Date :

29 September 2019 (Saturday)

Time :

08:00am - 06:00pm

Venue :

Malaysian Global Innovation & Creativity Centre (MaGIC), Cyberjaya.
[ Location ]

Agenda

08:00am

Registration

09:00am

Briefing

09:30am

Meetups session (Part 1)

12:30pm

Rest and Networking

02:30pm

Meetups session (Part 2)

06:00pm

End

Computer Vision Application for Self-Driving Cars

Trainer's Name :

Husein Zolkepli

About :

Husein knows Data Science, Machine learning, Deep learning, Serverless and Up-scaling architectures, DevOps, Low-level language integration, front-end and cook plain & fried rice. Now working as Data Engineer at Omnilytics CO. 

https://github.com/huseinzol05
https://github.com/devconx

Session's outline

1. Explain 1D and 2D convolution process.
2. Explain math required.
3. Code straight lanes detection.
4. Code curve lanes detection.
5. Try to cover pretty much this repository as we could [https://github.com/huseinzol05/Self-Driving-Cars-Engine]

Prerequisites

1. Understand Python syntax.
2. Github account for Devcon Jupyterhub Server authentication.
3. Took Additional Mathematics on high school or Mathematics during Diploma / O-level / Foundation. 

Getting Started with ReactNative And Expo

Trainer's Name :

Hijazi [iReka Soft]

About :

iOS developer for almost 8 years with Objective-C and Swift, have been published more than 30 apps on the App Store. Also have been involving with Android and Laravel development as well. Now involving with app's UI/UX planning & designing, and also React Native development.

Session's outline

1. How to setup React Native environment.
2. Your ‘Hello World’ React Native project.
3. Know about component, learn from React Native documentation.
4. Using react-native navigation.
5. Testing on device. 

Prerequisites

1. Mac or PC
2. Node JS
3. react-native CLI
4. yarn
5. Expo [https://expo.io/tools]
6. Visual Studio Code [https://code.visualstudio.com/download] 
7. Android Studio or Xcode

Machine Learning for Fintech: From Concepts to Deployment

Trainer's Name :

Faris Hassan [Farisology]

About :

Artificial Intelligence devotee meditating by orchestrating Machine intelligence. John Connor of humanity in the coming Ai Apocalypse.

Session's outline

1. Age of Ai
2. The concept of learning
3. Types of learning
4. Machine learning workflow
5. Preprocessing
6. Features engineering and selection
7. Modeling
8. Model evaluation
9. Optimization
10. Deployment

Prerequisites

1. If you like to use Collab you can skip all the that follows.
[https://colab.research.google.com/notebooks/welcome.ipynb]

or

1. Python Anaconda 3 (follow the steps from here installation)
2. Make sure you Flask installed.
3. If you have any problem with installation please ask in the DevCon telegram group 

Raspberry Pi Learn Together

Trainer's Name :

Syamsi

About :

A dedicated and passionate engineer who love in tinkering electronics stuff and sharing his skill and knowledge.

Session's outline

1. Getting started with Raspberry Pi (install, transferring file, etc)
2. Window 10 + bash on ubuntu + vscode + rmate = remote coding your raspberry pi
3. Linux basic command
4. Basic physical computing using python
5. Getting started with node-red: interact with open weather API 

Prerequisites

Hardware:
1. Raspberry Pi (including SD card! and reader)
2. Breadboard
3. DHT11
4. Breadboard
5. Jumper

Software:
1. Vscode [https://code.visualstudio.com/download]
2. Bash on Ubuntu [http://wsl-guide.org/en/latest/installation.html]
3. Node-RED [https://nodered.org/docs/hardware/raspberrypi]
4. FileZilla [https://filezilla-project.org/download.php?show_all=1]
5. Putty [https://www.chiark.greenend.org.uk/~sgtatham/putty/latest.html]

Data Processing and Visualization Using PHP

Trainer's Name :

Tikus Melompat

About :

A dedicated and passionate developer who love in sharing his skill and knowledge.

Session's outline

1. How to read the data from file.
2.Extract the data from file to database.
3. Design the database structure.
4. Solve a problem regarding to how to display the data from dataset.

UI / UX Design for Mobile

Trainer(#1)'s Name :

Nurhayani [Miss Lipas]

About :

Graduated in graphic designer & visual communication,
love in sharing skill & teaching what I know.

Trainer(#2)'s Name :

Ama

About :

Graduated in Software Engineering ,  Currently noob game dev :). Still learning

Session's outline

This course teaches how information obtained from the client, sales, and marketing to design and develop compelling visual experience for multiple platforms, including mobile, tablet, and desktop. You will learn more about wireframes, color schemes, tones, design templates, formatting, and typography. This course builds upon your abilities to implement user analysis techniques, usability concepts, usability testing procedures and the vital role of testing to publish and maintain a Web site.

Prerequisites

1. Know about Adobe Illustrator & Photoshop (beginner)
2. Download Adobe XD [https://www.adobe.com/sea/products/xd.html]
3. Bring your own laptop

Web Scraping and Sentiment Analysis

Trainer's Name :

Irfan Noordin

About :

Originally graduated in Mechanical Engineering, made the shift to Data Science. Currently a Junior Data Scientist in BTM Blockchain Technology (M). Looking forward to learn myself while teaching what I know.

Session's outline

1. Reading data from csv file
2. Explanation of Naive Bayes Algorithm
3. Code Sentiment Analysis using Naive Bayes Algorithm
4. Web scraping
5. Extracting data from website
6. Reading basic html tags 

Prerequisites

1. Basic knowledge of Math and Statistics
2. Python Anaconda 3 (follow the steps from here installation)
3. Download ImDB Reviews Dataset
[https://drive.google.com/open?id=1vQ80JUl3KbbrBfWm52UuALjQ1AlmcE2X] 

PyTorch On Natural Language Processing

Trainer's Name :

Abdul Rahim Bin Tahir

About :

Graduate Electronic Engineering and currently work as Software Developer. Pytorch is new to me and I passion to teach while I learn to master it.

Session's outline

1. Basic Introduction to Natural Language Processing
2. Introduction to Pytorch
3. Natural Language Processing using Pytorch
4. Working on project using NLP with Pytorch 

Prerequisites

1. If you like to use Collab you can skip all the that follows.
2. Python Anaconda 3 (follow the steps from here installation)