Choosing to invest in a data science boot camp can be a daunting task. Whether it’s weighing pros and cons or cross-checking reviews, it can be brain-wracking to make the perfect choice.
In order to assist you in making a well-informed decision and simplify your research process, we have created this comparison blog to let the features and statistics of the bootcamps speak for themselves.
So, without any delay, let’s delve deeper into the comparison: Data Science Dojo vs Thinkful Bootcamp.
Data Science Dojo vs Thinkful
Data Science Dojo
As an ideal choice for beginners with no prerequisites, Data Science Dojo’s Bootcamp is a great choice. It is a 16-week online bootcamp that covers the fundamentals of data science. It adopts a business-first approach in its curriculum, combining theoretical knowledge with practical hands-on projects. With a team of instructors who possess extensive industry experience, students have the opportunity to receive personalized support during dedicated office hours.
The boot camp covers various topics, including data exploration and visualization, decision tree learning, predictive modeling for real-world scenarios, and linear models for regression. Moreover, students can use multiple payment plans and may earn a verified data science certificate from the University of New Mexico.
Thinkful
Thinkful’s data science bootcamp provides the option for part-time enrollment, requiring around six months to finish. Students advance through modules at their own pace, dedicating approximately 15 to 20 hours per week to coursework.
The curriculum features important courses such as analytics and experimentation, as well as a supervised learning experience in machine learning where students construct their initial models. It has a partnership with Southern New Hampshire University (SNHU), allowing graduates to earn credit towards a Bachelor’s or Master of Science degree at SNHU.
Comparison of bootcamp features
Here is a table that compares the features of Data Science Dojo and Thinkful:
Data Science Dojo VS Thinkful
Which bootcamp is best for you?
Embarking on a bootcamp journey is a major step for your career. Before committing to any program, it’s crucial to evaluate your future goals and assess how each prospective bootcamp aligns with them.
To choose the right data science bootcamp, ask yourself a series of important questions. How soon do you want to enter the workforce? What level of earning potential are you aiming for? Which skills are essential for your desired career path?
By answering these questions, you’ll gain valuable clarity during your search and be better equipped to make an informed decision. Ultimately, the best bootcamp for you will depend on your individual needs and goals.
The job market for data scientists is booming. In fact, the demand for data experts is expected to grow by 36% between 2021 and 2031, significantly higher than the average for all occupations. This is great news for anyone who is interested in a career in data science.
According to the U.S. Bureau of Labor Statistics, the job outlook for data science is estimated to be 36% between 2021–31, significantly higher than the average for all occupations, which is 5%. This makes it an opportune time to pursue a career in data science.
Data Science Bootcamp
What are Data Science Bootcamps?
Data science boot camps are intensive, short-term programs that teach students the skills they need to become data scientists. These programs typically cover topics such as data wrangling, statistical inference, machine learning, and Python programming.
Short-term: Bootcamps typically last for 3-6 months, which is much shorter than traditional college degrees.
Flexible: Bootcamps can be completed online or in person, and they often offer part-time and full-time options.
Practical experience: Bootcamps typically include a capstone project, which gives students the opportunity to apply the skills they have learned.
Industry-focused: Bootcamps are taught by industry experts, and they often have partnerships with companies that are hiring data scientists.
Top 10 Data Science Bootcamps
Without further ado, here is our selection of the most reputable data science boot camps.
1. Data Science Dojo Data Science Bootcamp
Delivery Format: Online and In-person
Tuition: $2,659 to $4,500
Duration: 16 weeks
Data Science Dojo Bootcamp
Data Science Dojo Bootcamp is an excellent choice for aspiring data scientists. With 1:1 mentorship and live instructor-led sessions, it offers a supportive learning environment. The program is beginner-friendly, requiring no prior experience. Easy installments with 0% interest options make it the top affordable choice. Rated as an impressive 4.96, Data Science Dojo Bootcamp stands out among its peers. Students learn key data science topics, work on real-world projects, and connect with potential employers. Moreover, it prioritizes a business-first approach that combines theoretical knowledge with practical, hands-on projects. With a team of instructors who possess extensive industry experience, students have the opportunity to receive personalized support during dedicated office hours.
2. Springboard Data Science Bootcamp
Delivery Format: Online
Tuition: $14,950
Duration: 12 months long
Springboard Data Science Bootcamp
Springboard’s Data Science Bootcamp is a great option for students who want to learn data science skills and land a job in the field. The program is offered online, so students can learn at their own pace and from anywhere in the world. The tuition is high, but Springboard offers a job guarantee, which means that if you don’t land a job in data science within six months of completing the program, you’ll get your money back.
3. Flatiron School Data Science Bootcamp
Delivery Format: Online or On-campus (currently online only)
Tuition: $15,950 (full-time) or $19,950 (flexible)
Duration: 15 weeks long
Flatiron School Data Science Bootcamp
Next on the list, we have Flatiron School’s Data Science Bootcamp. The program is 15 weeks long for the full-time program and can take anywhere from 20 to 60 weeks to complete for the flexible program.
Students have access to a variety of resources, including online forums, a community, and one-on-one mentorship.
4. Coding Dojo Data Science Bootcamp Online Part-Time
Delivery Format: Online
Tuition: $11,745 to $13,745
Duration: 16 to 20 weeks
Coding Dojo Data Science Bootcamp Online Part-Time
Coding Dojo’s online bootcamp is open to students with any background and does not require a four-year degree or Python programming experience. Students can choose to focus on either data science and machine learning in Python or data science and visualization. It offers flexible learning options, real-world projects, and a strong alumni network. However, it does not guarantee a job, requires some prior knowledge, and is time-consuming.
5. CodingNomads Data Science and Machine Learning Course
CodingNomads offers a data science and machine learning course that is affordable, flexible, and comprehensive. The course is available in three different formats: membership, premium membership, and mentorship. The membership format is self-paced and allows students to work through the modules at their own pace. The premium membership format includes access to live Q&A sessions. The mentorship format includes one-on-one instruction from an experienced data scientist. CodingNomads also offers scholarships to local residents and military students.
6. Udacity School of Data Science
Delivery Format: Online
Tuition: $399/month
Duration: Depends on the program
Udacity School of Data Science
Udacity offers multiple data science bootcamps, including data science for business leaders, data project managers and more. It offers frequent start dates throughout the year for its data science programs. These programs are self-paced and involve real-world projects and technical mentor support. Students can also receive LinkedIn profile and GitHub portfolio reviews from Udacity’s career services. However, it is important to note that there is no job guarantee, so students should be prepared to put in the work to find a job after completing the program.
7. LearningFuze Data Science Bootcamp
Delivery Format: Online and in person
Tuition: $5,995 per module
Duration: Multiple formats
LearningFuze Data Science Bootcamp
LearningFuze offers a data science boot camp through a strategic partnership with Concordia University Irvine. Offering students the choice of live online or in-person instruction, the program gives students ample opportunities to interact one-on-one with their instructors. LearningFuze also offers partial tuition refunds to students who are unable to find a job within six months of graduation.
The program’s curriculum includes modules in machine learning and deep learning and artificial intelligence. However, it is essential to note that there are no scholarships available, and the program does not accept the GI Bill.
8. Thinkful Data Science Bootcamp
Delivery Format: Online
Tuition: $16,950
Duration: 6 months
Thinkful Data Science Bootcamp
Thinkful offers a data science boot camp which is best known for its mentorship program. It caters to both part-time and full-time students. Part-time offers flexibility with 20-30 hours per week, taking 6 months to finish. Full-time is accelerated at 50 hours per week, completing in 5 months. Payment plans, tuition refunds, and scholarships are available for all students. The program has no prerequisites, so both fresh graduates and experienced professionals can take this program.
9. Brain Station Data Science Course Online
Delivery Format: Online
Tuition: $9,500 (part time); $16,000 (full time)
Duration: 10 weeks
Brain Station Data Science Course Online
BrainStation offers an immersive and hands-on data science boot camp that is both comprehensive and affordable. Industry experts teach the program and includes real-world projects and assignments. BrainStation has a strong job placement rate, with over 90% of graduates finding jobs within six months of completing the program. However, the program is expensive and can be demanding. Students should carefully consider their financial situation and time commitment before enrolling in the program.
10. BloomTech Data Science Bootcamp
Delivery Format: Online
Tuition: $19,950
Duration: 6 months
BloomTech Data Science Bootcamp
BloomTech offers a data science bootcamp covers a wide range of topics, including statistics, predictive modeling, data engineering, machine learning, and Python programming. BloomTech also offers a 4-week fellowship at a real company, which gives students the opportunity to gain work experience. BloomTech has a strong job placement rate, with over 90% of graduates finding jobs within six months of completing the program. The program is expensive and requires a significant time commitment, but it is also very rewarding.
What to expect in a data science bootcamp?
A data science bootcamp is a short-term, intensive program that teaches you the fundamentals of data science. While the curriculum may be comprehensive, it cannot cover the entire field of data science.
Therefore, it is important to have realistic expectations about what you can learn in a bootcamp. Here are some of the things you can expect to learn in a data science bootcamp:
Data science concepts: This includes topics such as statistics, machine learning, and data visualization.
Hands-on projects: You will have the opportunity to work on real-world data science projects. This will give you the chance to apply what you have learned in the classroom.
A portfolio: You will build a portfolio of your work, which you can use to demonstrate your skills to potential employers.
Mentorship: You will have access to mentors who can help you with your studies and career development.
Career services: Bootcamps typically offer career services, such as resume writing assistance and interview preparation.
Wrapping up
All and all, data science bootcamps can be a great way to learn the fundamentals of data science and gain the skills you need to launch a career in this field. If you are considering a boot camp, be sure to do your research and choose a program that is right for you.
“Our online data science boot camp offers the same comprehensive curriculum as our in-person program. Learn from industry experts and earn a certificate from the comfort of your own home. Enroll now!”
Data Science is one of the most in-demand skills in today’s job market, and for good reason. With the rise of big data and the increasing importance of data-driven decision-making, companies are looking for professionals who can help them make sense of all the information they collect.
But what if you don’t live near one of our Data Science Dojo training centers, or you don’t have the time to attend classes in-person? No worries! Our online data science boot camp offers the same comprehensive curriculum as our in-person program, so you can learn from industry experts and earn a certificate from the comfort of your own home.
A glimpse into an online Data Science Bootcamp of Data Science Dojo
Our online boot camp is designed to give you a solid foundation in data science, including programming languages like Python and R, statistical analysis, machine learning, and more. You’ll learn from real-world examples and work on projects that will help you apply what you’ve learned to your own job.
Data Science Bootcamp Review – Data Science Dojo
1. Learn at your own pace
One of the great things about our online boot camp is that you can learn at your own pace. We understand that everyone has different learning styles and schedules, so we’ve designed our program to be flexible and accommodating. You can attend live online classes, watch recorded lectures, and work through the material on your own schedule.
2. Mentorship and support for participants
Another great thing about our online bootcamp is the support you’ll receive from our instructors and community of fellow students. Our instructors are industry experts who have years of experience in data science, and they’re always available to answer your questions and help you with your projects. You’ll also have access to a community of other students who are also learning data science, so you can share tips and resources, and help each other out.
3. Interactive course material
Our Data Science Dojo bootcamp is designed to provide a comprehensive and engaging learning experience for students of all levels. One of the unique aspects of our program is the diverse set of exercises that we offer.
These exercises are designed to be challenging, yet accessible to everyone, regardless of your prior experience with data science. This means that whether you’re a complete beginner or an experienced professional, you’ll be able to learn and grow as a data scientist.
4. Participate in data science competitions
To keep you motivated during the bootcamp, we also include a Kaggle competition. Kaggle is a platform for data science competitions, and participating in one is a wonderful way to apply what you’ve learned, compete against other students, and see how you stack up against the competition.
5. Instructor-led training
Another unique aspect of our bootcamp is the instructor-led training. Our instructors are industry experts with years of experience in data science, and they’ll be leading the classes and providing guidance and support throughout the program. They’ll be available to answer questions, provide feedback, and help you with your projects.
6. Ask your queries during dedicated office hours
In addition to the instructor-led training, we also provide dedicated office hours. These are scheduled times when you can drop in and ask our instructors or TA’s any questions you may have or get help with specific exercises. This is a great opportunity to get personalized attention and support, and to make sure you’re on track with the program.
7. Build a strong alumni network
Our bootcamp also provides a strong alumni network. Once you complete the program, you’ll be part of our alumni network, which is a community of other graduates who are also working in data science. This is a great way to stay connected and to continue learning and growing as a data scientist.
8. Master your skills with live code environments
One of the most important aspects of our bootcamp is the live code environments within a browser. This allows participants to practice coding anytime and anywhere, which is crucial for mastering this skill. This means you can learn and practice on the go, or at any time that is convenient for you.
Once you finish the bootcamp, you’ll still have access to post-bootcamp tutorials and publicly available datasets. This will allow you to continue learning, practicing and building your portfolio. Alongside that, you’ll have access to blogs and learning material that will help you stay up to date with the latest industry trends and best practices.
Start your data science learning journey today!
Overall, our Data Science Dojo bootcamp is designed to provide a comprehensive, flexible and engaging learning experience. With a diverse set of exercises, a Kaggle competition, instructor-led training, dedicated office hours, strong alumni network, live code environments within a browser, post-bootcamp tutorials, publicly available datasets and blogs and learning material, we are confident that our program will help you master data science and take the first step towards a successful career in this field.
At the end of the program, you’ll receive a certificate of completion, which will demonstrate to potential employers that you have the skills and knowledge they’re looking for in a data scientist.
So, if you’re looking to master data science, but you don’t have the time or opportunity to attend classes in-person, our online data science bootcamp is the perfect solution. Learn from industry experts and earn a certificate from the comfort of your own home. Enroll now and take the first step towards a successful career in data science
Bellevue, Washington (January 11, 2023) – The following statement was released today by Data Science Dojo, through its Marketing Manager Nathan Piccini, in response to questions about future in-person bootcamps:
Get a behind-the-scenes look at Data Science Dojo’s intensive data science Bootcamp. Learn about the course curriculum, instructor quality, and overall experience in our comprehensive review.
“The more I learn, the more I realize what I don’t know”
In our current era, the terms “AI”, “ML”, “analytics”–etc., are indeed THE “buzzwords” du jour. And yes, these interdisciplinary subjects/topics are **very** important, given our ever-increasing computing capabilities, big-data systems, etc.
The problem, however, is that **very few** folks know how to teach these concepts! But to be fair, teaching in general–even for the easiest subjects–is hard. In any case, **this**–the ability to effectively teach the concepts of data-science–is the genius of DS-Dojo. Raja and his team make these concepts considerably easy to grasp and practice, giving students both a “big picture-,” as well as a minutiae-level understanding of many of the necessary details.
Still, a leery prospective student might wonder if the program is worth their time, effort, and financial resources. In the sections below, I attempt to address this concern, elaborating on some of the unique value propositions of DS-Dojo’s pedagogical methods.
Data Science Bootcamp Review – Data Science Dojo
The More Things Change…
Data Science enthusiasts today might not realize it, but many of the techniques–in their basic or other forms–have been around for decades. Thus, before diving into the details of data-science processes, students are reminded that long before the terms “big data,” AI/ML and others became popularized, various industries had all utilized techniques similar to many of today’s data-science models. These include (among others): insurance, search-engines, online shopping portals, and social networks.
This exposure helps Data-Science Dojo students consider the numerous creative ways of gathering and using big-data from various sources–i.e. directly from human activities or information, or from digital footprints or byproducts of our use of online technologies.
The big picture of the Data Science Bootcamp
As for the main curriculum contents, first, DS-Dojo students learn the basics of data exploration, processing/cleaning, and engineering. Students are also taught how to tell stories with data. After all, without predictive or prescriptive–and other–insights, big data is useless.
The bootcamp also stresses the importance of domain knowledge, and relatedly, an awareness of what precise data-points should be sought and analyzed. DS-Dojo also trains students to critically assess: why, and how should we classify data? Students also learn the typical data-collection, processing, and analysis pipeline, i.e.:
Influx
Collection
Preprocessing
Transformation
Data-mining
And finally, interpretation and evaluation.
However, any aspiring (good) data scientist should disabuse themselves of the notion that the process doesn’t present challenges. Au contraire, there are numerous challenges; e.g. (among others):
Scalability
Dimensionality
Complex and heterogeneous data
Data quality
Data ownership and distribution,
Privacy,
Reaction time.
Deep dives
Following the above coverage of the craft’s introductory processes and challenges, DS-Dojo students are then led earnestly into the deeper ends of data-science characteristics and features. For instance, vis-a-vis predictive analytics, how should a data-scientist decide when to use unsupervised learning, versus supervised learning? Among other considerations, practitioners can decide using the criteria listed below.
Unsupervised Learning…Vs. … >>
<< …Vs. …Supervised Learning
>> Target values unknown
>> Targets known
>> Training data unlabeled
>> Data labeled
>> Goal: discover information hidden in the data
>> Goal: Find a way to map attributes to target value(s)
Overall, the main domains covered by DS-Dojo’s data-science bootcamp curriculum are:
An introduction/overview of the field, including the above-described “big picture,” as well as visualization, and an emphasis on story-telling–or, stated differently, the retrieval of actual/real insights from data;
Overview of classification processes and tools
Applications of classification
Unsupervised learning;
Regression;
Special topics–e.g., text-analysis
And “last but [certainly] not least,” big-data engineering and distribution systems.
Method-/Tool-Abstraction
In addition to the above-described advantageous traits, data-science enthusiasts, aspirants, and practitioners who join this program will be pleasantly surprised with the bootcamp’s de-emphasis on specific tools/approaches. In other words, instead of using doctrinaire approaches that favor only Python, or R, Azure, etc., DS-Dojo emphasizes the need for pragmatism; practitioners should embrace the variety of tools at our disposal.
“Whoo-Hoo! Yes, I’m a Data Scientist!”
By the end of the bootcamp, students might be tempted to adopt the above stance–i.e., as stated above (as this section’s title/subheading). But as a proud alumnus of the program, I would cautiously respond: “Maybe!” And if you have indeed mastered the concepts and tools, congratulations!
But strive to remember that the most passionate data-science practitioners possess a rather paradoxical trait: humility, and an openness to lifelong learning. As Raja Iqbal, CEO of DS-Dojo pointed out in one of the earlier lectures: The more I learn, the more I realize what I don’t know. Happy data-crunching!
Is there a relation between data science and law? Here’s what a lawyer learned from a 50-hour data science Bootcamp at Data Science Dojo.
With an increased focus on the growing role of data science and data analytics in the future of law, I decided that it was high time to learn what all the fuss is about. How do data science and law work together? Initially, I considered taking a course on data analytics geared for lawyers, but shockingly, I couldn’t find much, with the exception of a couple of classes that focused on e-discovery where predictive coding is a hot topic. One new player in the legal data space, LexPredict also offers a bunch of trainings for lawyers, but the company seemed geared towards big law and in any event, didn’t list dates or prices for its classes
Unable to find data engineering classes for lawyers, I decided to get at the subject from another angle: start with the data science tech and work my way back to the law. That approach gave me a plethora of options, from low-cost classes at Udemy and Coursera to 12-week bootcamps costing $10k or more. However, because I didn’t have the luxury of giving up my day job, I knew that I’d need a compact course since any program that dragged out over a period of weeks or months increased the chances that I’d drop out once my caseload and client emergencies presented a conflict. Likewise, given that I’d have to take time out of my practice for a class that would cause some financial loss, I didn’t want to shell out several thousands of dollars for a class.
Based on my criteria, Data Science Dojo’s data science bootcamp fit the bill: it’s a reasonably priced 5-day, 50-hour onsite program that didn’t have any pre-requisites (though there was about 10 hours of pre-class prep). And the class covered broad ground: in a span of the week I learned both the coding tools like basic R, MS Azure, Hadoop, and Hive along with concepts like data mining and visualization, predictive modeling, Ensemble methods like bagging and boosting, random forests, the importance of cross validation, the difference between training and test data, AB Testing basics, building a recommendation system and handling real time and streaming data (we hacked a quick IoT solution using Azure tools, though truth be told, I was pretty much lost by then). Below are some of my takeaways on big data, especially as it relates to the legal profession and what it’s like for a lawyer to learn a new skill at an advanced age.
Lesson 1
The mechanics of building a predictive model aren’t particularly difficult; understanding what features to include and how to approach the problem is – and that’s where domain knowledge is important.
One of the underlying themes of the class is that data science (itself a buzzword) is merely a collection of skills, intuition and domain knowledge matter as much as coding a predictive model. Yet oddly, when data science is discussed in the legal profession, we downplay the importance of legal expertise and its value in creating effective models.
Predictive models are iterative and constant questioning is a good thing.
Although most lawyers will argue a legal principal ad nauseam, when it comes to data, we’re surprisingly passive. For the past two years, Clio has released a Trends Report that produced interesting, albeit counter-intuitive results. Yet the results are reported as is, with no questions as to the methodologies used, what the data means or how it was gathered. That’s not true data science: its group think.
Big legal data Isn’t all that big
Our instructor shared with us the Five V’s — Volume, Velocity, Variety, Veracity, and Value – which are used to evaluate whether data rises to the level of big data. For volume, we’re talking about massive amounts of data – not terabytes, but exabytes and beyond – too large to be stored and processed on traditional machines. For example, on Facebook, 10 billion messages are exchanged each day. It’s hard to imagine many sources of legal data that approach that volume. Our instructor’s point was that we shouldn’t make a data problem into a big data problem unless necessary. So, I wonder whether lawyers are using the term “big data” for small data or treating ordinary data problems as big data problems.
Kaggle competitions are way cool
I didn’t know much about Kaggle before my class. Although our involvement in Kaggle was limited to an in class competition over who could build the most accurate model to predict survival on the Titanic, more broadly, Kaggle serves as a platform where companies can crowd-source creation of data models. Many of the contests attract large numbers of participants – because the sponsors pony up substantial cash prizes as incentive. Lawyers are often criticized for not crowd-sourcing orb-sharing information like other professions — but I’ve not seen a single platform that offers any financial reward to lawyers for creating content that might be used as the equivalent of case notes. If any of the companies adding blog content to supplement caselaw – as Fastcase in collaboration with Lexblog are doing now – offered a thousand dollar award every week for best content, I think we’d see an explosion of high-quality crowd-sourced materials
All practicing lawyers, not just millennials, need to understand new technology
Most of the conversation about the importance of learning about big data or AI or other new tools comes in the context of advice as to what millennials need to learn. But I think it’s even more important for us mid-career and older lawyers to to keep pace with the future if we want to have control over how the last decade or two of our careers play out.
After 50 hours of bootcamp, I’ve had to catch up on client work – and I’m not sure how soon it will be before I can apply all the fancy new tricks and knowledge that I’ve learned. For now, I’m satisfied that at least I’ve taken the first step. When will you do the same?
