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February 24, 2022

Python Fundamentals: The First Steps to Learning Data Science

Published by umnadmin on February 24, 2022
Categories
  • DQLab EN
  • General EN
  • News
Tags
  • artikel dqlab
  • dqlab
  • dqlab umn
  • webinar DQLab

(dok. DQLab)

(dok. DQLab)

TANGERANG – To proceed to a higher stage, it is necessary to have a strong foundation on the basics. Most people who learn data science will learn about python too. On Friday (26/11/21), DQLab held another Mini Bootcamp and a Closing Live Session Bootcamp virtually. DQLab collaborated with Kadareka Batch 2A, presenting Python Fundamentals for Data Science. The materials were thoroughly dissected by Putu Rika, a Data Scientist at BISA AI Academy.

Python is a programming language intended for general-purpose programs, and it belongs to the category of high-level programming languages. According to Putu, beginners new to the data science programming language can start by learning Python because it is easier to read and write Python. Putu provides a comparison between Python, C++, and Javascript. In writing, Python is simpler than C++ and Javascript.

“We have to strengthen the fundamentals first, so that in the future it will be more comfortable when coding,” Putu said.

Not just for data science, Python can also be used for web development, software development, etc. From year to year, Python gained popularity in language programming. As data practitioners, several libraries are needed in the data processing process, namely Pandas, Matplotlib, and NumPy. Other alternative coding environments, like Colab and Jupyter, can also be used.

Also read Pengenalan Data Science dalam Transformasi Digital

“Most companies use Python,†Putu said.

Putu also shared that when starting a career in data science, actively use LinkedIn. According to her, actively posting something can show a person’s competence in their field, allowing them to find jobs easier. The ‘like’ feature in LinkedIn also helps share the post, allowing people to reach more companies.

“Using data science as an example, you can create a post when you join webinars or boot camps on data science. Just like right now, as we are in a webinar talking about data science, if you have an assignment regarding this webinar, you can share it in your LinkedIn accounts. Showing people that you joined a training and have skills related to data,†Putu said.

It is recommended to conduct more projects on data science in DQLab to help you stand out from other candidates when looking for a job on LinkedIn.

During the closing session of this Boot camp, Putu also dissected the DQLab Python Fundamental module for data science which can be accessed through this link:

https://dqlab.id/yuk-kenalan-dengan-data-science

*by 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

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