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Nowadays, it is quite hard to browse through the internet without getting reminded of data science’s importance and popularity.
That small advertisement you’ve at the right top of a website claims you can become a data scientist quite quickly. But is it true? How long does it really take to learn data science and call yourself a data scientist?
On average, you will need to study around 500 hours of lectures to learn data science adequately. For around 100 hours, you can understand the basics of data science. The numbers can vary depending on your knowledge of programming, calculus, and statistics.
The 21st century has proven to be the age of technology and science. Every sector you could imagine records, studies, and analyzes the data in their hands. In this article, I will be guiding you through the whole process of becoming a self-trained data scientist. In the end, I will even talk about getting a job in the industry as a data scientist.
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Data science has become a „thing“ in the 2010s. Another trending topic of our decade is Massive Open Online Courses (MOOCs). MOOCs claim to make all learning resources are free for you and millions of others to take. The amount of available online educational resources on data science is ENORMOUS.
Just one of the respectable online learning platforms, Edx contains 49 data science programs and 234 data science courses. Now think about all the platforms, apps, software and books waiting for you. While there are free and paid alternatives, there are enough resources available to learn data science on your own.
The real question is whether you are good at studying on your own or not. After the new coronavirus disease started in 2019, the home office has become a part of our daily life and most of us proved we could indeed work remotel0y.
Yet, studying at home and working at home are two separate phenomena and you should be careful. Even if you work remotely, you always have assignments, deadlines, projects and sadly a boss that scares you.
In fact, you can start from the beginning and get to the point of having a master’s degree in data science on your own. If you are ready to spend some money on education, you can obtain certificates from respectable institutions that are valid internationally.
However, you must not forget it is not just a watch video, pay money, get the document process. All the programs and courses that offer certificates include assignments you have to submit and a final test to take.
If you decide to get a certificate to demonstrate in your resume, you will have to accomplish that certificate’s requirements.
There are alternative routes you can take if you have decided to become a self-trained data scientist. The route you would take depends on what kind of a learner you are. Are you a good reader? Or do you prefer watching educational videos? Would you prefer hands-on tutorials?
The time you need to become a data scientist, depends on your background. Before starting the training to become a data scientist, you should already have collected some of the skill set required from the profession.
You should have knowledge and understanding of programming, mathematics, statistics and data structures. While some of the data science courses include some introduction on these subjects, it usually just scratches the surface. They will probably cause more confusion if you don’t have the necessary foundation.
All basics you should cover before the data science training is widely available online. In a rough estimation, you would at least spend a year (5 hours per day, 300 days per year) to knock the doors of data science education.
Of course, you can always jump straight into data science, but I must say it will not go unnoticed later on in your career.
Once you get there, it is actually easier and faster than you would expect. One of the most popular educations is IBM’s certificated data science course. The program expects you to be able to „graduate“ in a year and a month if you allocate between 10-15 hours per week.
The more time and concentration you dedicate to your self-training, the sooner you will be able to call yourself a data scientist. On average, if you approach the training as a full-time occupation, it would not be a miracle if you could obtain a certificate within three months.
Even if you graduate from a program, train yourself sufficiently or get a certificate, you should not forget this is just the beginning. The curriculum for data science education was completely different five years ago and will be quite different in five years.
Mastering data science requires years of dedication and self-education. Remaining at that level requires even more. But, don’t worry! You have accomplished the hardest part. You have started!
So far, I have covered if you could become a self-trained data scientist and if so, how long would it take? Since the internet is full of resources, I will be summarizing the most efficient ones.
Before beginning, I should summarize the rules I will be following through the listing. First, none of the education listed here will need you to get up from your couch, as long as your PC is within your reach.
Whenever you think about education, your first urge is to check what A-grade universities offer. As expected, many of them offer online education on data science, and although really good, they are not that cheap.
One of the most well-known universities, Harvard University, offers a 4-course graduate program.
Edx.com contains programs and courses offered by universities and institutions. Data science is not an exception. Through Edx, reputable institutions like Harvard, MIT, Berkeley, and IBM offer certification education.
On average, you would pay around $900 for the certificated programs with 8 to 10 courses. Remember you can always take the courses for free if you don’t care about the certificate! But if you do plan paying, you can share the certificate on Linkedin
All education platforms, Udemy.com, Udacity.com, Coursera.org, etc. have plenty of data science education available. The costs and quality of the courses vary. I will include some of my recommendations here, but you can always check the ratings of courses.
A particular one I would recommend for you to check is a 10-course program in Coursera, offered by John Hopkins University. The program is called „Data Science Specialization“ course.
With over 600,000 people enrolled and tons of positive reveiws taught by a reputable University, it offers a solid foundation for R. When you finish every course and complete the hands-on project, you’ll earn a certificate.
Similarly, the University of Michigan offers a certificated data science program, „Applied Data Science with Python Specialization. “As the name suggests, the program specializes in Python-based Data science, a very popular recent programming language.
If you have $750 you intend to spend for your education, a program by Metis Bootcamp, „Introduction to Data Science“ is a good way to go. You will receive five weeks of live online training four days a week and 3 hours a day.
A good free alternative from reputable Harvard University is the CS109 Data Science course. Everything is available online for you to grab on Github.
Unlike others mentioned so far, the course is not interactive and does not offer any certificate. But, you will definitely not waste money, since you won’t spend any!
For $95, a good alternative for you would be „Data Science and Machine Learning Bootcamp with R“ course available in Udemy. The instructor deserves applause as the course covers all basics. The course provides a cheap alternative for the ones starting from scratch. Also Udemy tends to have lots of sales on courses offering deep discounts. Be sure to check them every so often.
If you are a good reader and a bad watcher, you have plenty of options. One of the best, „Statistical Learning with Sparsity: The Lasso and Generalizations“ by CRC Press, is waiting for you to download it for free.
You can grab it from the website of Stanford University. The book covers nearly all approaches you should learn to become a data scientist.
To be honest with you, all these available online trainings tend to inflate the number of data scientists jobs available. This does not necessarily mean it is hard to get a data science job in 2021, though.
A recent report by IBM states around 3 million job openings were available in data science-related careers in 2020. This equals a 45% increase compared with 2019, despite the global economic crisis. The numbers are only expected to continue to increase over the years.
As I said, there are quite many data scientists, thanks to the available online training. It requires only dedication and hard work to shine as a data scientist and fill one of the openings available.
Just remember, looking for a data science job is not quite different from other professions. Aside from providing projects showcasing your skills, it will require a good resume, endless interviews and tests.
You should also expect to be competing with a number of others through the process. Be sure to:
- Reach out to several employers through LinkedIn or any other professional networking website. Also if you have a decently big network, reach out and see if any of them are looking to hire a data scientist.
- Apply for as many data science positions as you can online.
- Choose companies based on whether they use big data for their business. This is because smaller companies rarely have the resources to hire experienced professionals in this field.
It helps to keep yourself updated with the latest technology trends and industries! Set your expectations right, obtain the necessary qualifications and get that job!
Now you have all the necessary information to start your training and become a data scientist! Remember! Look at the mirror, smile at your boss, and never lose your motivation to study harder and further!