In 2017, data scientist was the 9th most in-demand, IT role in France and the United Kingdom, and demand continued to rise. Yes, data science bootcamps and courses are becoming increasingly valuable. Enrollment in data science bootcamps, which emphasize immersive, hands-on, and focused learning, has increased as more employers now favor experience and demonstrable skills over mere credentialism.
Data science and analytics courses and bootcamps have swiftly gained popularity because they provide the kind of intensive, targeted, and accelerated learning best suited to prepare people for data jobs with the field-specific, job-ready skills they'll need. Most importantly, enrolling in a bootcamp means that someone else is involved in your success and is ready to lend a hand when you need it, provide comments on your progress, CV, and portfolio, and get your job hunt started.
Data science bootcamps are intensive, three-to-six-month educational programs that promise to equip graduates for entry-level careers. Programming, data visualization, statistical analysis, data analysis, and predictive analytics are among the technical skills acquired by graduates.
Machine learning, prescriptive analytics, and predictive causal analytics are all used in data science to assist us in making predictions and, more importantly, judgments. To put it another way, it employs technology and math to uncover hidden patterns (as well as strategies to increase profitability and productivity) in raw data.
Data science bootcamps teach students how to do this using a range of languages and frameworks, such as Spark, SQL, Python, R, Pandas, and Hadoop. To mention a few topics, you'll study the fundamentals of linear regression, A/B testing, coding, and machine learning.
There are numerous advantages to attending a data science bootcamp. For starters, the program is less expensive and takes less time than a typical bachelor's degree in a related subject. Bootcamps can be completed part-time or full-time, allowing for greater adaptability and flexibility in learning. Also, these schools frequently provide career counseling, which can be critical in securing a job following graduation.
While there are numerous potential advantages to attending a bootcamp, it's vital to keep your expectations in check.
It quickly prepares you for a new career
Perhaps the most compelling selling argument is that you will be up and running and job-ready in a fraction of the time it takes to earn a standard college diploma (even more so if you tack on any post-graduate work at the end of that). You can be ready to ace an interview for an entry-level position in three to six months. When you consider that the typical entry-level Data Scientist in the Netherlands earns €68,880, €30,050 in Spain, €64,024 in Germany, and €55,485 in France, it's easy to see why.
Create a professional network
The quantity of networking choices it may provide is a significant selling factor. Most institutions arrange networking events, invite prominent tech titans to appear on campus as guest speakers, host graduate project displays, and have instructors that are industry experts with extensive networks of contacts. As they begin their job search, your classmates will also become essential contacts.
Get in on the ground floor of a high-demand field
For a reason, data scientist has been dubbed the most promising career and the most excellent employment in Europe by LinkedIn. Demand – and salaries – are now strong and expected to continue to climb.
According to MIT research, organizations that used data-driven decision-making in the top third of their industry were 5% more productive and 6% more lucrative than their competitors. Consider that data science is a relatively new subject, and many businesses have been reluctant to grasp the value of investing in data in terms of insights and revenue.
Statistics aren't as vital in these programs as in typical college programs
Because data science is such a broad subject, the type of job you're searching for will determine whether you should attend a bootcamp, get a master's degree, or use other online learning tools.
Data science bootcamps are a good fit for machine learning since they teach you all the programming languages you'll need to create and apply models. However, a bootcamp may not always be the best option. A graduate degree may be required for work in research. If you want to work in the financial sector, the same may be said. Examine some job advertisements for positions that you are interested in. Check to see if an advanced degree is required. This could assist you in making your selection.
The Cost of a Bootcamp Data science bootcamps aren't inexpensive, even when compared to the expense of higher education in the United Kingdom. Even after deducting the cost of tuition (let's say €750) and any essential technology (a laptop?), you still have to account for the revenue lost while enrolled in a full-time program for 12 weeks.
You can lessen the impact by applying for scholarships and learning about the various payment methods available at the institution. Part time programs can also be a good option to continue earning while learning.
The average salary for a data scientist is £59,781 in the United Kingdom, €68,880 in the Netherlands, €30,050 in Spain, €64,024 in Germany, €55,485 in France, and €37,785 in Italy.
Senior data scientists in the top four nations on the list earn an average of €67,428 in France, €80,300 in Germany, €90,500 in the Netherlands, and £87,575 in the United Kingdom. A chief data scientist, on the other hand, earns up to £128,040 in the United Kingdom, €114,155 in Germany, €102,033 in the Netherlands, and €89,000 in France.
Given that entry-level Data Scientists earn an average of €60,000, and seasoned industry experts make much, much more, the income potential for Bootcamp students is pretty significant.
Because data science is still relatively new as a field, experienced data scientists are in short supply, and their salaries reflect this.
Yes, it is quite likely to assist you in finding work, with the vast majority of data science bootcamp graduates stating that they have found work in the sector. Indeed, between 74% and 90% of bootcamp graduates find employment six months after graduation. According to reports, most people can discover alumni securing jobs at big organizations like Facebook, Amazon, Microsoft, and Google.
After finishing a data science bootcamp, you might have the following job titles:
- Data Engineer
- Machine Learning Engineer
- Big Data Analyst
- Business Analyst
- Database Administrator
It's worth mentioning, though, that some people complete bootcamps but are unable to find work in the business. It's not always easy to master, and not everyone is made out for the role of Data Scientist.
Yes, graduates of data science bootcamps are finding work in droves, with firms in desperate need of data talent snapping up alumni soon after graduation.
Because of the high demand for data experts, it's pretty rare for a bootcamp graduate to go unemployed. Check any well-regarded school's outcome report, and it should show this.
To ensure that you find work after graduation, you should apply yourself as much as possible during the course, and rely on your newly developed professional network when looking for an entry-level position.
You'll master your trade under the direction of industry experts at a reputable data science bootcamp. As you progress through the course, constructing models and creating visualizations, you must seek their constructive comments. Most data science bootcamp grads report that interacting with instructors was one of their favorite parts of the program. Taking advantage of that opportunity to learn from someone who knows what they're doing is critical to getting the outcomes you desire.
Yes, a data bootcamp is worthwhile, but your success depends on the school's quality, your degree of commitment (both learning and networking), and your background and previous expertise.
You would be an excellent contender for entry-level employment if you attend a bootcamp that has a strong reputation for producing qualified graduates, allows you to work on at least one live project, and helps you establish your professional network through networking events and other techniques.
During your bootcamp, you'll learn how to create and apply machine learning models, as well as learn how to program in a range of languages (such as Python) and create eye-catching visualizations.
Those are the abilities that most data science employers seek, and landing a data science job after only a 10 to the 16-week course would be well worth it for most people, depending on where they are in their careers now.
Another reason most graduates appear to think a data science bootcamp is a good investment? At the moment, it's a fantastic field to work in. In 2020, the field was expected to grow by 28%, resulting in around 2.7 million new jobs. That's more jobs than recent graduates can fill, so IT workers from other industries will have to brush up on their skills and transfer them into data to fulfill the need.
When it comes to bootcamps, your success will be determined by how much effort you put in, how you approach the situation, and how committed you are. Here are some pointers on how to make a data science camp worthwhile.
- Do your research and make informed decisions
Employers are interested in bootcamp graduates, but not every institution has a good reputation. Before starting your bootcamp experience, double-check that the program you're contemplating is well-regarded. Read online evaluations, speak with current or recent students or graduates, or ask a data science recruiter or hiring manager for their recommendations on the top programs and colleges. Examine the curriculum and prerequisites for the bootcamp in depth. Take a campus tour or look at a virtual time if it's an in-person course. Also, read the bootcamp's outcomes report to see how its graduates are faring.
Get out there and build a network
The networking possibilities provided by on-campus (and virtual) networking events, as well as the guest speakers from prominent tech organizations that visit the classrooms of the finest data science bootcamps, are something that bootcamp alumni frequently rave about. Your students may become future coworkers, so the ties you're creating are essential. That goes for your professors as well. You'll learn from industry professionals with extensive professional networks at a solid bootcamp. Use this moment to make an impression on them.
Begin working on live projects as soon as possible
One of the reasons that such a high percentage of data science bootcamp graduates are recruited soon after graduation is that they are allowed to work on real-world projects during their programs. They can later show employers to demonstrate that they know what they're doing.
Obtain feedback As previously said, a good data science bootcamp will feature professors who have worked in the field you want to work in. Take their feedback on your projects and visualizations carefully; a future employer will most likely see the same things they do. One of the best aspects of attending a bootcamp is having the ear of an industry expert, so make the most of it.
You should perform some self-reflection before deciding which data science bootcamp is suitable for you. What are your objectives, and how much time are you willing to devote to them?
Let's start with deciding which delivery method is ideal for you:
Bootcamps that are full-time and take place in person
This is most likely what comes to mind when you think about "Bootcamp." This would be an intensive, immersive curriculum in which you would spend 40 to 80 hours a week in class and some of your free time working on your projects. What are the advantages of this model? There is no faster approach to achieving your objectives. What's the drawback? Juggling a job can be difficult, if not impossible.
Online bootcamps that are full-time
There's a good chance you're under the impression that these courses are more straightforward. They aren't. Usually, online bootcamps that are full-time will still require about 40 to 60 hours of classroom time per week, and you'll have to finish your assignments on evenings and weekends. Don't expect to get away with it.
Part-time, face-to-face bootcamps
For individuals who are hesitant to commit to a full-time schedule, this could be a good compromise. You still receive some of the advantages of taking an in-person course, such as greater networking chances, the ability to attend campus activities, and, at the very least, top-of-the-line technology that you can use after hours if you follow a decent bootcamp. Of course, there's a catch: you won't be able to get started as a data scientist as quickly. Compared to full-time studies, most part-time courses take two to three times as long to finish.
Online bootcamps that are part-time
You can take a flexible online course for the most flexibility. This option may most appeal to folks already employed and who want to upgrade their skills. However, just like in-person programs, the course will take longer to finish – especially if it's self-paced.
You must first establish what is most important to you to determine which data science bootcamp is best for you.
Overall, you must assess whether a data science bootcamp is appropriate for you. You are likely to succeed if you want to alter your profession at your own pace with no fluff in the course content, and you are a hustler and prepared to put in the effort. And, of course, to select a bootcamp that feels like a good match for you.
Finally, you can have a look at the Data Science bootcamp available on our platform. We are providing the most current coding bootcamps! Our courses are available both in-person and online. Our instructors will assist you in developing the technical skills you'll need to succeed in your chosen field. No matter what your IT goals are, our 1:1 coaching services will provide you with specialized advice.
Start your career as a data scientist with our free workshops, which are based on an adaptable curriculum and guided by industry experts.