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Husein Zolkepli, Data Engineer, Omnilytics CO

Husein Zolkepli, one of Malaysia’s hidden gem in Data Science world! He will definitely wouldn’t admit himself as one, afterall humble is within his nature. A Python Developer (forever with it) and open source advocate. He unite people to make a
particular significant software product without any boundary and platform. He is also occasionally giving talks and tech classes related to data science, machine learning, deep learning, DevOps and Python.

Till today, Husein is a maintainer of Malaya, Bahasa Malaysia Natural-Language-Toolkit library, and mainly active in Github and Gitlab. Not forgetting a former Executive AI, used to develop Bahasa Malaysia parser to Chatbot, advanced face analysis (partially only), self-driving car prototype with SLAM and Computer Vision, deep learning interface for ROS.

Currently he is a data engineer for Omnilytics CO, responsible to handle more than 1 billion fashion and beauty products across the globe.

Among a few Data Science projects/experience;

  • Data Correlation visualization on the local government. http://www.huseinhouse.com/mampu/
  • Export and Import Malaysia analysis with real-time forecasting TF.jshttp://huseinhouse.com/tensorflow-js/matrade-v2/
  • Stock forecasting engine with big data correlation dashboard. http://huseinhouse.com/tensorflow-js/stock-forecasting-v2
  • Social network visualization for Trump circle based on news and searching influencer similarity.
  • Social network visualization for Najib Razak circle based on twitter and searching influencer similarity.
  • Tensorflow deep learning projects {CNN, RNN, Feedforward, GAN, Seq2Seq}.https://github.com/huseinzol05/Deep-Learning-Tensorflow
  • Malaya, Bahasa Malaysia NLP library for Python, powered using deep learning models. Supports POS,Entities
  • Recognition, Stemming, Normalizer, Topic Modelling and Semantic searching. https://github.com/DevconX/Malaya
  • (Hackathon Competition) Titanic: Machine Learning from Disaster (top 1%, 53rd of 8649)
  • Porto Seguro’s Safe Driver Prediction (top 8%, 284th of 3138)
  • and many more…


We couldn’t agree more that Python is gaining the popular and important in Data Science! Hence, in order to shape the nation’s Big Data journey, we will be organising a 2 days workshop on Data Science with Python and it will be conducted by Mr. Husein Zolkepli, Malaysia’s hidden gem talent who has successfully execute/create with more than 20 Data Science projects and counting! Google his name up to get amazed!

Session Topics (Day 1)

Refreshing Python programming language
Python language fundamentals, including basic syntax, data types, lists, dictionaries, sets, tuples.

Introduction to linear algebra library, Numpy, and vector programming
What is numpy and why linear algebra is very crucial for data science.

Introduction to dataframe library, Pandas
What is pandas and it offers data structures and operations for manipulating numerical tables and time series.

Pandas fast indexing and selecting data
We will focus on how to slice, dice, and generally get and set subsets of pandas objects.

Pandas groupby
We will focus on how to group a series using mapper (dict or key function, apply given function to group, return result as series) or by a series of columns.

Pandas time frame type manipulation
We will focus on how to use Pandas time series and dates functionality for time series dataset.

Pandas case study on Iris dataset
Basic indexing, groupby and simple visualization for exercises using Iris dataset.

Pandas grouping for aggregation, filtration and transformation
What is aggregation and how to aggregate using Pandas.

Introduction to maplotlib, seaborn and plotly
Introduction to famous graphic python libraries.

Simple matplotlib visualization
matplotlib 2D histograms / heat maps / levelplots, matplotlib 3D Plots, matplotlib Bar plots, matplotlib Line plots, matplotlib Scatter plots

Session Topics (Day 2)

Advanced matplotlib visualization
matplotlib Boxplots, matplotlib Clustering – Heatmaps and Dendrograms, matplotlib multi charts

Seaborn visualization with Iris dataset
Storytelling with Kernel density plot, distribution plot, boxplot, violinplot, swarmplot, and pairplot.

Some exercises with Pokemon dataset
Participant should reimplement back what we done previous hours.

Basic statistics
What is mean, standard deviation, variance, min, max, mode, median and percentiles.

Covariance and correlation
What is covariance and what can learn from it. Why we need to understand correlation.

Probability mass and density functions
What is probability, binomial distribution, normal distribution, Binomial Probability Mass Function, Binomial Cumulative Distribution Function, and Poisson Distribution.

Least-square linear regression
fit slope and intercept so that the linear regression fit and minimizes the sum of the residuals (vertical offsets or distances).

Who should attend

This professional training is designed for Technical Professionals as below:

  • CTO
  • CIO
  • Data Scientist
  • Data Engineer
  • Data Analyst
  • Big Data Department Staff
  • Big Data Project Lead
  • Solution Architect
  • Big Data Executive
  • Software Engineer

From various local and global organizations. 

Key takeaways

This course is a great introduction to data science using Python. By the end, you’ll be familiar with common data science practices and how to solve it using Python.

This is a pre-requisite workshop, students, with at least Programming or coding skills required.

sign up here!

Penang Edition ( 12-13 January 2019)

Kuala Lumpur Edition ( 23-24January 2019)


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BIGIT CAMPUS’ workshops are niche, exclusive and tailored according to market needs of the host city and address the evolving nature of technological advancement.

Incorporating both quality and quantity into our shows, some attendees have described us to have “a great balance between business networking and knowledge sharing”. Thus, we strive to Build Intelligence Globally in Technology and that makes us truly unique.

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