Introduction to Machine Learning I

Unlock the full potential of machine learning with our comprehensive 5-module course!

  • Python, SQL
  • Pre-Requisite: SQL Query & Capstone Project
  • Difficulty: Beginner
  • Duration: 4 Days

Course details

Unlock the full potential of machine learning with our comprehensive 5-module course! From mastering data representation and exploratory analysis to implementing support vector machines (SVM) in both classification and regression, you’ll gain the essential skills needed to excel in the field. Learn to handle numerical and categorical data, train-test splitting, and optimize SVM hyperparameters to achieve optimal results. By the end of this course, you’ll be equipped with the knowledge and tools to confidently tackle real-world machine learning problems!

Please bring along:

  • 1x Laptop
  • Purchased Ticket


  • Basic Principles of Machine Learning

    Day 1

  • Data Preprocessing

    Day 2

  • Train-test Splitting

    Day 2

  • Implementation SVM

    Day 3

  • Model Improvement Technique

    Day 4

Course Producer

Samuel Chan

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), a certified professional (certificates from Microsoft, MongoDB, Stanford University, John Hopkins University), and an experienced consultant that has worked with several public-trading companies from his time staying in China, Japan and Singapore.

Between 2017 and 2018, Samuel has trained and consulted with more than 20 companies around Indonesia and a regular guest speaker/trainer in a number of universities in Singapore and Indonesia. He 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.

4-Day Workshop Modules

Syllabus: Introduction to Machine Learning I

Module 1: Basic Principles of Machine Learning

  • What is data, types of data, component of data ML
  • Representation of data in the Scikit-learn
  • Why machine learning?
  • Load data & exploratory data analysis

Module 2: Data Preprocessing

  • Handling numerical data
  • Handling categorical data

Module 3: Train-test Splitting

  • Why train-test splitting?
  • How to train-test splitting

Module 4: Implementation SVM

  • Introduction to Support Vector Machine (SVM)
  • SVM in classification
  • SVM in regression

Module 5: Model Improvement Technique

  • Model evaluation
  • Hyperparameters SVM

Program Receivables:

  • Cutting Edge Curriculum

    A hands-on coding bootcamp with the opportunity to work on real datasets donated by businesses and the public sector. Coursebooks (PDF/HTML files), data set for practice, reference notes, and working files (R Notebook or Jupyter Notebook) are accessible through our Learning Management System account.

  • Project-Oriented Learning

    Work with real-life cases and learn under the assistance of our qualified instructors throughout the 1-month 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.

  • Engaging Community

    Be a part of our data-passionate community with 5000+ members and 300+ alumni.

A structured approach to learning data analysis

The Data Analytics Specialization is a 4-week bundle that is curated to accelerate a student’s mastery in building data products, develop a web application, and data visualization.

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

Learn data analysis by building:

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 Data Analytics Specialization

This course is part of the Algoritma Data Analytics Specialization. Participants are rewarded with a certificate of completion upon passing criteria.