Intellij’s Trainings of the Month

This May we will have 3 events.

16 – 17 May 2016
The workshop breaks down the processes of becoming an iOS developer.
Level: Beginner to Intermediate.
Sign up at:


23 – 24 May 2016
The workshop breaks down the processes of becoming an Android developer.
Level: Beginner to Intermediate.
Sign up at:

28 – 29 May 2016.
OpenCV training using Python. Hands-on, practical exercises will be plenty.
9.00am to 6.00pm at Ovul Damansara.
Sign up at:

Grab your seats now!

Let’s change to world.

email: | call: 01126252058


Dimensionality Reduction on Github Event using PCA approach

This case study using Github Event dataset focus on Malaysia’s developers.

This is a read-only API to the GitHub events. These events power the various activity streams on the site.

github star wars

github star wars

The columns in this dataset are:

  1. a_login
  2. e_CommitCommentEvent
  3. e_CreateEvent
  4. e_DeleteEvent
  5. e_DeploymentEvent
  6. e_DeploymentStatusEvent
  7. e_DownloadEvent
  8. e_FollowEvent
  9. e_ForkEvent
  10. e_ForkApplyEvent
  11. e_GistEvent
  12. e_GollumEvent
  13. e_IssueCommentEvent
  14. e_IssuesEvent
  15. e_MemberEvent
  16. e_MembershipEvent
  17. e_PageBuildEvent
  18. e_PublicEvent
  19. e_PullRequestEvent
  20. e_PullRequestReviewCommentEvent
  21. e_PushEvent
  22. e_ReleaseEvent
  23. e_RepositoryEvent
  24. e_StatusEvent
  25. e_TeamAddEvent
  26. e_WatchEvent

Sample Github Event data.

sample Github Event data

sample Github Event data

Lower dimension representation of our data frame.

lower dimension representation of our data frame

lower dimension representation of our data frame

Explained variance ratio.

explained variance ratio

explained variance ratio

Plot on the data frame.

plot on the data frame

plot on the data frame

Re-scaled mean per a_login across all the events.

re-scaled mean per a_login across all the events

re-scaled mean per a_login across all the events

Bubble plot chart (a_login mean).

bubble plot chart (a_login mean)

bubble plot chart (a_login mean)

Bubble plot chart (a_login sum).

bubble plot chart (a_login sum)

bubble plot chart (a_login sum)

PyMathCamp aims to produce modern innovator through data science & mathematics

Innovative thinking and necessary skills set are critically crucial to solve real world problems. Approaching the future, problem will be getting more complex. Malaysia is in dire need of modern innovator to develop state-of-the-art solutions to solve them. And to develop solution, with just innovative thinking is not enough.

With lack of data science and mathematics talent, Malaysia is going to have tough time to have intellectual local resources to solve local problems.

Yes, it is true that Malaysia can outsource talents to foreign expertise but it is not right to be too dependent on them all the time. Even the dependency, the supply is still insufficient. Technology transfer can be very expensive and second, foreign workers shall be taking time to adapt with local structure before developing suitable solution. The more time taken, the more money out.

Malaysia is lacking of innovators.

study data scientist Malaysia

“Malaysia may not have enough engineers, architects, and other professionals, to achieve Vision 2020 based on the low level of interest by our students in science, technology, engineering, and mathematics (STEM). If the situation goes on, Malaysia may have to depend on foreign workers to attain developed status, warn expert.” Star Sunday.

Wawasan 2020 is getting nearer yet we are still incapable to show that we can ‘supply’ the vision.

Here we are, want to provide highly-impact education which focus on data science and mathematics, to ALL Malaysian for FREE so that, whole nation can change million of lives to be better.

Introducing to you, PyMathCamp.

PyMathCamp will be an online learning platform to teach data science and mathematics that make use of programming languages such as Python, C++ or R in preparation to produce future actionable Malaysian innovator to solve problems.

The online learning platform shall help them to learn how to code and further career in science, technology, engineering and mathematics (STEM). How?

How subjects of data science and mathematics can invent innovator?

Data science and mathematics are not “subjects in the class, stay in the class”. They are basic necessities to all kind of businesses; health, agriculture, finance, social sciences, maritime sciences, planetary sciences, meteorology, geography, and many more. You name it. STEM is WIDE. 

Data science in a simple word is a study of how to gather interesting data. And the interestingness of data shall depend on the searcher or data looker. Data is one oceanic word. However he/she may want to look for a matter that he/she is desired into, he/she must learn the science of pulling it from the ocean (of data), clean it, groom it and present it informatively.

Mathematics, on the other hand, is what makes life measurable to the basic thing like genomic. Mathematics demands wisdom, judgment and maturityWe can make error to find solution, we can alter our methods or start all over. When it comes to life, reality mostly doesn’t allow us to redo anything most of the time, but when it comes to ‘measurable condition’, we are allowed to attempt to change things.

By defining their importance in state-of-the-art programming, we shall have idea how both subjects are keys to economic prosperity. Without above talents, we will have difficulties to obtain interesting parameters. To obtain, data science and mathematics must be learnt.

Modern students of PyMathCamp should expect the following:

Student shall be able to create emphatic solutions. They shall be able to build advanced innovation through data science and mathematics and deliver curing values to others.

A variety of topics such as data exploration, visualization, feature engineering, predictive analytics, predictive modeling, clustering, big data pipelines, metrics and many more should be expected.

All trainers and mentors are experts, highly trained and well-experienced Malaysians. They are specialized in data science, computer vision, big data, machine learning, artificial intelligence and etc.

Students are also expected to find own solutions by leveraging our programming community portal and discussion group (chit chat). For open source development, PyMathCamp will be integrated with Github. 

We have evidential method to improve every of users’ learning curve to the finish line.

Note that PyMathCamp will only be committed to specific fields that are data science and mathematics.

There will be no age limit.

PyMathCamp will be focusing on Python, C++ or R because it’s beginner-friendly (easy to use and understand), math supported and mother tongue of Artificial Intelligence. Truly high in-demand skills set for sure.

And it is free. Yup. No charges.

Carpe diem.

Seize the day.

We want to build smart society to build smart structures.

We want to produce intelligent society. Malaysia needs smart society to help nation grow each other better to achieve Wawasan 2020 and further ages.

Other than fulfilling job vacancy, we aim that students shall be able to invent advanced solution and create intelligent startups to solve all society’s problems. This is our deepest aim actually. We want students to be modern innovator.

In simple word, PyMathCamp is really preparing Malaysians for the amazing (automated) future.

Join PyMathCamp.

IntelliJ is a deeply value-oriented company.

We want to educate and bring Malaysian mind to advanced level, starting from small, FOR FREE, which is the essence to change Malaysia into economically, a prosperous place.

We want to produce marketable Malaysians, in this self-serving economy, with highly-impact education as the first defense.

We pray that every mission of ours enrich all lives.

“Future is belongs to those who figure out how to collect and use data successfully.” 

Muhammad Nurdin, CEO of IntelliJ.


OpenCV training using Python

Introduction to Computer Vision for Robotics

Course Overview:

Computer vision is fast becoming a major component of a robotics system. With the capability to process and analyse visual data, the robot is able to ‘see’ and perceive its surrounding, thus completing tasks that are beyond imaginable limits of non-visual robots. Incorporating computer vision is the crucial next step in advancing your robotics systems.

This course will introduce the basic principles of computer vision, with emphasis on applications in robotics. The participants will learn the theories behind how computers capture 2D images and translate them into meaningful 3D information. Hands-on, practical exercises will be plenty, where participants will develop algorithms and control a mobile robot to perform tasks such as obstacle avoidance, ball tracking and target recognition, using no other sensors but a webcam.

Participants will be using the OpenCV library in the Python programming language. OpenCV is widely used in computer vision developments, as it hosts a large number of useful tools and algorithms. Python is the preferred language as it is easy to learn, and has great integration with OpenCV. This combination also has a world-wide supportive online community, providing contents, guidelines and tutorials for our advantage.



More details: