Fact checked by Picture this: You need a data science bootcamp to jump start your career. Where do you start?
Join me as I give an insider review of TripleTen’s data science bootcamp.
But why TripleTen? Good question!
For starters, their data science bootcamp is accessible to absolutely anyone, as there are no prerequisites.
And it’s not just about learning data science — it’s a comprehensive journey from fundamental concepts to advanced data manipulation and machine learning techniques, all while getting hands-on to gain real-world experience.
But one of the biggest standouts for me is the fact that they have an 87% hiring rate and a money back guarantee if you haven’t landed a job within 6 months of graduating.
Whether you want to formalize existing skills to make the transition to a bonafide data scientist, or you’re passionate about data and have no existing skills, TripleTen’s bootcamp can get you where you need to be in just 8 months.
So, let’s dive in to see just what this data science bootcamp is like behind the scenes!
Overview of TripleTen’s Data Science Bootcamp
To kick things off, I’ll cover the structure of TripleTen’s data science bootcamp, including what you can expect to learn and when.
And remember, this bootcamp is designed for anyone with an interest in data, which means you don’t need any coding, math, or data science background to take and pass the program.
Just 8 months of consistent effort, and you can go from zero knowledge to a fully-fledged data scientist.
I think that’s very cool, and that’s not to mention various other benefits like a money-back guarantee if you aren’t able to find a job. But more on that later…
Ready to sprint..?
First, rather than opting for standard modules, you will tackle the various segments in sprints.
Depending on your previous experience, this might be new to you, but in tech, it is an Agile management technique that tends to be the de facto standard.
Put simply, a sprint is a short, time-boxed period during which a specific set of work has to be completed and made ready for review.
And typically, a sprint lasts from one to four weeks, with two weeks being common, hence why the TripleTen sprints are each set at two weeks long.
I really love this idea because sprints help you focus on specific tasks within a defined timeframe by breaking down work into smaller, manageable chunks.
It also means that you get some real-world practice working in a pseudo-Agile way, which is ideal for prepping for a job in the actual industry.
Extra help for beginners
So, now you know that you’ll be working in 2-week sprints, what will you be learning?
Well, there are a total of 17 sprints in the main boot camp to be completed, but before you dive into those, there are 4 preparatory sprints designed to help students with zero background in math or coding.
Remember when I said this is designed for anyone and everyone with a passion for data science?
With this in mind, the idea of these prep sprints is to help you gain the foundational skills and knowledge you’ll need to succeed in the main boot camp.
Here's a summary of what these 4 intro sprints cover:
- Basic Python: Begin with the essentials of Python programming, focusing on key concepts for data science, including basic syntax, data types, control structures, and practical applications. This sprint lays the groundwork for data science projects by emphasizing hands-on learning with coding tasks and case studies.
- Computer Literacy: Get a comprehensive introduction to the world of computers, including hardware, software, operating systems, and maintaining computer health. You’ll also cover internet basics, effective browsing techniques, and online safety.
- Math Course: Get to grips with essential math concepts, including natural and integer numbers, variables, exponentiation, logarithms, common fractions, scientific notation, and percentages. This is ideal if you haven’t done any math for a long time because, after all, data science relies on math!
- Sandbox: Get to grips with the TripleTen coding environment with guided case studies on Python fundamentals, working with data types, arithmetic operations, creating functions, and handling data issues like missing values and duplicates.
I really appreciate the extra thought that TripleTen has put into these introductory sprints, as they’ve been clearly structured to help absolute beginners build a solid foundation in programming, math, and computer literacy.
Plus, they require you to get practical and hands-on right away. I am a big advocate of this approach, as data science is a hugely practical discipline.
Main content
Okay, now let’s cover the 17 main sprints that comprise the bulk of this boot camp.
As I mentioned earlier, the idea is that you’ll take 2 weeks per sprint. This means you’ll need around 34 weeks to complete the main bootcamp.
But I should be clear: this is not 34 full-time work weeks of 40 hours. TripleTen recommends that you set aside 20 hours per week to stay on track.
Of course, if you want to take these at a faster or slower pace you can, as you won’t be attending live classes or seminars.
But if you can, I’d recommend following the suggested pace, as this gives you plenty of time to absorb the content without running the risk of burning out if you go too fast or losing interest if you go too slowly.
That said, I know that many of our readers have varied circumstances, whether they have a full-time job, parenting duties, or other commitments.
So, my advice will always be to choose the pace you can sustain consistently, as this will be the key to your success.
Let’s dive into these 17 sprints and what they cover. I should also point out that each sprint culminates in a project to cement your newly gained skills while building your portfolio.
Sprint 1 - Working with Data in Python: Learn how to handle, manipulate, and analyze data with Python by covering dictionaries, lists, and complex data structures before diving into functions and built-in methods to create reusable and efficient code. You’ll also get an intro to Jupyter Notebook, a pivotal tool in data science for writing and sharing code.
Sprint 2 - Exploratory Data Analysis (EDA): Hone EDA skills in Python by focusing on essential data handling techniques, master data cleaning, learn how to tackle missing values and duplicates, and create dynamic visualizations with matplotlib. You’ll also dive into DataFrame manipulation, enrich datasets with new columns, and master aggregation and data merging strategies.
Sprint 3 - Statistical Data Analysis: Explore the essentials of statistical analysis by learning to work with continuous and discrete data while also getting hands-on with techniques like location, variance, and standard deviation. You’ll also expand your knowledge of probability and probability distributions while enhancing your skills in statistical inference via hypothesis testing and population means analysis. Plus, it’s nice to see a focus on professional skills like communication and teamwork.
Sprint 4 - Software Development Tools: Dive into essential software development tools and practices, emphasizing the terminal and command line across MacOS, Windows, and Linux. You can expect to dive deep into file management, command execution, and advanced editing techniques at the command line while also getting to grips with version control with Git.
Sprint 5 - Integrated Project 1: By this stage, you’ve reached the first major milestone in this boot camp. The idea here is to consolidate the first 4 sprints with a comprehensive real-world project where you apply everything you’ve learned while also testing your ability to create documentation, handle errors and debugging, and effectively synthesize information.
Sprint 6 - Data Collection and Storage (SQL): Gain expertise in web data management by exploring web mining, GET requests, and parsing HTML using regular expressions. You’ll then transition to SQL to learn database fundamentals, execute statements, and tackle advanced operations like data slicing, aggregate functions, window functions, and SQL joins. You’ll wrap up with an introduction to PySpark for managing large datasets and executing complex SQL queries within DataFrames.
Sprint 7 - Introduction to Machine Learning (ML): Now it’s time to dive into ML. You’ll start by learning how to define business tasks and how to use training datasets. Then, you’ll cover supervised learning via classification and regression with Scikit-Learn before tackling challenges like randomness in algorithms, managing test datasets, and mastering evaluation metrics. You’ll also be diving into advanced topics like hyperparameter tuning and model comparison, all while getting stuck into practical exercises with Random Forest and Logistic Regression models.
Sprint 8 - Supervised Learning: Building on your newly gained ML skills, you’ll get hands-on with supervised learning by covering data uploading and pilot training before delving into one-hot, label, and ordinal encoding, and feature scaling to standardize data. You’ll also learn how to assess model performance with decision trees and accuracy metrics and how to handle class imbalances with confusion matrices, recall, precision, and F1 scores. Wrapping up this sprint, you’ll learn to optimize classification models with class weight adjustments and threshold settings while diving into regression analysis and data dispersion effects.
Sprint 9 - Machine Learning in Business: It’s now time to apply your newly gained ML skills for business operations and strategic goal-setting. Expect to start with an overview of business metrics like revenue, COGS, and ROI before implementing and analyzing A/B tests and stats techniques like confidence intervals and bootstrapping to refine business decisions. You’ll also explore data management via data labeling and quality control via methods like cross-validation to prevent data leakage.
Sprint 10 - Integrated Project 2: This is the second consolidation milestone. You’ll start with a thorough review of the essential concepts you’ve covered in the previous sprints before tackling a comprehensive real-world project that emphasizes data cleaning and preparation techniques.
Sprint 11 - Linear Algebra: It’s fair to say that math is the language of data science, making this sprint on linear algebra essential for advancing your skills and knowledge. Expect to master foundational skills like vector and matrix operations, including vector addition, scalar multiplication, and matrix transposition. You’ll also explore practical applications of these techniques for solving complex problems like linear regression models with matrix methods.
Sprint 12 - Numerical Methods: In this sprint, you’ll start with computational complexity, including how to examine its impact on training models like linear regression. You’ll then explore iterative methods to enhance efficiency before moving on to optimization techniques via loss function minimization and gradient descent with Python. Finally, you’ll round out this sprint by studying neural networks from the foundational theories to practical training and advanced ensemble techniques like gradient boosting.
Sprint 13 - Time Series: Expect to start with the basics of time series data by learning about resampling techniques, rolling means, and identifying trends and seasonality. You’ll then move on to the critical concepts of stationarity and differencing methods for reliable analysis. Building on this, you’ll be ready to cover forecasting techniques by using historical data to project future values, improve forecast accuracy, and create model features. Finally, you’ll dive deeper into advanced time series models like autoregression and moving averages.
Sprint 14 - Machine Learning for Texts: Circling back to ML, you’ll explore the specialized field of ML for text data. Expect to begin with text analysis basics, progressing to practical text preprocessing tasks like lemmatization and regular expressions to clean data. You’ll also delve into feature extraction with Bag-of-Words and N-Gram models before advancing to sentiment analysis and deep learning methods such as Word Embeddings and Word2vec, not to mention BERT for text classification.
Sprint 15 - Computer Vision: At this stage you’ll be ready to build out your practical knowledge of ML by diving into computer vision with neural networks and Keras. Expect to cover various neural network tasks for image data, including logistic regression and fully connected networks for basic visual tasks. You’ll then advance to handling color images and multi-class classification, deepening your skills with convolutional layers, and implementing networks like LeNet and ResNet. You’ll even explore advanced training methods like the Adam optimization algorithm and image data augmentations.
Sprint 16 - Unsupervised Learning: This is the penultimate sprint before the final project. By this stage, you’ll be ready to cover unsupervised learning, emphasizing cluster analysis and anomaly detection to learn about its importance for uncovering hidden patterns in unlabeled data. Expect to delve into K-means clustering, optimizing algorithms, and tackling challenges like the optimal number of clusters with visualization techniques. You’ll then cover anomaly detection by applying boxplots, Isolation Forests, and KNN to identify unusual data points in real datasets.
Sprint 17 - Final Project: This is the final sprint! It’s now time to apply all the skills and knowledge acquired throughout the previous weeks in a comprehensive final project. You’ll begin with an overview of the project's structure and what is expected before moving on to developing a detailed work plan, detailing timelines and necessary resources. Then, you’ll tackle the development of the solution code, applying all of the coding techniques and various methods you’ve learned along the way. Finally, you’ll need to write a comprehensive report articulating the problem you tackled and the project's real-world impact.
What To Expect From The TripleTen Platform
When it comes to TripleTen’s teaching method, expect a range of interactive text-based lessons that are interspersed with quizzes, exercises, hands-on coding labs, and projects.
They also use a chatbot style interface for certain lessons where you’re able to interact in a back and forth conversation to mix up the learning format.
Overall, I really enjoyed their teaching style as it helped me to stay engaged throughout the various sprints.
Another feature I appreciated was the integrated code snippets that allow you to run and experiment with code directly within the sprint’s learning material.
This is ideal for testing out new ideas and concepts right away, and it also includes hints and informational prompts if you make an error or need help figuring out what to do.
Building on this, when the time comes to get really stuck into a coding project, they’ve also included a fully-fledged coding sandbox.
Think of this as an online coding editor or compiler where you can experiment with coding challenges without having to fire up your own IDE.
They’ve even added direct integration with Jupyter notebooks, which is a massively popular coding environment for data scientists and data science students.
I’m really impressed by this coding environment, as it makes it so easy to get your hands dirty by coding and playing with data.
It also meant I didn’t need to spend any time setting up my own coding environment, allowing me to dive right in and start trying things out right away.
Another nice feature of the TripleTen platform is the account calendar interface, which helps me keep track of my progress by showing how far along I am in the current 2-week sprint.
It’s also really handy for displaying the various options available for tutor hours and coworking hours.
I’ll dive into these in more detail shortly, but the general idea is that you have various support options available to you if you need help with a particular sprint, exercise, or project.
DOT, The AI Assistant
Something else that impressed me was TripleTen’s built-in AI assistant, DOT.
This is available when you access the TripleTen Discord server, and you can think of this like a ChatGPT-style tool that will help whenever you get stuck or have questions about a specific sprint, exercise, or project.
Just ask your question in Discord, and the AI will reply with very detailed, and step-by-step suggestions to help.
Very efficient, fast, and useful.
But maybe you prefer dealing with humans?
Well, that’s no problem because the Discord server is full of fellow students, previous graduates, tutors, and success managers who are there to help.
But if you’re looking for a rapid response, DOT is always available, and usually provides incredibly helpful responses.
Something else that I really appreciated though, is that TripleTen’s tutors will also check on the answer provided by DOT to ensure it meets their expectations.
So, if for some reason, the response provided by DOT does not fully align with the answer that a human tutor would provide, there is an opportunity to add corrections or additional guidance.
Discord Community
Let’s now dive into the beating heart of the TripleTen boot camp community in the form of their Discord server.
If you’re not familiar with Discord, it’s a communication platform that allows you to create or join servers where you can then engage in text, voice, and video conversations.
These servers are usually centered around specific topics or communities, and they are hugely popular among gamers, developers, and various interest groups.
When you start the TripleTen Data Science bootcamp, one of the first things you will do is join the Discord server.
You’ll then get access to a wealth of resources, not to mention a direct line to tutors, success managers, and fellow students.
I genuinely love this feature because it gives you a direct line to fellow learners for help and support or just a general forum to chat.
I think this is especially helpful if you like the comradery of a traditional classroom setting but need the flexibility of self-paced learning online.
And as you’d expect, it’s very simple to get set up, so you can get involved right away.
In general, you should expect to spend a lot of time in Discord, so let’s go into a little more detail about it.
Firstly, each sprint has its own Discord channel. These are just like Slack channels or subreddits, and they’re the perfect place to interact with other students and tutors when you want to discuss any challenges or successes you’ve had with a particular sprint.
It’s also really helpful to organize the server in this way because it allows specialist tutors for each sprint to focus their help and expertise where it’s best placed.
Outside of the sprint channels, other important channels include announcements, faqs, rules, career events, and coworking.
You might be wondering what the rules channel is for? Well, this is actually really useful, as it provides guidelines for how to ask technical questions, including how to include code.
The idea here is to ensure that questions are well formed and simple to understand, as this will increase the chances that DOT or a tutor can answer them helpfully the first time.
This also helps to build a body of knowledge with questions and answers that your fellow students can use to bolster their own understanding and learning.
Next up, the careers channel is an excellent place to find the latest news on any events that TripleTen have put together to help you land a job.
As you’d expect, this is very helpful for both current students and recent graduates who are not heavily focused on landing their first job post-graduation.
One of the most important channels, in my opinion, is the announcement channel.
This is the first place to look for the latest tutor hours, coworking hours, workshops, or live lessons in that week.
Which segues nicely to the question of what these actually are?
Let’s start with tutor hours. This is fairly self-explanatory, but during tutor hours, a tutor is available to answer your questions.
This means you can have a discussion with a tutor to get more detailed explanations or help with your questions right away.
This is just like attending a workshop at college or university to ask an experienced teaching assistant for help with anything you might be struggling with.
Next up, coworking sessions are a chance for students to study together and help each other with any questions they might have or anything they are struggling with.
This is a great idea in my book, as it gives you a chance to work together with your peers to overcome any common challenges, while also allowing you to have some human contact with other students.
Of course, these are optional, but for anyone who enjoyed working with fellow students in high school or college or for anyone who likes working in teams, this is a great way to do that.
Then, there are live lessons, which have been designed to help you better understand the concepts covered in the sprints. These are essentially webinars that are hosted by tutors.
Once again, what I like about these is that they give you a chance to have live interaction while learning, which makes this feel even more like an in-person rather than online bootcamp.
Of course, these are also optional, but I really appreciated the ability to attend these.
Now, let’s cover workshops. To my mind, these are a lot like recordings of live lessons. Think about a video lesson that’s between 40-60 minutes long and delivered by an expert tutor.
If you’ve always liked video content for learning new skills, the combination of workshops and live lessons is a great way to bolster the interactive text content in the main sprints.
Lastly, I should also emphasize the communication and community aspect of Discord.
If you have a question for a tutor, a success manager, or maybe even your fellow students, this is the place to ask.
Depending on what you’re looking for, you can typically arrange a meeting with a tutor or success manager within 24 hours.
But equally, you will also have a dedicated success manager that is available to meet with you on a weekly basis.
This is something I’ll cover in more detail below, but I really appreciated this level of contact, as it makes you feel like there is a team that’s as invested in your success as you are.
That’s one of the key differentiators for the TripleTen boot camp versus a standard online course.
Another great feature of the Discord community is the access you have to recent graduates, who are often very happy to share their own experiences during the boot camp and during their job search.
I really like this alumni feel for the community, as it offers a chance to network and a fantastic opportunity to learn from successful graduates.
This might include tips and advice on how to prepare for interviews, how to build your portfolio, or even advice on things not to do in interviews.
In my opinion, this is a literal goldmine of information, as there’s no substitute for learning how to succeed from someone who has already done it.
Code Reviews
One of the most impressive parts of the TripleTen Data Science Bootcamp is the code review process.
The idea here is to ensure that you the student not only complete your projects, but that you also reach a professional standard to prepare you for the workplace.
But how does this actually work in practice?
- Expert Reviewers: Each project you submit will be scrutinized by experienced tech professionals. Their role is to meticulously go through each line of your code, ensuring that you understand the material thoroughly and apply the tools and concepts correctly.
- Feedback and Iteration: The code review isn’t a one-time check. It involves multiple iterations where code reviewers provide detailed feedback on your work. This iterative process may include one, two, or even three rounds of reviews and revisions, refining your projects to a level that they stand out to potential employers.
- Learning from Mistakes: The reviewers at TripleTen provide constructive feedback, giving you the student space to learn from errors and improve your coding skills. This approach is taken to help cultivate a learning environment where mistakes are opportunities for growth rather than setbacks. Remember, nobody knows everything right away, so feel comfortable making errors!
- Professional Preparedness: This is my favorite aspect of the process, as the rigorous standards upheld during the code review ensure that by the time you graduate, your code is not only correct but also well-structured, clean, and understandable by others. This is essential for making you job-ready after graduation.
- Soft Skills Development: An added bonus of engaging in the code review process at TripleTen is the fact that you can enhance your soft skills. The idea here is that it prepares you to receive and utilize feedback effectively and to collaborate with colleagues in your future data science roles.
So, what does this all actually mean to you?
Well, it means that the code review process is much more than just an evaluation of your code for correctness — it’s an integral part of the training to prepare you for the real-world demands of a tech career.
After all, the idea of taking and passing this bootcamp program is to become job-ready with both hard coding skills and essential professional competencies.
For me, it’s one of their stand-out features, as it helps you cross the gap between just learning skills and learning how to apply them in a professional way.
Success Managers
I think it’s really important to also take a moment to touch on the idea of a success manager, as these will become an integral part of your boot camp experience.
If you want the TL-DR, these are a lot like guidance counselors or personal tutors who are heavily invested in helping you to succeed.
Think of these as your confidante during the boot camp experience, as they are there to help, listen, and support you with anything you might need.
In my opinion, the benefits of having access to someone like this cannot be overstated.
One of the most difficult things about self-learning is the potential for feeling isolated, but with your success manager (not to mention Discord), you always have someone to talk to.
Typically speaking, after you’ve signed up for the bootcamp, your success manager will reach out and ask to meet with you 1-2 weeks before you start and before your orientation.
This is your chance to get to know each other, but more importantly, it’s their chance to learn about you and how they can best support you.
For example, you can share how many hours you think you will have free per week to study, whether you have any particular learning challenges, whether you’re currently working a full-time job, whether you might need to take things slower, and so on.
The idea is that you can share your circumstances with your success manager so that they can help you plan for success without feeling overwhelmed in any way during your studies.
Equally, they will also be keeping an eye on your progress as you move through the sprints, including receiving any feedback from your tutors.
This gives them the chance to figure out if there’s something more that they can do to help you, whether that’s extra help with math, or computer literacy, etc.
This also means that they’re the ideal people to talk to if you need an extension to any sprints, or if you feel like you need extra help.
Overall, my advice is to take full advantage of the fantastic help that they have to offer, as their goal is to make sure that you reach the final project in the final sprint.
Is The TripleTen Data Science Bootcamp Right For Me?
Perhaps you’ve decided you want to join a data science boot camp and you’re not sure which provider is best?
Or maybe you’ve never considered a boot camp at all, and you’re still trying to figure out whether it’s the best fit for you?
Whatever your situation, it probably helps to answer the question of whether the TripleTen Data Science bootcamp is right for you.
I think the best way to do that is to break this down into a range of sub-questions.
Who is this bootcamp for?
This bootcamp has been designed for anyone with an interest in data science — regardless of their background in coding, mathematics, or data science.
This inclusivity is a key point because the program starts from the very basics, including preparatory sprints that cover Python programming, computer literacy, and essential math concepts.
This foundation ensures that even absolute beginners can start on solid footing, making it an excellent choice whether you're looking to transition into data science from a different field or if you’re looking to re-enter the workplace after a long absence.
What is the curriculum, and how is it taught?
This bootcamp is structured into 17 two-week sprints, each culminating in a practical project to reinforce the skills you’ve learned.
This project-based learning is crucial for helping you understand real-world applications of data science and for building a robust portfolio.
If you thrive in a structured environment and benefit from applying learning directly through projects, this format will suit you really well.
What is the time commitment for this bootcamp?
The recommendation is to dedicate around 20 hours per week over approximately 8 months.
This means it is a part-time model that’s flexible enough to accommodate professionals who might be balancing work or other commitments.
It’s also good if you prefer a learning pace that allows for depth without overwhelming intensity, the pacing of this bootcamp would be ideal.
That said, you can go as fast as you like and complete the sprints as fast as you can manage because, ultimately, it is self-paced.
However, I would recommend that most students adhere to the 2-week sprint format if they can, as the program was designed with this in mind.
Will TripleTen help me find a job?
If your primary goal is to transition into a data science role, TripleTen's boot camp is designed to equip you with both the hard skills and the professional skills needed in the industry.
The curriculum not only covers technical subjects like machine learning and SQL but also emphasizes soft skills such as communication and teamwork.
But most importantly, with an 87% hiring rate for graduates and a money-back job guarantee, the program is heavily geared towards making you attractive to employers.
Is this bootcamp good value for money?
There’s no doubt that any bootcamp can be a significant financial investment, and in terms of the TripleTen Data Science program, this is priced at $9,700 when paid upfront.
Although there are also various payment plans to ease this cost if it’s not feasible to pay upfront.
That said, the potential return on investment is high, given the career outcomes and the bootcamp's job placement support.
Additionally, the money-back guarantee if you don't find a job within six months post-graduation significantly reduces the financial risk.
How much support is there for me while taking the boot camp?
Despite being an interactive and online bootcamp, TripleTen provides some very impressive and robust support with a network of tutors, mentors, and peers.
This is all accessible via Discord, where you’ll find a vibrant and active community to support and encourage you on your journey.
Plus, this is also where you can interact with DOT, the integrated AI assistant that’s available to help with any technical questions you might have.
Also, this community aspect is also a great way to network, and this can even help land a job post-bootcamp.
What Are Externships?
You’ve likely heard of an internship, but what about an externship?
Well, this is a unique feature provided by TripleTen that offers you the chance to engage in real-world projects.
As you’d expect, these are akin to internships, but they’re integrated directly into the bootcamp’s curriculum, providing hands-on experience with real tasks that companies face today.
Being a massive fan of getting hands-on to reinforce technical skills, I absolutely love this idea. But what’s most impressive to me is the ability to work on projects for real companies.
That said, let’s take a closer look at the various benefits of these externships, including a summary of some example externship projects.
Practical Experience: TripleTen externships are designed to bridge the gap between academic learning and the real-world application of data science and coding skills. You will participate in actual projects, such as developing websites, mobile apps, or analyzing extensive datasets for real companies. This not only enhances your technical skills but also sharpens your problem-solving abilities under real-world constraints.
Professional Growth: Through these projects, you can receive valuable feedback from IT specialists, which is ideal for refining your work to meet professional standards. This feedback is crucial to help you understand how to improve and succeed in tech roles while also boosting your profile as a capable and knowledgeable tech professional.
Networking Opportunities: Externships also provide a platform for you to connect with industry professionals and potential employers. These interactions can and do lead to job opportunities, recommendations, and valuable insights into the industry, not to mention career advancement.
Confidence Building: Working on significant projects and receiving positive feedback can be a great way to boost your confidence in your newfound skills. I think this is also essential during job interviews and in future job roles, as it can empower you to tackle challenges assertively and competently.
Portfolio Enhancement: Unsurprisingly, one of the largest benefits of participating in an externship is the addition of real, completed projects to your portfolio. For potential employers, a portfolio featuring actual work on real-world projects is often more impressive than hypothetical school assignments because it demonstrates a candidate’s ability to deliver work that impacts real businesses.
So, what kind of projects can you expect to be involved in if you take part in an externship?
Here are some examples from previous TripleTen students:
- Helping Permits.com optimize its targeted ad spending and define key customer demographics. This involved analyzing transactional data to identify spending patterns and customer preferences, which directly influenced the company's marketing strategies.
- Creating a support widget for EdTonomy, an educational platform, enhancing user interaction and feedback mechanisms within the app.
- Enhancing game localization at Allcorrect Games by analyzing user reviews to identify the effectiveness of translations and the issues gamers face across different regions.
- Optimizing data analytics for Prepare4VC by analyzing extensive data sets to identify growth opportunities and investment patterns.
As you’d expect, these projects not only provided practical learning experiences but also delivered real business results, helping companies improve their operations and strategies based on data-driven insights.
This is the type of experience that can truly elevate your resume when applying for jobs, and it’s something I’ve been massively impressed with.
And in fact, it’s also one of the many reasons why I’m so enthusiastic about this bootcamp outside of their impressive hiring rate and money back guarantee, because one of the biggest barriers to newcomers in data science is practical experience.
But this completely removes this obstacle alongside delivering the other benefits I covered earlier.
So, put simply, by tackling real challenges from real companies, you not only enhance your learning but also make a tangible impact in the tech world.
Soft Skills Training
Now, while we all know that data science is a very technical field, it can’t be overstated just how important it is to also hone your soft skills.
After all, the purpose of data science is to physically communicate hidden insights to customers and project stakeholders.
Now, of course, you most definitely need hard skills, but the importance of soft skills can often be overlooked by newcomers who are keen to learn Python but less aware of the need to speak effectively about their findings.
But what do I mean when I say soft skills?
Well, in general, I’m referring to teamwork, resilience, and effective communication, all of which are essential for working effectively in diverse teams.
And in fact, these can often be the deciding factor in hiring decisions, especially when technical skills are comparable among candidates.
Plus, with the rise of remote work, soft skills can help maintain productivity and foster a cohesive team dynamic across different geographical and cultural landscapes.
That said, how does TripleTen help you with this in the Data Science bootcamp? Great question.
Well, soft skills are integrated into each sprint through practical examples and real-world applications.
This means that rather than lecturing you about soft skills, they are actually embedded into the fabric of the technical training.
This includes immersive activities where you can engage in peer-to-peer storytelling, manage team projects, and interact with career coaches to refine these skills.
Plus, each technical module includes segments that encourage you to practice these soft skills in real scenarios, such as during externships with partner companies.
Something else that stood out to me about TripleTen’s focus on soft skills was their understanding of the skills that are actually valued by employers.
After all, the goal here is to land a job, so you need to make sure you’re emphasizing the skills that employers want and need.
What does this all mean?
Well, employers are particularly keen on candidates who exhibit learning agility, an ability to work well within teams, goal-setting acumen, and a self-driven attitude.
And, of course, proficiency in storytelling and business thinking is highly regarded, as these contribute to clearer communication and strategic decision-making.
TripleTen understands this, which means that by taking the program, completing all of the tasks, and graduating, you will have gained these skills naturally along the way.
Plus, to help you showcase your soft skills to potential employers, TripleTen will even guide you in creating detailed career maps and help you understand the cultural norms of your target job market.
Although I’m straying into their career coaching now, which I cover in more detail below.
But the main message is that with their help, you’ll not only know your technical stuff, but you’ll also walk into interviews ready to demonstrate how your soft skills make you the perfect fit for the team.
Sounds good to me!
What Real-World Skills Will You Learn?
Whenever I’m weighing up a new course or boot camp, this is always my first question!
After all, if you’re like me, you probably want to take a data science boot camp to gain practical skills to use in the real world.
Of course, that’s not to say that learning data science can’t be fun for its own sake!
But let’s be honest: if you’re thinking about taking a boot camp, you should have your eyes on landing a job or a promotion in the field, right?
So, what can you expect?
Well, after taking TripleTen’s Data Science Bootcamp, here’s a summary of the real-world skills I think you can gain:
Data Handling and Python Programming
From the very first sprint, you dive into Python to manipulate, analyze, and visualize data. You’ll gain proficiency in using libraries like Pandas for DataFrame manipulation and Matplotlib for creating dynamic visualizations, which are essential skills in any data science role.
Advanced Data Analysis Techniques
As you progress, you’ll master Exploratory Data Analysis (EDA) and statistical methods, learning to uncover insights from both structured and unstructured data sets. This includes handling missing data, merging datasets, and applying statistical tests—a must-have skill set for interpreting complex data in real-world scenarios.
Software Development and Version Control
You’ll develop essential software engineering skills, such as using Git for version control and navigating the command line, which is crucial for collaborating in data science work environments.
Machine Learning and Modeling
Delving into machine learning, you’ll start from the basics and advance to complex models. You'll learn to build, evaluate, and refine predictive models using supervised and unsupervised learning techniques, preparing you for roles that require building or improving automated systems based on data.
Business Acumen and ML Applications
Applying machine learning to business scenarios, you’ll analyze key performance indicators and employ advanced algorithms to solve real-life business problems, enhancing your ability to contribute strategically to business outcomes.
Specialized Techniques in Text and Image Processing
By exploring advanced fields like natural language processing and computer vision, you’ll be equipped to tackle specialized roles that require processing and analyzing text and image data.
Project Management and Real-World Application
Each sprint culminates in a project, simulating real-world challenges and ensuring that you can apply your learning practically. These projects not only enhance your understanding but also contribute significantly to a portfolio that showcases your ability to potential employers.
And the cool thing about all of these skills is that they are hard skills you gain by getting hands-on with data science projects.
Remember what I said at the beginning? When I take a course, I want to walk away with something tangible for my time investment.
And that’s exactly what you get: a practical set of data science skills to get you job-ready.
Will TripleTen Help You Get A Job?
I’ve said this more than once, but if you’re thinking about taking data science bootcamp, chances are fairly high that you want to use it as a platform to land a job. Right?
Well, it’s only reasonable then to ask the question, will TripleTen help you do this?
If you want the very short answer, yes, they do. But there’s much more to it than that.
Comprehensive Career Preparation
From day one of your training, you get access to the Career Prep course. This is designed to build your foundation in crucial job application skills such as resume writing, cover letter crafting, and assembling a compelling portfolio.
You'll also learn to showcase your projects effectively, highlighting the practical skills you've acquired during the bootcamp.
Personalized Interview Preparation
This is another nice feature, as TripleTen tailors its interview preparation to meet each student's specific needs.
This includes HR and technical mock interviews, where you practice responding to the typical questions asked by tech employers.
You can also support this practice with a wealth of resources like checklists and instructional videos, ensuring you feel well-prepared for every step of the interview process.
Networking and Brand Building
It might not immediately stand out to you, but it’s really important to understand the importance of networking.
To help you with this, TripleTen guides you through creating a networking map and teaches you how to engage with industry professionals effectively.
This includes the subtle art of initiating conversations on LinkedIn, making connections, and using your network to find job opportunities.
The idea here is to help you build a personal brand that stands out in the competitive job market.
Real-World Application Through Externships
We’ve already touched on the many benefits of externships in this article, but it bears repeating that these are practical platforms to apply both technical and soft skills in real-world settings.
These placements with partner companies can be pivotal in gaining hands-on experience, which not only bolsters your resume but also provides a critical understanding of working in tech environments.
Ongoing Support and Career Acceleration
Once you're ready to enter the job market, the Career Acceleration program kicks in.
This includes one-on-one coaching sessions where your career coach will work closely with you to refine your job application strategy, improve your interview techniques, and enhance your overall job-search approach.
Guaranteed Support Post-Graduation
Perhaps most importantly, TripleTen stands by its commitment to your success.
That’s why they offer a full refund if you don’t secure a job or promotion within six months of graduation.
Plus, with an employment rate of 87%, the effectiveness of their career support somewhat speaks for itself.
TripleTen Pricing & Value for Money
Now, if my first question about a boot camp relates to real-world skills, a close second, if not tied for first place, is the obvious question about cost.
After all, compared to something like an online course, boot camps can be significantly more expensive.
So, how much does the TripleTen Data Science boot camp cost?
Well, depending on the payment structure you choose to go with, you can expect to pay the following:
- Upfront cost: $9700
- Pay via installments: $1200 per month for 10x months ($12,000 total)
- Learn now, pay later: from $305 per month for 36x months, with the first payment due 3x months after graduating. Note that this option depends on the loan term and the agreed-upon APR.
The next question you’ll probably have is, does this seem like good value for money?
In my opinion, most definitely yes! But why?
Great question. Well, let’s start with the fact that TripleTen has an 87% hiring rate for successful graduates, and the median annual salary for these graduates is $76,600.
Even in the simplest terms, this can be equated to an 87% chance of landing a very well-paid job after graduating.
Those are fantastic odds, and given the challenges that many in tech have faced with finding work in the past 24 months, even more impressive.
Secondly, you have to factor in TripleTen’s money-back guarantee. For me, this is a massive deal.
The idea is that if you can’t find a job within 6 months, you get your money back.
Think about that for a moment. You have an 87% chance of landing a job, but if for some reason you can’t do so within 6 months of graduating, you get a refund!
In my brain, I really struggle to see any downsides to this.
In fact, if I was starting over, this is the type of value proposition that I’d find too hard to resist.
Plus, think about it like this. If you wanted to gain the same skills by attending a college or degree program, you could easily be paying 10-20x as much over a far longer time horizon.
But in that case, the college or university will not be offering you a money back guarantee if you can’t find a job within 6 months.
Not to mention the fact that this boot camp is tailored to get your market ready with practical and useful data science skills.
And that’s without re-examining the level of support you get from their career coaches and the incredibly vibrant and helpful network of tutors, mentors, and fellow students to help you during your learning journey.
It’s honestly very impressive.
So, if you want the TL-DR, this boot camp is extremely good value for money.
Wrapping Up
There you have it, an insider's tour of TripleTen's data science bootcamp, from the basics of Python programming to the complex landscapes of machine learning and data analysis.
Whether you're eager to break into the tech industry, leverage big data for strategic decisions, or advance your data science career with job-ready skills, this data science bootcamp is designed to help you make this happen.
And with TripleTen's hands-on, sprint-based learning approach, you’re not just learning theories but applying them in real-world scenarios, making it an ideal launchpad for both novices and professionals looking to deepen their expertise.
Plus, the collaboration with industry leaders and real companies ensures that the skills you gain are directly applicable, enhancing your employability and market relevance.
Moreover, TripleTen's successful track record with an 87% hiring rate speaks volumes about the effectiveness of their program. And that’s not to mention their money back guarantee if you’ve not landed a job within 6 months of graduating.
Whether you’re plotting a career shift, seeking promotion in your current field, or aiming to master the vast world of data, the knowledge and experience gained from TripleTen's Bootcamp are invaluable.
Plus, the robust support from career coaches and the vibrant community ensure you’re well-prepared and connected for your data science journey.
So, my advice? Dive into the world of data science with TripleTen, start shaping your future with each sprint, and build the skills that will define the next chapter of your professional life.
And remember, in the fast-evolving field of data science, every day is a learning opportunity.
Good luck, and I'd love to hear about your journey into data science with TripleTen. Share your experiences below.
