Programming for Data Science

R programming for the modern-day data scientist

Programming for Data Science Badge

Ad-Hoc Course Registration:

  • Time: 18.30 – 21.30
  • Venue: Menara Kadin Lantai 4, Jl. H. Rasuna Said, Jakarta Selatan
  • Time: 18.30 – 21.30
  • Venue: Google Classroom

Course details :

Programming for Data Science is a course that covers the important programming paradigms and tools used by data analysts and data scientists today. You will be guided through a series of coding exercises designed to maximize your familiarity with data science programming in RStudio, an integrated development environment for the statistical computing language R.

Upon completion of this workshop, you will be familiar with the programming language, popular tools, libraries (data science packages) and toolkits required to excel in your data analysis and statistical computing projects.


  • Data Science in R

    Day 1

  • Working with Data

    Day 1

  • Data Manipulation

    Day 2

  • Practical Data Cleansing

    Day 2

  • R in Practice

    Day 3

Course Producer

Samuel Chan

An  RStudio-certified instructor and machine learning practitioner in the field of marketing automation, fraud detection, finance and e-commerce.  Samuel is Indonesia’s top-ranked Stack Overflow user in R (top 5% worldwide) for three years running, and boasts certifications from RStudio, Microsoft, MongoDB, Neo4J Database, Stanford University, John Hopkins University, among others.

Prior to Algoritma, he has 8 years of working experience, including a stint as in-house consultant to several public-trading companies from his time staying in China, Japan and Singapore. He is today an active trainer and consultant for various companies in the financial industry. He has guest lectured in various campuses: Binus, NUS (National University of Singapore)’s The Logistics Institute, University of Indonesia, Universitas Gadjah Mada (UGM), Binus, Institute of Technology Bandung (ITB), Telkom University etc. Courses he authored are offered also in Singapore through Ngee Ann Polytechnic.

Samuel is also among the first recipients of Microsoft Professional Program Certificate in Data Science in Southeast Asia, having demonstrated proficiency in R, Python, Microsoft Azure, SQL / T-SQL, PowerBI and a list of other technologies, and among the first to be certified in RStudio’s program. Technical committee member and competition judge on Finhacks 2018, the largest Machine Learning competition of the year organized by PT. Bank Central Asia (BCA) and DailySocial.

3-Day Workshop Modules

Module 1: Data Science in R

Data Science in R

  • R Programming Basics
  • Why Learn R?
  • R Studio Interface
  • Data Structures in R

Working with Data

  • Reading & Extracting Data
  • Understanding Statistics
  • Exploratory Data Analytics

Data Manipulation

  • Working with Your Global Environment
  • Getting Familiar with Your Workspace
  • Continuous and Categorical Data

Module 2: Data Manipulation

Data Manipulation II

  • Vector Types and Classes
  • List and Objects
  • Matrix and Data Frames

Practical Data Cleansing

  • The Data Transformation Process
  • Reproducible Data Science Projects
  • Reading and Writing from Your IDE

R in Practice

  • Programming Exercise: e-Commerce Retail Datasets
  • In-depth Review of Data Frame Subsetting
  • Sampling and Randomization
  • Cross-Tabulations
  • Aggregations

Academy Modules

Graded Quiz

Working with R

  • R Scripts and Functions
  • R Markdown
  • Why Care About Reproducibility

Learning-by-Building Module (2 Points)

Writing your code as R scripts make up for automation and integration with other tools and services, while writing a R Markdown presents your findings and recommendations in a way that is friendly to non-technical / managerial team members.

  • R Script to clean & transform the data

Write a R script containing a function (name the function however way you want) that reads a dataset as input, perform the necessary transformation and export a cross-tabulation numeric result or plot as output.

  • Reproducible Data Science

Create an R Markdown file that combines your step-by-step data transformation code with some explanatory text. Add formatting styles and hierarchical structure using Markdown.

Workshop Receivables:

  • Workshop Lecturer’s Notes

    Including 2x Course Books (PDF), HTML files, course transcripts (if any).

  • Highly-accelerated Learning

    Learn under the assistance of mentorship of our lead instructor and a band of qualified teaching assistants throughout the 3 day course.

  • Certification of Completion

    Show current and prospective employers that you’ve completed the course with a signed certificate of completion.

  • Quality Learning Environment

    We pay meticulous attention to the logistical details of our workshops: quality audio and visual setups, comfortable sitting arrangements, small group size. Dinners are included for evening workshops.

  • Supplement Materials

    Receive supplement datasets to practice on, reference notes, working files (R Notebook or Jupyter Notebook), and other materials that will help you master the topics.


The Programming for Data Science workshop is designed for casual learners, working professionals and non-programmers that are taking their first steps into data science and machine learning.

Students are not assumed to have a working knowledge of R or prior proficiency in statistics / mathematics / algebra. At such the workshop follows a gentle learning curve and emphasize on hands-on, one-to-one tutoring from our team of instructors and teaching assistants.

Consider taking our Intermediate-level workshops instead for more advanced-level materials in statistical programming and machine learning.

Past Workshops in this Series:

Students work through tons of real-life examples using sample datasets donated by our team of mentors and corporate partners. We believe in a learn-by-building approach, and we employ instructors who are uncompromisingly passionate about your growth and education.

Data Science Specialization Badges

Part of the Data Visualization and Machine Learning Specialization Track

This workshop is part of the two specialization tracks offered by Algoritma Data Science Academy. Participants are rewarded with a certificate of completion upon passing criteria, and are encouraged to advance further in the respective data science specialization.