Regression Models

An in-depth look at regression models

Ad-Hoc Course Registration:

  • Date: 4 – 7 January 2021
  • Time: 18.30 – 21.30
  • Venue: Menara Kadin Lantai 4, Jl. H. Rasuna Said, Jakarta Selatan
  • Investment: Rp. 5.200.000

  • Date: 4 – 7 January 2021
  • Time: 18.30 – 21.30
  • Investment: Rp. 2.600.000


Course details :

This course strives for a fine balance between business applications and mathematical rigor in its treatment to regression models, one of the most essential statistical techniques in the field of machine learning. Its aim is to equip you with the knowledge to investigate relationships between variables of a data effectively and rigorously.

We strongly recommend that you complete Practical Statistics prior to taking this course. Upon completion of this workshop, you will acquire a rigorous statistical understanding of machine learning models, allowing you to extrapolate the same ideas into other, more advanced machine learning models.


  • OLS Regression

    Day 1

  • Linear Models in R

    Day 1

  • Interpreting Linear Models

    Day 2

  • Multiple Regression

    Day 3

  • Dive Deeper: Regression Models

    Day 3

  • Learn-by-Building

    Day 4

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.

4-Day Workshop Modules

Syllabus: Regression Models

Module 1: Regression Models I

OLS Regression

  • Understanding Least Squares
  • Simple Linear Regression

Linear Models in R

  • Understanding Coefficients
  • Plotting Regression
  • Model Construction

Interpreting Linear Models

  • Residuals Manually
  • Coefficients Manually
  • R-Squared Manually

Module 2: Regression Models II

Interpreting Linear Models

  • Estimates and Standard Errors
  • t-Value and p-Value
  • Adjusted R-Squared

Multiple Regression

  • Multicollinearity and VIF
  • Model Assumptions
  • Bias-Variance Trade-off
  • Outliers: Leverage and Influence
  • Model Limitation and Evaluation

Dive Deeper: Regression Models

  • Model Selection and Specification
  • Step-wise Regression
  • All-possible Regressions
  • Residual Plots
  • Model Diagnostics
  • Limitations of Regression Models

Academy Modules

Graded Quiz

Learning-by-Building Module (3 Points)

Recommendation on Lowering Crime Rates

  • Write a regression analysis report applying what you’ve learned in the workshop. Using the dataset provided by you, write your findings on the different socioeconomic variables most highly correlated to crime rates.

    Explain your recommendations where appropriate.

Ad-Hoc Course Registration:

  • Date: 4 – 7 January 2021
  • Time: 18.30 – 21.30
  • Venue: Menara Kadin Lantai 4, Jl. H. Rasuna Said, Jakarta Selatan
  • Investment: Rp. 5.200.000

  • Date: 4 – 7 January 2021
  • Time: 18.30 – 21.30
  • Investment: Rp. 2.600.000


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 4-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.

This workshop is recommended for:

The Regression Models workshop is an intermediate-level programming workshop best suited to R programmers that are taking their first steps into data science and data visualization.

Students are assumed to have a working knowledge of R and have completed the necessary pre-requisites. Consider taking the pre-requisite course or a beginner-level course instead if you have no prior programming experience or statistics knowledge.

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.

Part of the Machine Learning Specialization

This workshop is part of the Machine Learning Specialization 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.