From Fashion Operations to Business Intelligence: How Ray Switched to a Career in Tech
Ray Rusli Jr, Graduate
Business Intelligence Consultant at bdg
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
“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
“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
Overview
Get in touch with usThe 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
Skills-focused
Every aspect of the curriculum is designed for you to cultivate the industry’s most in-demand skills. From hard skills like statistical analysis, testing, and automating tasks with AI, to the soft skills of stakeholder management and team collaboration—you’ll graduate well-rounded and job-ready.
Rigorously practical
Learn with a project-based curriculum that takes you beyond theory and into immersive tasks that will directly reflect the kind of work you’ll do on the job. Put everything you learn to immediate, practical use through hands-on projects you’ll build your extensive portfolio around.
Expert-written
Our instructional designers and editors work with skilled subject matter experts to write and continually update learning materials to teach the most cutting-edge content. Through mentorship and demonstrable project work, you’ll have the knowledge and skills needed to get hired.
Curriculum overview
Part-time
Flexible
Full-time
Intro to Data Analytics
approx.
1 month
1 month
Data Analytics Immersion
approx.
7 months
7 months
Specialization
approx.
2 months
2 months
Intro to Data Analytics
approx.
0.5 months - 1 month
0.5 months - 1 month
Data Analytics Immersion
approx.
3.5 - 7 months
3.5 - 7 months
Specialization
approx.
1 - 2 months
1 - 2 months
Intro to Data Analytics
approx.
0.5 months
0.5 months
Data Analytics Immersion
approx.
3.5 months
3.5 months
Specialization
approx.
1 month
1 month
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.
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.
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.
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.
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
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.
Learning with AI
Our Data Analytics Program has recently been updated with AI content to ensure you stay up-to-date with the latest trends and technologies. That includes being ready to use AI tools and techniques on the job when you graduate.
With useful exercises, best practices, and brand-new learning material about AI, you’ll learn how to use AI in a way that is reflective of how real-world tasks are approached in the industry, while still building the core skills of your new profession.
Your mentor and tutor will teach you to use generative AI and large language models (like ChatGPT) to become more effective in your work, and you’ll learn how to use AI tools and techniques critically and ethically so that it supports you professionally, rather than replaces you.
Create head-turning work with industry-standard 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!
Attend your first live data analytics event
Join free events and skills workshops to explore data analytics with industry professionals! Bring questions to the Q&A, gain insider knowledge, and take the first step in your future career.
Join free, online events with leading data analysts. Bring your questions for our experts!
Success Stories
Our students go on to launch challenging new careers in the tech industry
From Teacher to Data Analyst: How I Leveled Up My Math Skills for a Career in Data
Azadeh Rezaei, Graduate
Data Analyst at Affirm
Read story
From Math Teacher to Data Analyst: How I Transformed My Career
Nick Logan, Graduate
Data Analyst at Lockton Companies
Read story
From Sales Manager to Global Development Analyst: How My Career in the Hotel Industry Came Full Circle
Cheryl Poulain, Graduate
Global Development Analyst at Marriott
Read story
From Tech Recruiter to Data Analyst: How I Found My Vocation
Chad Stacey, Graduate
Data Analyst at The Telegraph
Read story
Data for Social Good: Why I Chose To Learn Data Analytics (and How the Edie Windsor Scholarship Made It Possible)
Brittany Anderson-Freese, Graduate
Program Manager at Signature Health
Read story
From Barista to Data Analyst: How I Transformed My Career In Less Than 6 Months
Elizabeth Decker, Graduate
Data Analyst at JLMI
Read story
How I Retrained As A UX Designer And Landed A Dream Job—And All For Free
Alexander Frimpong, Graduate
UX Designer at mediaworx berlin AG
Read story
From Graphic Design To UI: How I Learned The Value Of Designing For The User
Francis Pujols, Graduate
UI Designer at flying saucer
Read story
How I Went From Uber Driver To Web Developer In A Matter Of Months
Gabriel Aleman, Graduate
Web Developer at TopSpot Internet Marketing
Read story
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:
- Take our free data analytics short course.
- Get a free consultation with one of our program advisors who will give you personal feedback on which direction to go based on your interests and goals.
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
€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.
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.
€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.
Talk to your program advisor
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
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.
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.
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.
How would you like us to contact you?
Book a time to speak with a program advisor
Send us a message
What questions do you have about the program? We're happy to help.
Thank you!
Our program advisor will be in touch with you shortly.
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