Revealed! The Secret to Success as a Data Scientist Without an IT Background (2024)

Revealed! The Secret to Success as a Data Scientist Without an IT Background (1)

Tangerang – Data Science marks a new era of promising career opportunities in various industries. The rapid development of information and communication technology is now inseparable from the important role of data, which is key to making every decision in a company. The demand for Data Science talent, predicted to continue to increase rapidly in the next few years, opens up brilliant career opportunities for individuals who want to enter the world of Data Science.

“Nowadays, a lot of decision-making is based on data; if there is data, we will be more confident when making decisions, especially when companies want to make decisions. In the past, maybe in our parents’ era, they considered the luck factor to be big, but nowadays, there is data that we can be more confident in,” Dharma said.

DQLab’s Free Class program was held again on Wednesday, April 17, 2024. This free introductory class program received tremendous enthusiasm from beginners interested in learning and working in the data field so that the implementation could reach Batch 33.

On this occasion, Dharma Setiawan, an experienced Data Scientist in various well-known companies who is also one of DQLab’s alumni, shared his experience and knowledge about the introduction to Data Science, opportunities in the data field, and career tips.

Dharma started the class by explaining that understanding Data Science must begin with understanding the problem. He also described the differences in each task between Data Scientist, Engineer, and Analyst.

According to him, the Data Science profession requires much knowledge and expertise. From math and statistics to programming, someone who wants to have a career in this field must be confident in their interests and abilities.

The goal is that every individual who wants to study in this field does not only pursue certificates when attending a training or boot camp because, according to him, mastery of skills is much more important.

Furthermore, he also shared knowledge related to the workflow of a Data Scientist. This workflow begins with understanding a strong business problem, starting with collecting and cleaning data and ending with processing it.

A Data Scientist must clean and reformat the data, especially when missing value data or a nonnormal distribution interferes with the modeling. The Data Scientist then hypothesizes and begins the Exploratory Data Analysis process by visualizing and validating the data. Finally, the ready data can be reported and deployed as material for making business decisions within a company.

“To be an advanced company, you must be able to analyze your company’s data well,” Dharma said.

In addition, Dharma explained that the Data Scientist profession is more focused on carrying out the data validation process and its distribution for reporting and deployment. For example, creating a dashboard for a Machine Learning Model so that when new data is entered, the dashboard can display an insight in real time to be displayed to the C-level or management of a company.

This shows that all flows in Data Science, in essence, produce valuable value as a basis for the decision-making process, so pursuing a profession as a Data Scientist requires many skills.

In addition to sharing knowledge about Data Science, Dharma shared his experience until he could reach his current career. Starting from his learning experience at DQLab when participating in the TETRIS Batch 1 program, up until he got an opportunity at BCA with a position as a Data Analyst thanks to the program’s help.

He was very grateful to have this opportunity because he could learn to run real projects in a supportive environment related to waiting time for service queues at BCA Bank.

In addition, he shared his experience as an assistant mentor and mentor in several boot camp live classes at DQLab. Dharma’s experience was conveyed through tips on choosing training classes that suit one’s talents and interests so as not to take the wrong steps in starting a career in the data field later.

Dharma also shared insights on the opportunity to become a Data Scientist in Indonesia, where entry-level positions offer a salary range of Rp5,000,000 to Rp8,000,000. He also offered tips for finding career opportunities in the data field through various trusted platforms such as LinkedIn, Glassdoor, and Glints.

Dharma also clearly illustrated career projections in the data field, starting from the position of intern, associate, staff, manager, VP, and director, so that participants in this activity could get a clear picture of where they should start their careers in the data field.

At the end of the opportunity, Dharma also took the time to conduct a mini hands-on session directly using the Data Science Fundamentals module, which can be accessed by redeeming the Free Class voucher. In this module, participants can try the learning experience using DQLab’s superior learning platform features, namely the Live Code Editor and Ask AI Chatbot.

Therefore, beginners who want to start a career in data, especially Data Scientists, can follow Dharma’s tips. They can also join training classes like the Machine Learning & AI for Beginner Bootcamp program.

The learning process in this program has been specifically designed by experts according to a comprehensive industry curriculum. In addition, the learning methods in this boot camp have also been proven effective in improving skills in the data field, even for beginners. For more information, please visit https://dqlab.id/bootcamp-machine-learning-and-ai-for-beginner!

By Lisya Zuliasyari | DQLab

English translation by Levina Chrestella Theodora

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

Revealed! The Secret to Success as a Data Scientist Without an IT Background (2024)
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