ahead of the competition.

future with AI
Create head-turning work with industry-standard tools
course-tools
A pillar of your data analytics education is, of course, tooling. Attend free workshop events and become a CareerFoundry student to gain free trials and exclusive discounts. Whether immersed as a student, or still researching data analytics, prepare to explore industry staples: Excel, Tableau, Python, Anaconda, Jupyter, GitHub, PostgreSQL, and more.
Student perks

Get exclusive hands-on work experience

  • Gain real-world data experience when you apply for one of our partner apprenticeships
  • Build a portfolio based on real-world projects, including an optional bonus project
  • Forge a stand-out applicant profile built on portfolio work, end-to-end capstone projects, industry exposure, and demonstrable expertise you can point top employers to
  • Build your soft skills on external work experience placements and partner with other analysts, engineers, data scientists, developers, marketers, and product managers
I am beyond grateful for the apprenticeship as it actually led to me landing a full-time job. Thanks to both CareerFoundry and Tech Fleet this past year has been an amazing success!

Lade Kolawole

CareerFoundry graduate

Success Stories

Our students go on to launch challenging new careers in the tech industry

Portfolio projects

Our graduates now work at...

Data Analytics Program admission criteria

What you need:

 

The motivation to transform your career

Even though you can study flexibly, the program requires some commitment as it takes a minimum of 15-20 hours per week to complete in 10 months.

An interest in data analytics

If you're already reading books and blog posts about different types of analysis, that is a great start. If you are unsure if data analytics is really for you, here are some great ways to explore it:

Written and spoken English skills at a level B2 or higher

A computer (macOS, Windows, or Linux) with a webcam, microphone, and an internet connection

What you don’t need:

 

A background in data analytics or tech

This program is designed to take you from beginner to job-ready—regardless of your background. And now more than ever, employers see bootcamp graduates as excellent job candidates. A 2021 study by Career Karma found that companies as respected as Amazon, Google, Facebook, and Microsoft are some of the largest employers of bootcamp graduates. The same study revealed that, in 2020, those same companies hired up to 120% more bootcamps graduates than they did in 2019!

Unlimited free time

You can study part-time at 15-20 hours per week to finish the program within 8 months; or complete the program in as little as 5 months by studying up to 30-40 hours per week. 

To learn all on your own

You can enjoy the flexibility of online learning with the accountability and one-on-one attention traditionally associated with brick-and-mortar institutions. Much like a college professor might inspire you to pursue a career in a certain field, your mentor, tutor, career specialist, and student advisor will keep you motivated and on track.

Price and payment options

Next start dates:

Pay upfront

Get 5% off your tuition when you make a one-time, upfront payment.

upfront, then for months

Pay monthly

Pay today to secure your place, and then per month for months.

€6900

€1500 upfront, then €450 for 12 months

Pay monthly

Pay €1500 today to secure your place, and then €450 per month for 12 months

$158*/month

$158* per month for 60 months

Pay less per month

Apply for an education loan with one of our partners (Ascent or Climb) and benefit from low monthly payments over an extended period.

*Installments depend on your approved interest rate.

$0 upfront

Pay later

Apply for deferred payment with our one of our partners (Ascent or Climb) and only start paying for your program several months after completion.

€0

Only available for residents in Germany

Bildungsgutschein

Talk to your local job center to find out if you're eligible. You can download our application guide for step-by-step instructions.

Need a more flexible payment plan?

We can set up a custom payment plan that better suits your needs. Book a call with a program advisor to learn more.

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FAQ

1.    Is becoming a data analyst a secure career choice?

In short, yes—there’s a high demand for qualified data analysts. In fact, World Economic Forum’s 2020 Jobs of Tomorrow report identified data analytics as one of seven high-growth emerging professions.

Curious about what salary you could earn? Check out our data analyst salary guide.

2.    What are the prerequisites and requirements for the program?

This program is designed with the absolute beginner in mind. Meaning, there are no prerequisites or prior experience in data analytics or tech required.

Regardless of age or background, we’ve built a learning experience to ensure your success. From the catered curriculum and hands-on exercises to one-on-one mentorship and support throughout.

What’s required*:

  • Motivation to transform your career
  • Interest in data analytics
  • Written and spoken English proficiency at a B2 level or higher
  • A computer (macOS, Windows, or Linux) with a webcam, microphone, and an internet connection
*Note that you will be required to invest some independent study time into familiarizing yourself with the tools you’ll use throughout the program, and learning how to use them. It is estimated that you will need to spend an additional 1-2 hours per week of extracurricular study time becoming comfortable with them.
3.    Which tools will I use and what are the costs?

In the Data Analytics Program you’ll use Microsoft Excel, as well as Tableau, Python, Anaconda, Jupyter, PostgreSQL, GeoPandas, and GitHub.

All tooling for this program is free to use, apart from Microsoft Excel, where you can get a free one-month trial through the Intro to Data Analytics Course. After the month trial, you’ll be able to purchase one month only (as opposed to a full subscription) in order to continue on and complete the first Achievement in the Data Immersion Course.

For further tool requirements related to specialization courses, please view their respective pages:

4.    What are the minimum system requirements?

Compatible operating systems: Windows 10, macOS versions 10.13 and later, Ubuntu, Debian, CentOS, or Fedora (Linux). We recommend a minimum of 12 GB of RAM on your device, but 16 GB would be preferable.

Questions? Contact us for more information on requirements for your specific operating system.

5.    Is the program 100% online?

Yes, the program is entirely asynchronous and online—so you can study when and wherever you’d like so long as you can get online and stay on track for graduation.

But this doesn’t mean the learning experience is isolated or lonely! You’ll have regular contact with your mentor, tutor, student advisor, and career specialist—as well as full access to our active student community on Slack.

6.    How long does the program take to complete?

The program is flexibly-paced within a 10-month duration. There are three deadlines along the way that we’ve put in place to help keep you on track for graduation.

Expect to devote a minimum of 15-20 hours per week to graduate within that maximum time frame. This is considered part-time study, and matches the default pacing of the program. If you’d like to graduate in as little as five months, you can devote 30-40 hours per week to reach that goal.

7.    What’s included in the program tuition?

The Data Analytics Program offers you a complete career change package—including expert-authored curriculum, hands-on projects, personalized mentorship, and career coaching. Find out more here:

  • How it works: From curriculum details to your career change team, and beyond—here are the details.
  • Meet our mentors: Get to know who the CareerFoundry mentors are and how the dual-mentorship model works.
  • Career services: Everything you need to know about our personalized career coaching, Job Preparation course, Career Support Center, alumni community, and more.
  • Graduate outcomes: Here’s some of the work our graduates did in the program—and where they’re at today.
In addition to all of this, you can request read access to our course library—so you can study other corners of the tech world independently, with all the course materials included in your program tuition! You can ask your student advisor about this once you start the program.
8.    Are there payment plans available?

Yes, we offer two payment options. You can save 5% of your total tuition by paying it up front. Alternatively, you can pay a set amount up front to reserve your place in the program, and the remainder in 10 monthly payments (regardless of when you graduate from the program).

Still not feasible for you? Book a call with a program advisor to see if you’re eligible for a customized payment plan.

9.    Does CareerFoundry offer full or partial scholarships?

While we do offer an ongoing tuition reduction to active U.S. military personnel and veterans, as well as periodic, partial scholarships/tuition reductions, we do not offer any full scholarships or funds at this time.

If you’d like to learn more about any of these offers, please reach out to a program advisor.

10.    What’s the refund policy if I change my mind?

If you’re not happy with the program in the first 14 days from the start date, you can simply cancel for a full refund.

If you are 60% or less of the way through the program duration (not including any extensions) and need to cancel for any reason, you may be eligible for a prorated refund. For more information, see our full terms and conditions.

11.    Do I get a certificate at the end?

You will receive a signed CareerFoundry certificate when you complete the program. This will make it easy for you to share your new qualification on LinkedIn and with potential employers or clients.

12.    Is the program accredited and what does ZFU-approved mean?

While the program is not university accredited, it does undergo a rigorous quality assurance and certification process with the ZFU (Staatliche Zentralstelle für Fernunterricht)—the state body for distance learning in Germany.

This process ensures that the program meets a high stand for an excellent and effective learning experience.

On successful completion of this certification process, the program is assigned a unique approval number (7374920) which can be checked against a public register.

13.    Are there eligibility requirements for the job guarantee?

There are conditions that graduates need to meet in order to be eligible for the job guarantee. We’re transparent about these requirements because we want them to be easy for you to follow and because we know they genuinely help graduates succeed in their job search.

You’re eligible for the job guarantee when:

  • You’ve successfully completed 100% of your CareerFoundry program as well as our free Job Preparation course.
  • You’re applying to at least five relevant jobs a week.
  • You live in a metropolitan area with a population above 200K people in any of the following countries: USA, Canada, European Union or EFTA countries, UK, Australia, or New Zealand (or you’re willing to relocate).
  • And when you meet other qualifying criteria. Please read the full terms and conditions.
If you have any questions about the job guarantee or the eligibility criteria, simply book a call with a program advisor—they’re happy to help!
14.    What kind of job can I get after the program?

Based on the program’s comprehensive curriculum, you’ll be ready to apply for and step into a junior data analyst role or mid-level data analyst position.

Keep in mind that many job ads for data analysts ask for 2+ years of experience, but it is often part of their "wishlist" rather than a requirement.

If you have transferable skills from your previous career, it’s possible to land a more senior role. Your dedicated career specialist (during the Job Prep course) will help you understand your transferable skills and craft the right narrative to present in your job application materials.

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