3 Components of the Data Scientist Profession that Need to Be Prepared in Industry 4.0

Data Science is a science that can be applied in everyday life but we are often unaware of the presence of this data science. For example, when you surf the internet you just read some articles about cats, then some time later you watch youtube you will see a lot of cat videos on your homepage. This happens because when you read an article about cats your data will be sent into Big Data and read that you are interested in cats and Big Data will provide relevant content.

Without realizing it by bringing up content that suits your taste will make you surf the internet more often and the company can provide custom ad that matches the content you like. Data Scientist is responsible for managing and maintaining data in Big Data.

Although Data Scientist is a job that is much sought after by companies, but currently in fact the talent of a Data Scientist is still very sought after, especially for those who are pursuing data science competencies. Vacancies to become Data Scientist are abundant, but few pursue this profession.

Most people are intimidated by the word “data” which makes the profession of Data Scientist is still a prima donna profession that is quite difficult to achieve for most people. Basically being a Data Scientist is not as difficult as thought, even to become a Data Scientist can be by learning self-taught.

Here are the first steps for you to pursue a career as a Data Scientist!

1. Hard Skill

When you enter the world of Data Science, of course you can not just enter without having a mature provision. One of the things you need is skill.

Without adequate skills you will have difficulty in going through various projects. The skills needed to become a Data Scientist are:

• Statistics

Statistics is the basic science that every data scientist should have. By having an understanding of statistics will be useful when you determine the algorithms to be used when processing data, and also with statistical science you can develop machine learning software so that it will further improve your skills as a Data Scientist.

• Understanding logic

Of course, understanding logic is needed by a data scientist. A data scientist will dwell on unstructured data and make the data applicable in the form of graphs, machine learning, deep learning, and much more.

Understanding logic can be trained by working on mathematical problems in the form of stories or understanding the basic concepts used in processing data.

• Programming language

If you want to become a Data Scientist of course you must at least master at least two programming languages such as R or Python if you have started to understand the big picture of programming languages you can add your programming language to JavaScript, HTML, PHP, or C ++. Programming languages are important for providing instructions to the computer in order to perform certain tasks

DQLab also provides a free module for those of you who create a DQLab account now there are also modules “Introduction to Data Science with R” and “Introduction to Data Science With Python“. The two modules are complete discussions about the R and Python programming languages and there is a Quiz that can directly test how ability you are in capturing existing material.

Also read Know the Various Technologies Resulting from Data Science Implementation

• Database management

Often the data obtained is not perfect either from writing or placement. Of course, as sophisticated as computers today still cannot stand alone without human assistance, if there is writing that is not in accordance with the commands given certainly cannot be processed by the computer. For example, we get the word “Jakarta” while the new computer can run the command if the writing is “DKI Jakarta”. Therefore, having a “neat” database is also a skill needed by Data Scientist.

• Machine learning

If you want to work in a company where the product is related to data such as Waze, Netflix, or Gojek, of course, you need machine learning to process unstructured data with a very large amount. With machine learning can also create artificial intelligence.

• Deep learning

Many smartphone applications already use deep learning. What exactly is deep learning? Deep learning is a machine set up to mimic how the basic systems of the human brain work. The concept of deep learning itself is used in Google Photo where if we photograph pictures of dogs then the machine will ascertain whether the photos we capture there are dogs, if there is google will offer photos of other dogs.

• Data Mining

By understanding data mining, you can understand more about the observed data. If you explore this skill later you can find certain patterns hidden in a data. Because data mining itself has a complicated process ranging from, the stage where unstructured data is filtered back to the visualization stage that aims to visualize in the form of charts or charts helping clients in understanding the results of this data mining.

By having skills like above, of course, you can become a Data Scientist, but of course the theory with its application will have some differences. Therefore, the second point is also an important one in pioneering a career as a Data Scientist.

Also read Kenali Data Mining untuk Belajar Data Science Pemula

2. Work on Project Data Science to Get a Certificate

Experience is important if you want to start a career as a Data Scientist. Start looking for projects related to Data Science that are large or small scale.

This experience will certainly be useful if you want to continue your career as a Data Scientist in a large company. By working in a small project, the company can see how responsible you are in working on a project even though the project is relatively small.

3. Build a Data Portfolio

Building your portfolio is an important element if you want to be accepted into a large company. In your portfolio you can list things you’ve achieved, work experience, and more. You can also show your company that you’re a responsible person, one of the best ways to create a portfolio is to build on a website. By building your portfolio through the website, you can show your work without any restrictions on file size.

In this portfolio you can also build your persona that suits the character of the company. No less important with skills, attitude is also a big thing in determining you are worthy in working in the company. So build a positive image and be willing to learn in your portfolio.

4. Start Learning With DQLab Now!

DQLab is ready to accompany you to learn Data Science in a structured and simple manner. For those of you who want a career as a Data Scientist do not worry, because you have the right opportunity to learn Data Science with DQLab.

Start studying with DQLab by signing up now at DQLab.id and enjoy a practical and applicable learning experience to get you ready to compete in the real industry. Happy learning DQLab!

So what else are you waiting for, let’s join DQLab! You can learn data science from scratch to join a large company. By joining now you can get a FREE module “Introduction to Data Science” loh!

By John Ricky & Annissa Widya | DQLab

Kuliah di Jakarta untuk jurusan program studi Informatika| Sistem Informasi | Teknik Komputer | Teknik Elektro | Teknik Fisika | Akuntansi | Manajemen| Komunikasi Strategis | Jurnalistik | Desain Komunikasi Visual | Film dan Animasi | Arsitektur | D3 Perhotelan | International Program, di Universitas Multimedia Nusantara. www.umn.ac.id