Raffel Ravionaldo
About Me
My name is Raffel Ravionaldo, I’m a fresh graduate from Bandung state polytechnic with a GPA of 3.55 in applied telecommunication. I’m interested in the data science world because with the right data, we can solve business problems in many ways, one of them with machine learning models that know about our data patterns.
To have knowledge about data I completed 2 data scientist boot camps and a deep learning course at coursera provided by Deepelearning.ai and Joined a virtual Project by rakamin and forage.com. From that activities, I gained skills to build a dashboard at Tableau and google looker, Write SQL queries at PostgreSQL and google big query, NoSQL at Google firebase and build machine learning/neural network models at jupyter lab.
For now, I learn about data science tools at AWS via a course at coursera provided by AWS and Deeplearning.ai.
Education
Politeknik Negeri Bandung
Bachelor's Degree in Telecommunication Engineering with GPA of 3.55
Binar Academy Bootcamp
The course of data science held by the Indonesian Ministry of Information and Communication cooperates with Binar Academy, selected as one of participants to take part in the G20 side event
Rakamin Academy
The course of data science and I graduated as most outstanding student
Work & Experience
Project Based Intern : Big Data Analytics Virtual Internship Experience
Kimia Farma
• Learning about data warehouse, SQL Querying, Data Analysis, and Google Looker Studio. • Responsible for making datamart from 3 tables using PostgreSQL. • Assigned to analyze sales data to be made into a dashboard using Google Looker Studio.
Project Based Intern : Data Science Virtual Internship Experience
Home Credit Indonesia
• Learning Microsoft Excel and SQL queries, theory related to big data, and preparation for creating machine learning models. • Assigned to analyze 307k rows of data to determine the right business steps so the number of loans received increases. • Responsible for creating a machine learning model to help the team determine whether customer loan applications will be accepted or rejected where the model has 96% accuracy.
Project Based Intern : Data Science Virtual Internship Experience
ID/X Partnership
• Learned about business acumen, data cleaning, explanatory data analysis, data visualization, and machine learning. • Assigned to create a model to accept or reject loan proposals from users using logistic regression. • Managed more than 400k entries of data to train and test the model
Computer vision engineer intern
kecilin
• Uses object detection algorithms (YOLOX and Yolonas) for some projects like vehicle counting, speed estimation and fire detection. • Created a new logic for speed estimation to improve the accuracy. • Build a Convolution Neural Network with Tensorflow library for color detection. • Responsible for creating a python program using OpenCV library to create motion detection, and convert video to images for labelling it to train an object detection algorithm.
