Call +60 3-2711 7241

HDRD Approved Training Provider in Malaysia - Learn New Skills to Enhance Your Employability from our HDRF Approved Courses

Python Machine Learning with Scikit Learn Training

This training aims to equip you with basic machine learning knowledge using Python scikit-learn package such as regression, classification, clustering, decision trees and neural networks. The topics include:

  • Linear regression
  • Create representations of documents and images that can be used in machine learning models
  • Discover hidden structures in data using clustering and PCA
  • Basics of Neural Network

 

HRDF SBL Claimable for Employers Registered with HRDF

HRDF claimable

Course Code: M268

Course Booking

MYR880.00

Course Date

Course Time

* Required Fields

Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.


Course Details

Module 1 Getting Started on Scikit-Learn

  • What is Machine Learning
  • Machine Learning Steps
  • What is Scikit-Learn
  • Installing Scikit-Learn

Module 2 Datasets

  • What is Dataset 
  • Iris Dataset
  • Handwritten Digits Dataset
  • Boston Housing Price Dataset
  • Splitting Datasets for Training/Testing

Module 3 Supervised Learning

  • What is Supervised Learning
  • Key Classifiers Algorithms - KNN, SVM, GNB, DT, Ensemble
  • Performance Metric and Errors
  • Model Persistence
  • Regression

Module 4 Unsupervised Learning

  • What is Unsupervised Learning
  • Key Clustering Algorithms - K-Means, Mean Shift, Agglomerative
  • Dimensionality Reduction - PCA

Module 5 Neural Network

  • What is Neural Network?
  • Multi Layer Perceptron Classifier
  • Hidden Layers
  • Activation Function
  • Solver
  • Learning Rate
  • Momentum

Who Should Attend

  • Data Scientists
  • Data Analysts
  • Financial Analysts
  • Digital Marketers

Prerequisite

Prerequisite

This is a intermediate level course. The following prerequisite is assumed

  • Basic Python

Software Requirement

Pls download and install the following software prior to the class

Trainers

Data Science TrainerDr. Aanand is a Full Stack Data Scientist who once had a torrid love affair with Physics. He has consulted and published in the area of Public Health, Electricity Markets, Telecom, BFSI, Advertising & Communication Strategies and Digital & Social Media Technologies. He has worked on assignments with international agencies such as International Monetary Fund, World Bank, Royal Netherland Embassy etc. besides MNCs like Tata Consultancy Services, Kie Square Consulting and several government organizations of national importance.

He regularly conducts general training programs in Python (Pandas, NumPy, SciPy, Matplotlib, Bokeh), R (dplyr, rstanarm, knitR, ggplot2), Data Visualization (Tableau, D3.js) and Machine Learnng (Reinforced Learning, Scikit Learn) and specialized training programs on Structural Equation Modeling and SAP Hana.

He holds a doctorate in Operations Research from Indian Institute of Management Ahmedabad and a post graduate in Physics from University of Mumbai. He has advanced training in mathematical programming including optimization, advanced multivariate data analysis, and simulation techniques. When he is not teaching or consulting he can be found meditating or heading for an adventurous trek.

Machine Learning TrainerAmir Othman is a software engineer by profession. Being educated in Bauhaus Universität Weimar and Hochschule Ulm, he brings experiences from different facades of the world.

With expertise in web technology, natural language processing and machine learning, he is a freelance data scientist. Some of his works include two international news aggregator

www.kronologimalaysia.com and www.diezeitachse.de

He also holds an impressive portfolio for data visualizations, primarily focusing on web based techniques.

Python TrainerSaeid Alizadeh is a technopreneur specialized in field of IOT (Internet of things), Building Management System (BMS), Building Automation System (BAS), Automotive Hydroponics Systems, and generally sense, monitor and control mechanical and electrical equipment such as ventilation, lighting, power systems, fire systems, and security systems.

Saeid’s past experience on IoT application include:

  1. Smart Building System
  2. Energy Monitoring, Controlling and Saving
  3. Environmental Monitoring 
  4. Flood detection and prediction system based on IoT and big data 
  5. Online Weather Station Based on IoT
  6. Smart Farming System (Long Range Wireless Sensor Networks)
  7. Smart Hydroponic System Based on IoT
  8. IP TV and Digital Signage System
  9. RFID Solution 
  10. GPS Tracking System
  11. Remote Sensing

Basic Tableau Trainer Ghazaleh Babanejad has received her Ph.D from University Putra Malaysia in Faculty of Computer ‎Science and Information Technology. She is working on recommender systems in the ‎field of skyline queries over Dynamic and Incomplete databases for her PhD thesis. She is also working ‎on Data Science field as a trainer and Data Scientist. She worked on Machine Learning and Process ‎Mining projects. She also has several international certificates in Practical Machine Learning (John ‎Hopkins University) Mining Massive Datasets (Stanford University), Process Mining (Eindhoven ‎University), Hadoop (University of San Diego), MongoDB for DBAs (MongoDB Inc) and some other ‎certificates. She has more than 5 years of experience as a lecturer and database administrator.

Anas Arram has over 5 years of experience in Data mining and optimization with a strong computing science in machine learning, data mining, combinatorial optimization problems and optimization algorithms. His areas of interest include: Operations Research, artificial intelligence and evolutionary computation, machine learning algorithm, text mining, combinatoric algorithms, database management, statistical analysis and data mining techniques.

MachineLearning TrSyed Muhammad Farrukh Akhtar has more than 15 years of experience analysis, designing, developing, integrating and managing large applications for diverse industries. He has experience working in Dubai, Pakistan, Germany and Malaysia, strong hands-on experience of software design, development and integration on different platform like IBM J2EE, Oracle and Microsoft .Net, Big data, Hadoop, Spark, HBase, Hive, Sqoop, Flume and NoSQL. He also has expertise in Machine Learning/ Deep Learning with Tensor Flow, Keras and Python, excellent skills in React, Ionic 2, Angular 2, Mobile Apps with React Native and Node.js.

He is highly knowledgeable in object oriented software development, requirements analysis, and database design. Possess deep understanding of Open Source technologies’ applicability in emerging business areas. He possesses excellent knowledge in Rational Unified Process (RUP); Rational Software Architect; data modeling and mapping; and extensible system design using the UML and Visio. Professional experience on J2EE, JMS, Web Sphere, Oracle, Spring, Hibernate, Struts and 3-Tier Web-based Applications Development.

TensorFlow TrainerDr. Nouar Dah is an experienced Lab Instructor at YPU. He has experience has a software engineer and senior hardware engineer. He has a PhD in Mechatronics Engineering from IIUM. He is well-versed in microcontrollers, FPGA, Matlab and VHDL.

Python Scikit TrainerJack Goh is a machine learning engineer at Coqnitics, Kuala Lumpur Malaysia. His job scope included research and development in computer vision recognition using ML/DL object detection and classification models. He has experience in using Django, PHP, CSS, HTML and JavaScript.

Customer Reviews (5)

Will RecommendReview by NORMALA BINTI CHE EEMBI @ JAMIL
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Nil (Posted on 3/13/2018)
Might RecommendReview by Jeffery Ng
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
I supposed it should be a 2 day course unless the participants are well versed in Machine Learning theory. Else the theory itself will take the whole day. Perhaps having the Titanic demo earlier will provides a better understanding. (Posted on 10/10/2017)
Will RecommendReview by Teh Kian Wooi
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
With related examples (Posted on 8/3/2017)
Will RecommendReview by Rache Lim
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
too short training duration, require a basic class for modeling understanding before attending the class (Posted on 8/3/2017)
Will recommendReview by stella
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
ensure to improve schedule management (Posted on 7/10/2016)

Write Your Own Review

You're reviewing: Python Machine Learning with Scikit Learn Training

How do you rate this product? *

  1 star 2 stars 3 stars 4 stars 5 stars
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
  • Reload captcha

Tags

Other people marked this product with these Subjects:

Use spaces to separate Subjects. Use single quotes (') for phrases.

You May Be Interested In These Courses