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Data Wrangling and Visualization with R 11/2024.

Ngày diễn ra: 26/04/2025

After six successful editions, Data Wrangling and Visualization with R remains one of the most popular courses among our students. This November, CASED is pleased to officially announce the opening of enrollment for Data Wrangling and Visualization with R – November 2024.

The course aims to equip learners with the skills to collect, process, analyze, and visualize data using the R tool. By the end of the course, students will be able to apply R to data processing tasks and create high-quality charts and graphs for reporting purposes.

Benefit

– Review foundational knowledge in statistics, econometrics, and data analysis
– Develop skills in collecting, organizing, processing, analyzing, and visualizing data using R
– Practice on your own project with guidance from the instructor

Đối tượng tuyển sinh

Students, lecturers, and researchers in the fields of healthcare, economics, finance, and social sciences

Project officers, economic analysts, financial analysts, business analysts, and related professionals

Those who need to use R for data analysis

Course Details

🔸Course content: https://rpubs.com/chidungkt/1224950

🔸Instructor: Nguyễn Chí Dũng, Data Scientist at Funtap Vietnam, author of Applied Econometrics with R, with over 10 years of experience in the Data Science field.

🔸 Approach: Focused on hands-on practice through case studies using real-world datasets. In addition, after each session, there will be a small tea break to encourage discussion and networking between students and the instructor.

🔸 Target audience:

  • Students, lecturers, and researchers in healthcare, economics, finance, and social sciences

  • Project officers, economic analysts, financial analysts, business analysts, and related professionals

  • PhD candidates and researchers in economics, healthcare, finance, and social sciences

  • Anyone who needs to use R for data analysis

🔸 Course schedule: 4 sessions

  • November 3, 2024 (Sunday)

  • November 10, 2024 (Sunday)

  • November 17, 2024 (Sunday)

  • November 24, 2024 (Sunday)

🔸 Class time: 8:30 AM – 12:30 PM (morning session); 1:30 PM – 5:30 PM (afternoon session)

🔸 Mode of study: In-person in Hanoi (DEPOCEN Office – 7A Tôn Thất Thiệp, Cửa Đông, Hoàn Kiếm, Hanoi) with a limited number of seats available for online attendance via Zoom.

🔸 Tuition fee: 4,000,000 VND. Payment is made via bank transfer (details will be provided to students along with the registration confirmation email).

🔸 Tuition discounts:

  • 5% discount for those who register and complete payment before October 18, 2024

  • 5% discount for group registrations of three or more participants

  • 10% discount for group registrations of three or more participants who complete payment before October 18, 2024

  • 10% discount for students referred by CASED alumni who complete payment before October 18, 2024

  • 10% discount for CASED alumni

Cảm nhận của học viên

Trần Đạt Tín – Học viên lớp Data Wrangling and Visualization with R 11/2021

I feel that the course provided me with a strong foundational knowledge to continue self-studying data processing and visualization in the future. As a mathematics student, the course has been very helpful for my studies in statistics and probability. In particular, the instructor provided excellent resources and materials for further self-learning after the course.

Trần Hải Anh – Học viên lớp Data Wrangling and Visualization with R 05/2020

The Data Wrangling & Visualization with R course helped me build a solid foundation in data processing and visualization. The datasets used in class were very practical and relevant to current issues. The instructor was also extremely dedicated, supporting us not only during the course but also with our individual projects afterward.

Nguyễn Quốc Đạt – Học viên lớp Data Wrangling and Visualization with R 08/2019

The course helped me develop a data-driven mindset, enabling me to manage, process, and explore datasets using R. It was very suitable for beginners like me, helping me understand key ideas behind data usage and providing a solid foundation for further self-study.

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