AI-Powered Cybersecurity: Threat Detection & Response Training Course

This instructor-led, live training in Malaysia (online or onsite) is designed for data scientists and software engineers who wish to use AdaBoost to build boosting algorithms for machine learning with Python.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start building machine learning models with AdaBoost.
• Understand the ensemble learning approach and how to implement adaptive boosting.
• Learn how to build AdaBoost models to boost machine learning algorithms in Python.
• Use hyperparameter tuning to increase the accuracy and performance of AdaBoost models.

This instructor-led, live training in Malaysia (online or onsite) is tailored for data scientists as well as individuals with less technical backgrounds who wish to leverage Auto-Keras to automate the selection and optimization of machine learning models.

Upon completion of this training, participants will be able to:

• Automate the training of highly efficient machine learning models.
• Automatically identify the optimal parameters for deep learning models.
• Develop highly accurate machine learning models.
• Harness the power of machine learning to address real-world business challenges.

This instructor-led live training (online or onsite) is designed for technical professionals with a background in machine learning who want to optimise models for identifying complex patterns in big data using AutoML frameworks.

This instructor-led, live training in Malaysia (online or onsite) is designed for participants at various proficiency levels who aim to utilise Google's AutoML platform to create tailored chatbots for a range of applications.

Upon completion of this training, participants will be able to:

• Comprehend the core principles of chatbot development.
• Navigate the Google Cloud Platform and access AutoML services.
• Prepare data for training chatbot models.
• Train and assess custom chatbot models using AutoML.
• Deploy and integrate chatbots across various platforms and channels.
• Monitor and optimise chatbot performance over time.

This instructor-led live training in Malaysia (online or onsite) examines various dimensions of enterprise security, including AI and database security. It also covers the essential tools, processes, and strategic mindset needed to counteract cyber threats.

This instructor-led, live training in Malaysia (online or onsite) offers an introduction to the fields of pattern recognition and machine learning. It covers practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.

By the end of this training, participants will be able to:

• Apply fundamental statistical methods to pattern recognition.
• Utilize essential models such as neural networks and kernel methods for data analysis.
• Implement advanced techniques to solve complex problems.
• Enhance prediction accuracy by integrating various models.

This instructor-led live training in Malaysia (online or onsite) is designed for data scientists and analysts who wish to automate, evaluate, and manage predictive models using DataRobot's machine learning capabilities.

By the end of this training, participants will be able to:

• Load datasets in DataRobot to analyze, assess, and quality check data.
• Build and train models to identify important variables and meet prediction targets.
• Interpret models to create valuable insights that are useful in making business decisions.
• Monitor and manage models to maintain an optimized prediction performance.

This programme immerses students in an interactive environment, demonstrating how to scan, test, hack, and secure their own systems. The lab-intensive setting provides in-depth knowledge and practical experience with essential modern security technologies. Students start by understanding perimeter defenses, then proceed to scan and attack their own networks—without harming any real infrastructure. They learn how intruders escalate privileges and what measures can be taken to secure a system. The curriculum also covers Intrusion Detection, Policy Creation, Social Engineering, DDoS Attacks, Buffer Overflows, and Virus Creation. Upon completing this intensive 5-day class, students will have hands-on understanding and experience in Ethical Hacking.

The purpose of the Ethical Hacking Training is to:

• Establish and govern minimum standards for credentialing professional information security specialists in ethical hacking measures.
• Inform the public that credentialed individuals meet or exceed the minimum standards.
• Reinforce ethical hacking as a unique and self-regulating profession.

Audience:

The course is ideal for professionals working in roles such as, but not limited to:

• Security Engineers
• Security Consultants
• Security Managers
• IT Director/Managers
• Security Auditors
• IT Systems Administrators
• IT Network Administrators
• Network Architects
• Developers

This instructor-led live training in Malaysia (online or onsite) is aimed at data scientists, data analysts, and developers who wish to explore AutoML products and features to create and deploy custom ML training models with minimal effort.

By the end of this training, participants will be able to:

• Explore the AutoML product line to implement different services for various data types.
• Prepare and label datasets to create custom ML models.
• Train and manage models to produce accurate and fair machine learning models.
• Make predictions using trained models to meet business objectives and needs.

The Certified Ethical Hacker (CEH) certification is a globally recognised credential in the field of cybersecurity.

This comprehensive programme combines instructional theory with practical application to prepare students for both the CEH certification exam and the CEH Practical Exam. Those who successfully pass both assessments are awarded the CEH Master credential alongside their standard CEH certification.

Participants have the option to enhance their learning package by including either the Certified Penetration Testing Professional (CPENT) course or the Computer Hacking Forensic Investigator (CHFI) course.

Training for either the CPENT or CHFI courses is delivered to each student through EC-Council’s online, self-paced, streaming video platform.

CPENT (Pen-testing):
This module teaches students how to apply the concepts and tools acquired in the CEH programme to a pen-testing methodology within a live cyber range environment.

CHFI (Computer Forensics):
This module instructs students on a methodological approach to computer forensics, covering search and seizure procedures, chain of custody management, data acquisition, preservation, analysis, and the reporting of digital evidence.

Course Description

The CEH programme provides a deep understanding of the phases involved in ethical hacking, various attack vectors, and preventative countermeasures. It educates participants on how attackers think and operate maliciously, enabling them to better establish security infrastructure and defend against potential future threats. By understanding system weaknesses and vulnerabilities, organisations can strengthen their security controls to minimise the risk of incidents.

CEH is designed to integrate a hands-on environment and systematic processes across every domain and methodology of ethical hacking. This approach gives students the opportunity to demonstrate the knowledge and skills required to achieve the CEH credential. Participants will be exposed to a unique perspective on the responsibilities and measures necessary for maintaining security.

Who Should Attend

• Law enforcement personnel
• System administrators
• Security officers
• Defence and military personnel
• Legal professionals
• Bankers
• Security professionals

About the Certified Ethical Hacker Master

To earn the CEH Master certification, candidates must pass the CEH Practical exam. This exam is designed to allow students to demonstrate their ability to execute the principles taught in the CEH course. The practical assessment requires candidates to demonstrate the application of ethical hacking techniques, including threat vector identification, network scanning, operating system detection, vulnerability analysis, system hacking, and more.

The CEH Practical exam does not rely on simulations. Instead, candidates challenge a live cyber range designed to mimic a corporate network using live virtual machines, networks, and applications.

Successfully completing the challenges in the CEH Practical Exam is the next step after attaining the Certified Ethical Hacker (CEH) certification. Passing both the CEH exam and the CEH Practical Exam earns you the additional distinction of the CEH Master certification.

About the Certified Ethical Hacker Practical

To verify your proficiency in ethical hacking, your abilities are tested through real-world challenges in a realistic environment. Using labs and tools, you will complete specific ethical hacking tasks within a set time limit, mirroring the pressures faced in actual professional scenarios.

The EC-Council CEH (Practical) exam consists of a complex network that replicates a large organisation’s real-life infrastructure, including various network systems such as a DMZ. You must apply your ethical hacking skills to discover and exploit vulnerabilities in real-time while auditing the systems.

About CPENT

EC-Council’s Certified Penetration Tester (CPENT) programme focuses entirely on pen-testing. It teaches you to operate in an enterprise network environment that requires attacking, exploiting, evading, and defending. If you have primarily worked in flat networks, CPENT’s live practice range will help elevate your skills. You will learn to pen-test IoT and OT systems, write custom exploits, build your own tools, conduct advanced binary exploitation, double pivot to access hidden networks, and customise scripts and exploits to reach the innermost segments of a network.

About CHFI

The Computer Hacking Forensic Investigator (CHFI) course delivers the discipline of digital forensics from a vendor-neutral perspective. CHFI is a comprehensive programme covering major forensic investigation scenarios, enabling students to acquire hands-on experience with various forensic investigation techniques and standard forensic tools required to successfully conduct computer forensic investigations.

This instructor-led live training, available online or onsite, is designed for developers looking to utilise Google’s ML Kit to build machine learning models optimised for mobile devices.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start developing machine learning features for mobile apps.
• Integrate new machine learning technologies into Android and iOS apps using the ML Kit APIs. 
• Enhance and optimize existing apps using the ML Kit SDK for on-device processing and deployment.

Pattern Matching is a method employed to identify specific patterns within an image. This technique helps determine whether certain defined characteristics exist in a captured image, such as verifying the correct label on a faulty product on a production line or confirming that a component meets specified dimensions. It differs from "Pattern Recognition," which identifies broader patterns based on extensive sets of related samples, by focusing on pinpointing exactly what is being sought and confirming the presence or absence of that specific pattern.

Course Format

• This course covers the approaches, technologies, and algorithms used in pattern matching as applied to Machine Vision.

This instructor-led, live training in Malaysia (online or onsite) is designed for data scientists and software engineers who wish to use Random Forest to build machine learning algorithms for large datasets.

By the end of this training, participants will be able to:

• Set up the necessary development environment to start building machine learning models with Random forest.
• Understand the advantages of Random Forest and how to implement it to resolve classification and regression problems.
• Learn how to handle large datasets and interpret multiple decision trees in Random Forest.
• Evaluate and optimize machine learning model performance by tuning the hyperparameters.

This instructor-led, live training in Malaysia (online or onsite) is aimed at intermediate-level data analysts who wish to learn how to use RapidMiner to estimate and project values and utilise analytical tools for time series forecasting.

By the end of this training, participants will be able to:

• Apply the CRISP-DM methodology, select appropriate machine learning algorithms, and enhance model construction and performance.
• Use RapidMiner to estimate and project values, and utilise analytical tools for time series forecasting.

RapidMiner is an open-source data science software platform designed for rapid application prototyping and development. It features an integrated environment encompassing data preparation, machine learning, deep learning, text mining, and predictive analytics.

Through this instructor-led live training, participants will gain practical skills in utilizing RapidMiner Studio for data preparation, machine learning, and the deployment of predictive models.

By the conclusion of this training, participants will be equipped to:

• Install and configure RapidMiner
• Prepare and visualize data using RapidMiner
• Validate machine learning models
• Integrate data sources and build predictive models
• Implement predictive analytics within business processes
• Troubleshoot and optimize RapidMiner performance

Audience

• Data scientists
• Engineers
• Developers

Format of the Course

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• To request customized training for this course, please contact us to arrange.