Introduction to AI

for

Computer Vision

An introductory course to computer vision in Python

Introduction to AI for Computer Vision

An introductory course to computer vision in Python

Saturday, 4 January 2020
13.00 – 16.00
Citywalk Sudirman
2nd Floor, Kantorkuu Coworking Space.

Jl. KH Mas Mansyur Kav 121. Jakarta Pusat.
IDR 100,000
Kickstart session, Online Quiz Portal, all materials in digital PDF / HTML

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Course Summary

The workshop that accompanies this course will also demonstrate:

Object recognition and classification
Code Solution: Belitung Map Restoration (assignment 1)
Code Solution: Lego Brick object counter (assignment 2)
Live coding a video capturing tool
Live coding a lego-bricks counter (counting lego bricks from raw images)

The intended audience for this course and accompanying workshop are absolute beginners who have an interest in computer vision and the application of artificial intelligence in modern day CV libraries. Some familiarity in Python and / or geometry will be helpful but is not required as the instructor assumes no prior math / programming knowledge for all workshops in the Kickstart series.

All materials will be provided in HTML, PDF, Python Scripts format.

A follow-up classroom-based workshop is planned for January where students sharpen their skills in computer vision and python. A free online quiz would be available at the end of the workshop, available for participants to put their knowledge to test and earn a badge.

Syllabus

An introductory course to computer vision, with the following emphasis:

1.5 hour: Ground-up principles
- Trigonometry
- Image Transformation
- Thresholding Algorithms
- Architectural introduction to Convolutional Neural Networks (CNN)

45-minute: Diving into opencv and python
15-minute: Code Solution to Belitung Map Restoration (assignment 1) and Lego Brick object counter (assignment 2)
30-minute: Q&A

The workshop will be delivered in English.

Q&A Sessions will be in English and Bahasa Indonesia.

Course Preview

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Instructor

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.

Workshop Receivables:

Workshop Lecturer’s Notes
Including an e-course book (PDF) and/or HTML files.
Highly-accelerated Learning
Learn under the assistance of mentorship of our lead instructor.
Quality Learning Environment
We pay meticulous attention to the logistical details of our workshops: quality audio and visual setups, comfortable sitting arrangements. Snacks are included for evening workshops.

Kickstart Series

Workshops in our Kickstart series are tailored to casual programmers and non-programmers that are taking their first steps into data science. It assumes no prior knowledge or academic background, and attendees will be introduced to the beautiful art of writing R / Python code to produce data visualization, build machine learning models and solving modern day problems using mathematically-sound principles.

Students are encouraged to download the course materials beforehand if they wish to follow along with the Code Along exercises.

The workshop has a gentle learning slope that is designed with non-technical professionals and academics in mind.