Data science is the career of the future and undoubtedly an exciting path for many people wanting to pursue a tech career. With formal degrees being less popular and attractive to employers, many aspiring data scientists turn to data science bootcamps and courses to refine their education and knowledge level.
While paid bootcamps usually offer more structured support, free bootcamps have become increasingly sophisticated, offering high-quality education and valuable hands-on experience without the financial burden.
But how do you pick a free bootcamp that’s worth your while? This article will explore seven of the best free data science bootcamps, looking at pre-defined criteria that will influence your decision.
Table of Contents
Free Data Science Bootcamps
Springboard
Although focusing on analytics specifically, Springboard’s Data Analytics course also explores data science topics and gives students a holistic understanding of the field.
The course includes data visualization, machine learning, probability, and statistics modules and incorporates practical applications of tools and programming languages like Python, Excel, or Tableau.
Through this bootcamp, students get a solid data analytics foundation and acquire insights into the broader data science field through 25 learning units taught by industry experts. They get to focus on real-world scenarios, engaging with materials through documentation, videos, and a case study to add to their portfolio.
Prerequisites:
The only prerequisite for enrolling in Springboard’s Data Analytics course is an interest in data and problem-solving. Ideally, you should have a basic understanding of mathematics and statistics.
While having prior experience in programming or data analytics is helpful, this is optional. The course is perfect for a diverse audience, including students and professionals looking to pivot into tech.
RATING
4.6/5 @ Course Report
FEATURES
- A practical case study in finance;
- Teaches a wide range of tools and programming languages;
- Flexible learning units;
- Free access;
- Opportunity to pursue a Career Track course for guaranteed job opportunities.
DURATION
The course includes 24+ hours of content, and you can pursue it at your own pace.
AI Planet
AI Planet’s 5-week Data Science bootcamp is designed for both beginners and experts. It’s an online, self-paced course that covers a wide range of topics – from the basics of Python to advanced machine learning model optimization.
In response to a lot of initial success, AI Planet has made the entire bootcamp content, including tutorials, exercises, live sessions, and additional resources, freely available to the public.
The course content is taught by industry experts and academics who bring a wealth of knowledge. Students are guided through a structured program, starting with an introductory week (Week 0) for newcomers, followed by focused weekly modules on data analysis, exploratory data analysis (EDA), machine learning, model optimization, and practical application on real-world datasets.
Prerequisites:
While there are no strict prerequisites, you’ll need a basic understanding of programming concepts and mathematics. For those new in the field of data science, the bootcamps includes an introductory week.
RATING
NA
FEATURES
- Beginner-friendly
- Taught by Google Developer experts
- Free access to all materials (previously paid)
- Live session recordings
- Community support of learners and instructors
- Feedback-driven
DURATION
The bootcamp lasts five weeks, with an additional introductory Week 0 for beginners.
IBM on Coursera
As part of a Coursera subscription, the IBM Data Science Professional Certificate is a program led by seasoned instructors like Dr. Pooja and Romeo Kienzler. It is structured to get students job-ready in as little as five months without experience.
It dives into relevant topics like Python programming, SQL, machine learning, and data visualization. As an enrolled student, you’ll get to work on practical projects in the IBM Cloud, and you’ll get a Professional Certificate with access to IBM’s Talent Network.
Prerequisites:
The program is perfect for those with no previous experience in data science.
RATING
4.6/5 on Coursera
FEATURES
- Certificate of completion
- No previous experience required
- Financial aid available
- Earn college credits (Program is ACE® and FIBAA recommended, offering up to 12 college credits and 6 ECTS credits upon completion)
DURATION
The IBM Data Science Professional Certificate can be completed in approximately five months if you commit to about 10 hours per week.
Fellowship.AI
Fellowship.AI’s program promises some of the fastest paths to a data science career in tech and machine learning.
The program’s core philosophy is rooted in the understanding that the most valuable asset for employment in the machine learning field is practical experience rather than formal degrees. Students are immersed in an interactive environment that simulates professional ML engineering roles, engaging in the development of scalable machine learning models.
As a student, you are expected to participate and contribute to the learning community through pair programming, daily scrum updates, and attending reading groups or demo sessions.
Prerequisites:
Before enrolling, ensure you possess a foundational understanding of machine learning concepts and be proficient in relevant programming languages (primarily Python).
RATING
NA
FEATURES
- Mentorship by experienced ML professionals
- Exposure to the latest research in deep learning
- Collaborative learning environment
- Potential partnerships with leading companies
DURATION
The bootcamp lasts five weeks, with an additional introductory Week 0 for beginners.
Correlation One
Correlation One’s Data Science for All (DS4A) initiative is a groundbreaking effort that aims to bridge the opportunity gap for underrepresented communities in the data-driven job market.
Their programs are 100% free to learners, thanks to the support of their Employer Partners. They’re designed for individuals identifying as Women, Black, Latina, and/or LGBTQ+, providing them with the relevant, hands-on training needed to excel in the field.
Prerequisites:
The DS4A programs are open to all individuals passionate about starting or advancing their careers in data science. Specific requirements vary by program, but all students must commit to completing the program and actively engaging in the learning process.
RATING
4.9/5 on Course Report
FEATURES
- Real-world, business-focused curriculum
- Synchronous learning
- Career services support
- Training provided by employers
DURATION
DS4A offers multiple programs with varying lengths to accommodate different learning needs and career goals:
- Data Science for All / Empowerment: A 17-week foundational training program
- Data Science for All / Women: A 7-week fellowship program for female data-driven leaders
- Data Engineering: A 17-week training program for students with intermediate programming skills
freeCodeCamp.org (on YouTube)
The “Learn Data Science” tutorial course on YouTube is offered by freeCodeCamp.org and created by Barton Poulson from Datalab. The 5-hour introduction to the field of data science is for complete beginners.
Throughout this course, participants will be introduced to the fundamental principles and practices of data science and learn how to use the basic tools necessary to succeed. It spans multiple parts and briefly introduces data science, its applications, and ways to apply their knowledge to solve real-world problems.
Prerequisites:
This course is created for absolute beginners, requiring no prior knowledge of data science, programming, mathematics, or statistics.
RATING
NA
FEATURES
- Free access on YouTube
- Teaches a variety of tools and languages
- Interactive learning
- Community support access to freeCodeCamp.org and datalab.cc
DURATION
The course has five parts and lasts for 6 hours.
NYC Data Science Academy
NYC Data Science Academy’s Introduction to Data Science is a free prep course designed to kickstart careers in data science.
Over 8 hours and three units, students are introduced to essential data structures in Python and the principles of object-oriented programming, setting the stage for learning data analytics and visualization tools such as NumPy, SciPy, pandas, matplotlib, and seaborn.
Those who complete the Introduction to Data Science course receive accelerated admissions consideration for the NYC Data Science Academy Bootcamp.
Prerequisites:
This course is intended for beginners without prior data science or programming knowledge.
RATING
4.9/5 on Course Report
FEATURES
- Accelerated admissions to the NYC Data Science Academy Bootcamp
- Engaging a community of 2000+ data science professionals
- Hands-on practice
- Flexible learning
DURATION
The Introduction to Data Science course lasts approximately 8 hours, divided into three units
Is A Free Bootcamp Even Worth It?
Free data science bootcamps are a fantastic way to dip your toes in and see if you enjoy the data game. They can introduce you to essential tools like Python and foundational concepts. However, keep in mind these tasters might not cover the full data science experience. If you get hooked and crave a deeper dive with practical application, a structured course with project-based learning can really propel you forward. We offer comprehensive data science programs that do just that, but for now, happy exploring with those free bootcamps!
How Do You Choose A Free Data Science Bootcamp?
Our Springboard panel of data science experts has looked at available bootcamps and highlighted six key factors you should pay close attention to before enrolling.
- Syllabus. When examining a bootcamp’s syllabus, look for a curriculum that covers the breadth and depth of data science fundamentals while also touching on more advanced topics. The syllabus should at least include topics like programming, statistics, machine learning, and data manipulation. The progression of topics should feel logical, from basic concepts to more complex ones. A well-put-together syllabus balances both theoretical understanding and practical application.
- Instructor’s expertise. The instructor’s expertise is central to any bootcamp’s success (and yours, too). Look for programs led by instructors with both theoretical and practical knowledge. They should ideally have a track record of achievement in data science, whether through published research, real-world projects, or contributions to the field. They should also be able to convey complex ideas in an accessible way – in other words, they should be great teachers.
- Skills and tools. A good data science bootcamp should teach you a broad set of technical and soft skills. Some of these skills include:
- Proficiency in programming languages such as Python and R
- AI skills like big data and machine learning
- Data visualization
- Statistics
- Probability
- Data wrangling and cleaning
- Prerequisites needed. Before committing to a bootcamp, review its prerequisites to ensure you’re not stepping into a program that’s too advanced or too basic for your current skill level. A mismatch can lead to frustration and prevent you from finishing the bootcamp. Most bootcamps specify prerequisites for programming knowledge, mathematical background, or familiarity with specific tools. If you’re unsure about meeting these requirements, contact the bootcamp organizers for clarification.
- Practical projects. Including practical projects in a bootcamp’s curriculum strongly indicates its quality. These projects allow you to apply what you’ve learned in real-world scenarios, reinforcing your knowledge and building your portfolio. Look for programs that offer a variety of projects across different domains, as this diversity can help you discover your areas of interest and expertise within data science.
- Student reviews. Finally, don’t underestimate the value of student reviews when choosing a bootcamp. Positive and negative feedback can give you insights into the program’s strengths and weaknesses. Look for recurring themes in reviews, as these can highlight consistent benefits or issues with that bootcamp.
Making The Most Out Of Your Free Data Science Bootcamp Or Course
Once you enroll, you need to make the best of your bootcamp so you absorb as much knowledge as possible. Here’s how to do that.
Get familiar with the fundamentals
Make sure you’ve got the fundamentals covered:
- Python/R programming;
- Statistics and probability;
- Machine Learning algorithms;
- Data wrangling and cleaning;
- Data visualization;
- SQL for data analysis;
- Basics of Big Data technologies;
Don’t rely only on your bootcamp to teach you these. Be curious and explore additional research and resources so you don’t limit your understanding of the topic.
Implement the learnings
The true test of your data science knowledge comes when you apply it to solve real problems.
While the bootcamp projects simulate real-world scenarios, you should also extend your practice to independent projects such as open-source data science mini-projects or tackling data challenges during hackathons.
Plan next steps
As you approach the finish line of your bootcamp, think about your next steps.
Consider looking into internships or volunteer opportunities to gain practical experience, depending on your confidence and skill level.
When ready, you can start applying for junior data science positions.
Join the data science community
Attend meetups, conferences, and workshops to connect with people pursuing the same career path. If you’re an introvert, start by hanging out online on forums and groups on LinkedIn, Reddit, and Indie Hackers.
If you contribute to enough conversations and start sharing your projects, your network will increase, and many opportunities will open up.
FAQs About Best Free Data Science Bootcamps
We answer your most frequently asked questions.
Is A Free Data Science Bootcamp Worth It?
Yes. Free data science bootcamps can be incredibly worthwhile for those seeking more understanding and practical experience in this field. While the depth and breadth of learning may vary compared to paid alternatives, free bootcamps offer a valuable opportunity for self-starters and motivated learners to acquire essential skills and knowledge.
What Can You Expect To Learn In A Free Data Science Bootcamp?
In a free data science bootcamp, you can expect to learn a range of foundational topics. These typically include an introduction to programming languages commonly used in data science, such as Python or R, and an overview of data manipulation, analysis, and visualization techniques. Bootcamps often cover basic statistical concepts and methods, machine learning algorithms, and how to apply these to real data sets to derive insights. Many programs introduce tools and libraries specific to data science, such as pandas, NumPy, SciPy, matplotlib, and seaborn for Python.
Can I Learn Data Science On My Own?
Yes, it is possible to learn data science without a degree on your own, thanks to a wealth of online resources, including free online courses, tutorials, and documentation. Self-learners can access educational content covering all major data science topics, from programming and statistical analysis to machine learning and data visualization. Online platforms like Springboard, freeCodeCamp, Coursera, and Kaggle provide structured pathways and projects for practical application. All you need to make it on your own is a disciplined approach, consistent practice, and engagement with a community for support and feedback.
Can A Data Science Bootcamp Get Me A Job?
A data science bootcamp per se does not get you a job, but it does enhance your job prospects in the field. Many coding bootcamps are designed with employability in mind, offering a curriculum aligned with the tech industry’s demands and allowing you to build a portfolio as you move through the course content. However, securing a job post-bootcamp also depends on your effort in networking, continuous learning, and the ability to put your learned skills to work.
Since you’re here…
Curious about a career in data science? Experiment with our free data science learning path, or join our Data Science Bootcamp, where you’ll get your tuition back if you don’t land a job after graduating. We’re confident because our courses work – check out our student success stories to get inspired.
