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15 Courses

MODULE 3: Micro Award Machine Learning in Data Exploration
Fakulti Kejuruteraan dan Alam Bina
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Teacher: Dr. Nur Arzilah Ismail

MODULE 3: Micro Award Machine Learning in Data Exploration

Module Info


Course Name
:MCKK56073 Micro-credential Engineering Statistics
Module Title:Module 3: Micro Award Machine Learning in Data Exploration
Module Code:MCKK56091 
Credit Hours:1
Learning Mode
:Online, Physical, Self Learning
Language
:English
Entry Requirement:Minimum SPM pass/equivalent with 3 years of work experience in related field 

Or; 

With 5 years of experience in related field.

Registration Date: 
Module Synopsis:This module provides an introduction to machine learning and its applications in data exploration. Topics covered include basic statistical analysis, data visualization, and machine learning algorithms for pattern recognition and predictive modeling. Learners will apply machine learning techniques to extract insights from data, enhancing their analytical skills for engineering and industrial applications.
Module Learning Outcomes:
MLO 1Analyse data in machine learning using statistical programming.
MLO 2Apply statistical programming in the industry.
Fee: 
Lecturer's Name:
  1. Dr. Nur Arzilah Ismail
  2. Dr. Anies Faziehan Zakaria
  3. Dr. Muhamad Alias Md. Jedi


  • 11
  • 7
Python Programming for Machine Learning
Fakulti Kejuruteraan dan Alam Bina
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Fakulti Kejuruteraan dan Alam Bina

Python Programming for Machine Learning

Module Info


Course Name
 :Machine Learning
Module Title : Python Programming for Machine Learning
Module Code : MCKK52011
Credit Hours : 1
Learning Mode
 :  Hybrid
Language
 :  English
Entry Requirement : SPM with a minimum of 5 years of work experience in a related field
Registration Date :  
Module Synopsis : This module introduces participants to the basic concepts of Python programming required for developing machine learning applications. The module covers 1) Python Basics - cover data types, variables, and control loops, 2) Functions and Data Structures - explore creating functions and using lists, dictionaries, etc., 3) Numpy - a powerful numerical library for scientific computing, 4) Project-Based Learning - embrace  to apply skills through real-world projects.
Module Learning Outcomes :
MLO 1 Apply data structures and various Python libraries according to data types.
MLO 2 Produce effective Python programs to solve problems related to data preparation for machine learning.
Fee :  
Lecturer's Name :  Dr. Mohd Faisal Ibrahim / Dr. Seri Mastura Mustaza / Dr. Aqilah Baseri Huddin / Assoc. Prof. Dr. Mohd Asyraf Zulkifley




  • 17
  • 6
MODULE 2: Micro Award Basic Linear Regression in Quality Control
Fakulti Kejuruteraan dan Alam Bina
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Teacher: Dr. Nuryazmin Ahmat ZainuriTeacher: Dr. Nur Arzilah IsmailTeacher: Dr. Mohd. Haniff Osman

MODULE 2: Micro Award Basic Linear Regression in Quality Control

Module Info


Course Name
:MCKK56073 Micro-credential Engineering Statistics
Module Title:Module 2: Micro Award Basic Linear Regression in Quality Control
Module Code:MCKK56081
Credit Hours:1
Learning Mode
:Online, Physical, Self Learning
Language
:English
Entry Requirement:Minimum SPM pass/equivalent with 3 years of work experience in related field 

Or; 

With 5 years of experience in related field.


Registration Date: 
Module Synopsis:This module focuses on linear regression techniques and their applications in quality control and process optimization. Key topics include least squares estimation, correlation analysis, hypothesis testing, and control charts (X, R & S charts). Learners will gain hands-on experience in statistical modeling to monitor and improve product and process quality in various industries.
Module Learning Outcomes:
MLO 1

Analyse data through linear regression in real life.

MLO 2Evaluate suitable Statistical Quality Control methods in the industry.
Fee: 
Lecturer's Name:
  1. Dr. Nur Arzilah Ismail
  2. Dr. Mohd Haniff Osman
  3. Dr. Nuryazmin Ahmat Zainuri


  • 14
  • 8
Unsupervised Machine Learning
Fakulti Kejuruteraan dan Alam Bina
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Fakulti Kejuruteraan dan Alam Bina

Unsupervised Machine Learning

Module Info


Course Name
 :Machine Learning
Module Title :  Unsupervised Machine Learning
Module Code : MCKK52031
Credit Hours : 1
Learning Mode
 :  Hybrid
Language
 :  English
Entry Requirement :  At least passed SPM or equivalent with a minimum of 5 years of working experience in the related fields.
Registration Date :  -
Module Synopsis : This module aims to provide knowledge and understanding of unsupervised machine learning methods. The module starts with a general understanding of an unsupervised learning methodology focusing on clustering algorithms. Two unsupervised clustering algorithms will be taught in this module, which are hierarchical and K-means clustering algorithms. This module will delve into the basic theory of the selected clustering algorithms and also their pseudocode.
Module Learning Outcomes :
MLO 1 Ability to suggest unsupervised learning algorithms for engineering applications.
MLO 2 Ability to evaluate the effectiveness of the machine learning algorithms.
Fee :  
Lecturer's Name :  Dr. Mohd Asyraf Zulkifley




  • 17
  • 5
Application of Spectroscopy and Chromatography for Environmental Analysis
Fakulti Kejuruteraan dan Alam Bina
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Fakulti Kejuruteraan dan Alam Bina

Application of Spectroscopy and Chromatography for Environmental Analysis

Module Info


Course Name
 : Chemical Instrumentation Method
Module Title :  Application of Spectroscopy and Chromatography for Environmental Analysis
Module Code : MC-CECIM3
Credit Hours : 1 credit hour
Learning Mode
 :  Physical 
Language
 :  English & Malay
Entry Requirement :  
Registration Date :  
Module Synopsis : This module introduces students to the basic concepts of Marketing, the importance of strategic planning and elements in the marketing environment.
Module Learning Outcomes :

HPM3: Understand the basic operation of equipment and chemical instrumentation components found in the laboratory.

Memahami operasi asas peralatan dan komponen instrumentasi kimia yang terdapat dalam makmal. 

 

HPM4:Interpreting data obtained from analytical equipment.

 Mentafsir dan membuat laporan daripada data yang diperolehi daripada peralatan analisis.


HPM5:Determining chemical structures, performing concentration and purity and implementing quality assurance in chemical measurements. 

Menentukan struktur kimia, melakukan pengukuran kepekatan dan ketulenan serta melaksana jaminan kualiti dalam pengukuran kimia. 
Fee :  
Lecturer's Name :  ChM. Dr. Noorashikin Md Saleh & PM Ts. Dr. Wan Nor Roslam Wan Isahak




  • 22
  • 7
Introduction to Automation Systems
Fakulti Kejuruteraan dan Alam Bina
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Teacher: Prof. Madya Ir. Dr. Rizauddin Ramli

Introduction to Automation Systems

Module Info


Course Name
 : Micro-Credential Manufacturing Automation
Module Title :  Introduction to Automation Systems
Module Code : MCKK54011
Credit Hours : 1
Learning Mode
 :  Online 
Language
 :  English
Entry Requirement : Minimum pass SPM/equivalent with 3 years of experience in the related areas

or;

With 5 years of experience in related areas.
Registration Date :  
Module Synopsis :

This module introduces students to the basic concepts of automated machines and equipment, functions and applications of robots in industrial automation systems. This course discusses the theory and concepts of automation which related to systems in manufacturing industry.
     
Module Learning Outcomes :
MLO 1 Explain the concept of automation systems and industrial robot principles and its components.
MLO 2 Describe industrial robot configurations and Denavit Harternberg algorithms
Fee :
Lecturer's Name :  Associate Prof Ir  Dr Rizauddin Ramli(coordinator)
Dr Afifah Zakiyyah Juri
Dr Hawa Hisahmuddin

  • 17
  • 8
Determination of Toxic Substances/Penentuan Bahan Bertoksik
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Fakulti Kejuruteraan dan Alam Bina

Determination of Toxic Substances/Penentuan Bahan Bertoksik

Module Info


Course Name
 : INDUSTRIAL TOXICOLOGY 
Module Title :  Determination of Toxic Substances/Penentuan Bahan Bertoksik
Module Code : MCKK53061
Credit Hours : 1 credit hour
Learning Mode
 :  Physical at Faculty of Engineering and Built Environment (FKAB), UKM Bangi, Selangor, Malaysia.
Language
 :  English and Malay
Entry Requirement : Minimum SPM pass/equivalent with 3 years of work experience in a related field

or

5 years of work experience in a related field.
Registration Date :  
Module Synopsis :

This course is to provide students with processes that involve toxicants in industry and the generation of toxic waste. The effect of toxicants from the industry and agriculture towards the environment, and effective waste management will also be introduced. The dose - response correlation and basic mechanisms of absorption, distribution, metabolism and the production of toxic substances in the human body system will also be discussed. By the end of this course, students will be able to evaluate the risk, toxicity level and the solution method based on the right safety aspect.
Module Learning Outcomes : HPM3: Menganalisis perkaitan dos-tindakbalas serta mekanisme asas penyerapan, pengagihan, metabolisme dan pengeluaran bahan toksik dalam sistem tubuh manusia. 

Analyse the dose - response correlation and basic mechanisms of absorption, distribution, metabolism and the production of toxic substances in the human body system.

 

HPM4: Memahami dan menganalisis kaedah penyingkiran bahan bertoksik dari sistem tubuh manusia mengikut kelas bahan bertoksik.

Understand and analyze the excretion of toxicant from the human body system according to the classification.

 

HPM5.Menilai risiko, tahap ketoksikan dan kaedah penyelesaiannya berdasarkan aspek keselamatan yang betul.  

Evaluate the risk, toxicity level and the solution method based on the right safety aspect.  
Fee :  
Lecturer's Name :  ChM. Dr. Noorashikin Md Saleh & Ts. Dr. Nur Hidayatul Nazirah Kamarudin

  • 2
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Introduction to Toxic Substances
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Fakulti Kejuruteraan dan Alam Bina

Introduction to Toxic Substances

Module Info


Course Name
 : Micro-Credential Industrial Toxicology
Module Title : Introduction to Toxic Substances
Module Code : MC-CEIT 1
Credit Hours : 1
Learning Mode
 :  
Language
 :  English
Entry Requirement :  
Registration Date :  
Module Synopsis :

This course is to provide students with processes that involve toxicants in industry and the generation of toxic waste. The effect of toxicants from the industry and agriculture towards the environment, and effective waste management will also be introduced. The dose - response correlation and basic mechanisms of absorption, distribution, metabolism and the production of toxic substances in the human body system will also be discussed. By the end of this course, students will be able to evaluate the risk, toxicity level and the solution method based on the right safety aspect.
Module Learning Outcomes :
MLO 1

Identify the process that involved with toxicants in industry and the generation of toxic waste.
MLO 2

Investigate suitable detection methods for toxic substances from industrial and agricultural wastes.
Fee :  
Lecturer's Name :  Dr. Nur Hidayatul Nazirah Kamarudin




  • 1
  • 6
Spectroscopy
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Fakulti Kejuruteraan dan Alam Bina

Spectroscopy

Module Info


Course Name
:Chemical Instrumentation
Module Title: Spectroscopy
Module Code:MC-CECIM-2
Credit Hours:1
Learning Mode
: Online
Language
: English and Malay
Entry Requirement: Minimum SPM pass/equivalent with 3 years of work experience in a related field 

or 

5 years of work experience in a related field.
Registration Date: October 2024
Module Synopsis:This course aims to provide exposure and knowledge to the concept of chemical instrumentation methods in performing chemical analysis. It will emphasize the basic theory and main principles of chemical instrumentation as well as the opportunity to use most of the equipment found in the department's Analytical Laboratory through laboratory work given throughout the course. General concepts of electronic design such as signal multiplication, digital electronics and the signal-to-noise ratio of equipment will also be discussed. The general instrumentation layout of each piece of equipment used will be adequately discussed. Students will also be exposed to using the latest instrumentation analysis in the determination of chemical structure, composition and properties of materials, separation of chemical components, performing concentration and purity measurements and undergoing quality assurance processes in instrumentation measurements.
Module Learning Outcomes:
MLO 1Understand the basic operation of equipment and chemical instrumentation components found in the laboratory.
MLO 2Interpreting data obtained from analytical equipment.
MLO 3  Determining chemical structures, performing concentration and purity and implementing quality assurance in chemical measurements.

Fee: 
Lecturer's Name: Assoc. Prof. Ts. Dr. Wan Nor Roslam Wan Isahak




  • 21
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MODULE 1: Micro Award Data for Decision Making
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Teacher: Dr. Nur Arzilah Ismail

MODULE 1: Micro Award Data for Decision Making

Module Info


Course Name
 : MCKK56073 Micro-credential Engineering Statistics
Module Title : Micro Award Data for Decision Making
Module Code : MCKK56071
Credit Hours : 1
Learning Mode
 : Online, Physical, Self Learning
Language
 : English
Entry Requirement : Minimum SPM pass/equivalent with 3 years of work experience in related field 

Or; 

With 5 years of experience in related field.
Registration Date :  
Module Synopsis : This module introduces fundamental data analysis techniques for effective decision-making in engineering and industry. Students will explore parametric and non-parametric hypothesis testing, data visualization, and statistical reasoning to analyze and interpret data. Practical applications using modern software tools will enhance participants’ ability to make informed and data-driven decisions.
Module Learning Outcomes :
MLO 1 Identify the basic concepts of parametric and non-parametric hypotheses as well as the appropriate applications of hypothesis testing in real-life problems
Fee :  
Lecturer's Name :

Dr. Nur Arzilah Ismail
Dr. Izamarlina Asshaari 
Dr. Umawathy Techanamurthy








  • 14
  • 6
Supervised Machine Learning
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Fakulti Kejuruteraan dan Alam Bina

Supervised Machine Learning

Module Info


Course Name
 :
Module Title :  
Module Code :
Credit Hours :
Learning Mode
 :  
Language
 :  
Entry Requirement :  
Registration Date :  
Module Synopsis : This module introduces students to the basic concepts of Marketing, the importance of strategic planning and elements in the marketing environment.
Module Learning Outcomes :
MLO 1 example: Describes the basic concepts in marketing
MLO 2 example: Identify the element in the strategic planning and marketing environment.
Fee :  
Lecturer's Name :  




  • 17
  • 7
Fluid Power Systems
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Teacher: Hawa Hishamuddin

Fluid Power Systems

Module Info


Course Name
 : Manufacturing Automation
Module Title :  Fluid Power Systems
Module Code : MCKK54021
Credit Hours : 1
Learning Mode
 :  Hybrid
Language
 :  English
Entry Requirement :  Minimum pass SPM/equivalent with 3 years of experience in the related areas

or;

With 5 years of experience in related areas.
Registration Date :  
Module Synopsis : This module provides exposure to the concept of fluid power and its application in the industry. The titles covered include: fluid power components and circuits, industrial control systems, electro-hydraulic and pneumatic systems, programmable logic controllers (PLCs).
Module Learning Outcomes :
MLO 1 Ability to identify and select suitable components in manufacturing automation systems.
MLO 2 Ability to design penumatic and hydraulic circuits for an automation system application.
Fee :  
Lecturer's Name :  1. Dr. Hawa Hishamuddin(coordinator)
 2. Dr. Afifah Zakiyyah Juri
 3. Assoc Prof Ir Dr Rizauddin Ramli




  • 16
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Persistent Organic Pollutants in Water / Pencemaran Organik Berterusan dalam Air
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Teacher: Nur Hidayatul Nazirah KamarudinTeacher: Noorashikin Md Saleh

Persistent Organic Pollutants in Water / Pencemaran Organik Berterusan dalam Air

Module Info


Course Name
 : Industrial Toxicology
Module Title : Persistent Organic Pollutants in Water / Pencemaran Organik Berterusan dalam Air


Code		 : MCKK53051
Credit Hours : 1 credit 
Learning Mode
 : Online lecture and Recorded Video
Language
 : English & Malay
Entry Requirement :

Minimum SPM pass/equivalent with 3 years of work experience in a related field

or;

5 years of work experience in a related field.
Registration Date :  
Module Synopsis :

This course is to provide students with process that involved with toxicants in industry and the generation of toxic waste. The effect of toxicants from the industry and agriculture towards the environment, and effective waste management will also be introduced. The dose - response correlation and basic mechanisms of absorption, distribution, metabolism and the production of toxic substances in the human body system will also be discussed. By the end of this course, students will be able to evaluate the risk, toxicity level and the solution method based on the right safety aspect.


Module Learning Outcomes :

HPM1: Identify the process that involved with toxicants in industry and the generation of toxic waste. 

Mengenalpasti proses yang melibatkan bahan bertoksik di industri dan penghasilan sisa bertoksik. 

 

HPM2: Investigate suitable detection methods for toxic substances from industrial and agricultural wastes. 

Menyiasat kaedah pengesanan yang sesuai untuk bahan toksik daripada sisa industri dan pertanian. 
Fee :  
Lecturer's Name :  ChM. Dr. Noorashikin Md Saleh 

  • 2
  • 7
Robot Arm Kinematics
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Teacher: AFIFAH ZAKIYYAH JURI

Robot Arm Kinematics

Module Info


Course Name
 : Micro-Credential Manufacturing Automation
Module Title :  Robot Arm Kinematics
Module Code : MCKK54031
Credit Hours : 1
Learning Mode
 :  Hybrid
Language
 :  English
Entry Requirement :  Minimum pass SPM/equivalent with 3 years of experience in the related areas or;
With 5 years of experience in related areas
Registration Date :  
Module Synopsis : This module introduces students to the basic concepts of robot arm kinematics, including forward and inverse kinematics, simulations and programming of industrial robot.
Module Objective :
Module Learning Outcomes :
MLO 1 Explain the concept of industrial robot positioning using forward kinematics.
MLO 2
Analyse the position and orientations of industrial robot in 3 dimensions.
Fee :  
Lecturer's Name : 1. Assoc Prof Ir Dr Rizauddin Ramli(coordinator)
2. Dr Afifah Zakiyyah Juri
3. Dr Hawa Hishamuddin




  • 16
  • 8
Micro-Credential Chemical Instrumentation Method: Chromatography
Fakulti Kejuruteraan dan Alam Bina
Preview Course

Teacher: Noorashikin Md SalehTeacher: Wan Nor Roslam Wan Isahak

Micro-Credential Chemical Instrumentation Method: Chromatography

Module Info


Course Name
 : Chemical Instrumentation Method
Module Title : Chromatography
Module Code : MC-CECIM 1
Credit Hours : 1 credit 
Learning Mode
 :  Hybrid (Online + Physical)
Language
 :  English
Entry Requirement :  Minimum SPM pass/equivalent with 3 years of work experience in a related field

or

5 years of work experience in a related field.
Registration Date :  April 2024
Module Synopsis :

This course aims to provide exposure and knowledge to the concept of chemical instrumentation methods in performing chemical analysis. It will emphasize the basic theory and main principles of chemical instrumentation as well as the opportunity to use most of the equipment found in the department's Analytical Laboratory through laboratory work given throughout the course. General concepts of electronic design such as signal multiplication, digital electronics and the signal-to-noise ratio of equipment will also be discussed. The general instrumentation layout of each piece of equipment used will be adequately discussed. Students will also be exposed to using the latest instrumentation analysis in the determination of chemical structure, composition and properties of materials, separation of chemical components, performing concentration and purity measurements and undergoing quality assurance processes in instrumentation measurements.
Module Learning Outcomes :

HPM1: Explain the basic theory and principles of chemical instrumentation.  

Menerangkan teori dan prinsip asas instrumentasi kimia.

 

HPM2: Prepare theoretical samples that will be used in an analytical equipment.

Menyediakan sampel secara teori yang akan digunakan dalam sesuatu peralatan analisis. 

HPM3: Understand the basic operation of equipment and chemical instrumentation components found in the laboratory

Memahami operasi asas peralatan dan komponen instrumentasi kimia yang terdapat dalam makmal. 
Fee :  
Lecturer's Name : ChM. Dr. Noorashikin Md Saleh




  • 22
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