Get Security+ Training and Certification Online in Malaysia

Most in-demand in IT is CompTIA Security+ certification for engineers and alike.

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CompTIA Security+

Security+ Training and Certification in Malaysia

Duration: 4 days/32 hours

  • While there are no official prerequisites for CompTIA Security+, it is advisable to have a minimum of two years of experience in IT administration with a security emphasis, and obtaining the CompTIA Network+ certification before attempting the exam is recommended.

Security+ training may be used for a variety of job roles, including but not limited to:
  • Network Security Operations
  • Penetration Tester
  • Network Security Analyst
  • Web App Penetration Tester
  • Security Architect

Limited time Course Price

RM 4000

RM 2500

(Training Only)


Build a strong fundamental skill set, setting the path for a rewarding career. Security+ is the most widely recognized certification for baseline cybersecurity skills in the industry, employed in a greater number of job roles than any other certification.

Security+ holds the distinction of being the most widely recognized ISO/ANSI-accredited cybersecurity certification for professionals early in their careers. The certification exam includes hands-on, performance-based questions that evaluate your problem-solving skills in real-world scenarios, allowing you to showcase your expertise to potential employers right away.

Comprehend and leverage the latest developments in cybersecurity technology, terminology, methodologies, and tools. By acquiring foundational skills in emerging trends such as automation, zero trust, risk analysis, operational technology, and IoT, you will be well-prepared to thrive in the continually evolving cybersecurity field.

Get the best!


20 hours of Lab practice guided by an instructor
E-book with tools and software
600 latest exam practice questions
4.8 star rating of google reviews
Exam Practice questions that students will access and practice through a server
Live online or Classroom training
95% exam passing rate with one attempt

The examination format of Network+

  • Examination Name - SY0-601 , SY0-701 
  • CCNA Exam Price - USD 392
  • CCNA Exam Questions Format - Multiple choice and performance-based
  • Number of Questions - 90 Questions
  • Score required to pass the exam - 750 out of 1000
  • Duration of the exam - 1.5 Hours (90 Minutes)
  • Exam mode of language - English, Japanese, Vietnamese, Thai, and Portuguese for SY0-601 & English, with Japanese, Portuguese, and Spanish to follow  for SY0-701 
  • Exam Venue - Testing Centers, Online Testing

Course Benefits

CompTIA Security+ certifies that professionals possess the skills necessary to propose and deploy security solutions.

CompTIA Security+ is an internationally recognized certification that confirms the essential skills needed to carry out fundamental security tasks and embark on a career in IT security.

Join now and start preparing for the SY0-601 , SY0-701 exam, which gives you a CompTIA Security+ Certification .

The new CompTIA Security+ (SY0-701) embodies the forefront of cybersecurity, encompassing the most sought-after skills pertaining to contemporary threats, automation, zero trust, IoT, risk management, and beyond.

Show your skills and expertise to climb your career ladder as a Security+ certified professional

Improve your job prospects as an IT professional by earning a well-recognized certification.


Sure, here are some possible course objectives for the CompTIA Security+ course:

Evaluate the security status of an enterprise environment and propose and deploy suitable security solutions.

Supervise and fortify hybrid environments, which include cloud, mobile, Internet of Things (IoT), and operational technology.

Recognize, assess, and take action in response to security events and incidents.

Operate with a consciousness of relevant regulations and policies, encompassing principles of governance, risk management, and compliance.

Course Outline

  • MODULE 1
  • MODULE 2
  • MODULE 3
  • MODULE 4
  • MODULE 5
  • MODULE 6

Introduction To Data Science and Data Science Libraries

  • Data science is the field of applying advanced analytics techniques and scientific principles to extract valuable information from data for business decision-making, strategic planning and other uses. Through this module, you will learn the basics, how to analyze data, and then create some beautiful visualizations using Python.


  • It’s a general-purpose array-processing package that provides high-performance multidimensional objects called arrays and tools for working with them. NumPy also addresses the slowness problem partly by providing these multidimensional arrays as well as providing functions and operators that operate efficiently on these arrays.
  • NumPy Getting Started
  • NumPy Creating Arrays
  • NumPy Array Indexing
  • NumPy Array Slicing
  • NumPy Data Types
  • NumPy Copy vs View
  • NumPy Array Shape
  • NumPy Array Reshape
  • NumPy Array Iterating
  • NumPy Array Join
  • NumPy Array Split
  • NumPy Array Search
  • NumPy Array Sort
  • NumPy Array Filter
  • NumPy Random
  • NumPy Inbuilt Methods


Pandas is an important library in Python for Data Science. It is used for data manipulation and analysis. It is well suited for different data such as tabular, ordered and unordered time series, matrix data, etc.

  • Pandas Getting Started
  • Pandas Series
  • Pandas Data Frames
  • Pandas Read CSV
  • Pandas Read JSON
  • Pandas Read Excel
  • Pandas Analyzing Data

Data Cleaning and Data Wrangling Using Python Pandas

Data scientists spend a large amount of their time cleaning datasets and getting them down to a form with which they can work. In fact, a lot of data scientists argue that the initial steps of obtaining and cleaning data constitute 80% of the job. Therefore, if you are just stepping into this field or planning to step into this field, it is important to be able to deal with messy data, whether that means missing values, inconsistent formatting, malformed records, or nonsensical outliers. In this module, we’ll leverage Python’s Pandas to clean data.

  • Cleaning a DataFrame
  • Removing Columns
  • Removing Rows
  • Filling Missing Values
  • Improving Readability
  • Dropping Columns in a DataFrame
  • Changing the Index of a DataFrame

Matplotlib Visualization with Python

Matplotlib is a python library used to create 2D graphs and plots by using python scripts. It has a module named pyplot which makes things easy for plotting by providing feature to control line styles, font properties, formatting axes etc. It supports a very wide variety of graphs and plots namely - histogram, bar charts, power spectra, error charts etc.

  • Python Data Visualization
  • Python Chart Properties
  • Python Chart Styling
  • Python Box Plots
  • Python Heat Maps
  • Python Scatter Plots
  • Python Line Charts
  • Python Pie Charts
  • Python Bar Charts
  • Python Time Series
  • Python Geographical Data

Python seaborn Library

Seaborn is one of an amazing library for visualization of the graphical statistical plotting in Python. Seaborn provides many color palettes and defaults beautiful styles to make the creation of many statistical plots in Python more attractive. Seaborn library aims to make a more attractive visualization of the central part of understanding and exploring data. It is built on the core of the matplotlib library and also provides dataset-oriented APIs.

  • Plotting Chart Using seaborn Library
  • Line plot
  • Dist plot
  • Lmplot
  • Histogram
  • Bar Plot
  • Count Plot
  • Point Plot
  • Violin Plot
  • Heatmap


  • What is statistics?
  • Basic terminology of statistics
  • Types of statistics
  • Descriptive statistics
  • Measure of Central Tendency ( Mean, median, mode )
  • Measures of Dispersion ( Variance, Standard Deviation, Range-its derivation )
  • Inferential statistics
  • MODULE 7
  • MODULE 8
  • MODULE 9
  • MODULE 10
  • MODULE 11

Exploratory Data Analysis

In this module, you will learn what is meant by exploratory data analysis, and you will learn how to perform computations on the data to calculate basic descriptive statistical information, such as mean, median, mode, and quartile values, and use that information to better understand the distribution of the data. You will learn about putting your data into groups to help you visualize the data better. Exploratory data analysis (EDA) is an especially important activity in the routine of a data analyst or scientist. It enables an in depth understanding of the dataset, define or discard hypotheses and create predictive models on a solid basis. It uses data manipulation techniques and several statistical tools to describe and understand the relationship between variables and how these can impact business.

Capstone Project 1 : Credit Card Fraud Detection Case Study

Overview : Lots of financial losses are caused every year due to credit card fraud transactions, the financial industry has switched from a posterior investigation approach to an a priori predictive approach with the design of fraud detection algorithms to warn and help fraud investigators.

This case study is focused to give you an idea of applying Exploratory Data Analysis (EDA) in a real business scenario. In this case study, apart from applying the various Exploratory Data Analysis (EDA) techniques, you will also develop a basic understanding of risk analytics and understand how data can be utilized in order to minimize the risk of losing money while lending to customers.


Introduction To Machine Learning

  • Introduction To Machine Learning
  • Types Of Machine Learning

Supervised Learning - Classification 

  • Logistic Regression

Capstone Project 4 - Healthcare Industry Predicting Diabetes

This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. In this you will be learning the concepts of Logistic Regression.


 Unsupervised Learning

  • Types of Unsupervised Learning
  • Applications of Unsupervised Learning
  • Introduction to Clustering Algorithms
  • Types of Clustering Algorithms
  • What is K-Means Clustering?
  • Implementation Of Apriori Algorithms


Capstone Project 5 - Apriori Algorithm is a Machine Learning algorithm utilized to understand the patterns of relationships among the various products involved. The most prominent practical application of the algorithm is to recommend products based on the products already present in the user’s cart. Walmart especially has made great use of the algorithm in suggesting products to it’s users.


Supervised Learning - Regression 

Apply different Machine Learning algorithms

Capstone Project 6 - Bank Churn Prediction using popular classification algorithms

Knowing the customer churn rate is a key indicator for any business. According to a study by Bain & Company, improving the customer retention rate for existing customers by just 5 percent can improve a company’s profitability by 25 to 95 percent.

  •  In this module, we are going to look at the following:
  • Initial Exploratory Data Analysis
  • Predicting the churn rate for a customer and classify them by learning about different classification algorithms.
  • Comparing and evaluating different algorithms based on its performance.
  • And once we have our best model, we would perform optimization

What You Will Learn

Essential cybersecurity terminology and concepts at the beginning to establish a solid foundation for the security controls addressed during the examination.

Emphasizes the response to prevalent threats, cyberattacks, vulnerabilities, and security incidents, along with suitable mitigation techniques for the monitoring and safeguarding of hybrid environments.

It covers the security implications of various architectural models, the principles for securing enterprise infrastructure, and strategies for safeguarding data.

It has been updated to more accurately reflect the reporting and communication skills needed for Security+ job roles pertaining to governance, risk management, compliance, assessment, and promoting security awareness.

Includes applying and enhancing security and vulnerability management techniques, as well as security implications of proper hardware, software, and data management.

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Will I receive a certificate upon finishing this course?

Yes, you will get a personalized digital certificate downloadable as a PDF. You will need to complete over 85% of the curriculum lessons

Do you provide support for this course? 

Yes, our trainers are there to support you during training and post training.

Can I request a refund if I am not happy with the training?

Yes, subject to our refund policies. 

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