AI-Powered Cybersecurity: Threat Detection & Response Training Course

This instructor-led live training in Taiwan (available 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.

Upon completing this training, participants will be able to:

• Configure the necessary development environment to begin building machine learning models with AdaBoost.
• Grasp the concept of ensemble learning and learn how to implement adaptive boosting.
• Acquire the skills to construct AdaBoost models that enhance machine learning algorithms in Python.
• Apply hyperparameter tuning to improve the accuracy and overall performance of AdaBoost models.

This instructor-led live training in Taiwan (online or onsite) is tailored for data scientists and non-technical professionals who wish to utilize Auto-Keras to automate the process of selecting and optimizing a machine learning model.

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.
• Construct highly accurate machine learning models.
• Leverage machine learning capabilities to address real-world business challenges.

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

This instructor-led, live training in Taiwan (online or onsite) targets participants with varying levels of expertise who aim to utilize Google's AutoML platform to develop customized chatbots for diverse applications.

Upon completing this training, participants will be able to:

• Grasp the fundamentals of chatbot development.
• Navigate the Google Cloud Platform and access AutoML.
• Prepare data for training chatbot models.
• Train and evaluate custom chatbot models using AutoML.
• Deploy and integrate chatbots into various platforms and channels.
• Monitor and optimize chatbot performance over time.

This instructor-led, live training in Taiwan (online or onsite) covers the different aspects of enterprise security, from AI to database security. It also includes coverage of the latest tools, processes and mindset needed to protect from attacks. 

This instructor-led, live training in Taiwan (online or onsite) provides an introduction into the field of pattern recognition and machine learning. It touches on 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 core statistical methods to pattern recognition.
• Use key models like neural networks and kernel methods for data analysis.
• Implement advanced techniques for complex problem-solving.
• Improve prediction accuracy by combining different models.

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

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

• Import datasets into DataRobot to analyze, evaluate, and perform quality checks.
• Develop and train models to identify key variables and achieve prediction objectives.
• Interpret models to generate valuable insights that support business decision-making.
• Monitor and manage models to ensure optimal prediction performance.

This course immerses students in an interactive environment, demonstrating how to scan, test, exploit, and secure their own systems. The lab-intensive setting provides each participant with in-depth knowledge and practical experience with current essential security technologies. Students will start by understanding how perimeter defenses function, then proceed to scan and attack their own networks without harming any real infrastructure. The curriculum covers how intruders escalate privileges and the steps necessary to secure a system. Additionally, students will learn about Intrusion Detection, Policy Creation, Social Engineering, DDoS Attacks, Buffer Overflows, and Virus Creation. Upon completing this intensive 5-day class, students will possess 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 those working in positions such as, but not limited to:

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

This instructor-led, live training in Taiwan (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 certification is a highly regarded cybersecurity credential recognized globally.

This program combines comprehensive instruction with practical application to prepare students for both the CEH certification exam and the CEH Practical Exam. Candidates who successfully pass both examinations will earn the CEH Master credential alongside their CEH certification.

Students have the option to enhance their package by choosing either the CPENT or the CHFI course.

Each student will receive training for either the Certified Penetration Testing Professional (CPENT) course or the Computer Hacking Forensic Investigator (CHFI) course through EC-Council’s online, self-paced, streaming video program.

CPENT (Pen-test):
Instructs students on how to apply the concepts and tools learned in the CEH program to a penetration testing methodology within a live cyber range environment.

CHFI (Computer Forensics):
Teaches a methodological approach to computer forensics, covering areas such as searching and seizing, chain-of-custody protocols, data acquisition, preservation, analysis, and reporting of digital evidence.

Course Description

CEH offers a deep understanding of ethical hacking phases, various attack vectors, and preventative countermeasures. It reveals how hackers think and operate maliciously, empowering you to better structure your security infrastructure and defend against future threats. By understanding system weaknesses and vulnerabilities, organizations can strengthen their security controls to minimize incident risk.

CEH is designed to integrate a hands-on environment and systematic process across each ethical hacking domain and methodology. This provides the opportunity to demonstrate the knowledge and skills required to achieve the CEH credential. You will encounter a completely different perspective on the responsibilities and measures necessary to maintain security.

Who Should Attend

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

About the Certified Ethical Hacker Master

To earn the CEH Master certification, you must pass the CEH Practical exam. This exam is designed to demonstrate that you can execute the principles taught in the CEH course. The practical exam requires you to apply ethical hacking techniques, such as identifying threat vectors, network scanning, operating system detection, vulnerability analysis, system hacking, and more.

The CEH Practical exam does not rely on simulations. Instead, you will challenge a live 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 obtaining the Certified Ethical Hacker (CEH) certification. Passing both the CEH exam and the CEH Practical Exam will earn you the additional CEH Master certification.

About the Certified Ethical Hacker Practical

To prove your proficiency in ethical hacking, we test your abilities through real-world challenges in a realistic environment. Using labs and tools, you will complete specific ethical hacking challenges within a set time limit, simulating the pressures of the real world.

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

About CPENT

EC-Council’s Certified Penetration Tester (CPENT) program focuses entirely on penetration testing. It teaches you to operate within an enterprise network environment that must be attacked, exploited, evaded, and defended. If you are accustomed only to flat networks, CPENT’s live practice range will elevate your skills. You will learn to pen test IoT and OT systems, write custom exploits, build tools, conduct advanced binary exploitation, double pivot to access hidden networks, and customize scripts and exploits to penetrate the innermost segments of the network.

About CHFI

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

This instructor-led, live training (available online or onsite) is designed for developers who wish to employ Google’s ML Kit to develop machine learning models optimized for mobile device processing.

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

• Establish the necessary development environment to commence creating machine learning features for mobile applications.
• Integrate new machine learning technologies into Android and iOS applications utilizing ML Kit APIs.
• Enhance and optimize existing applications using the ML Kit SDK for on-device processing and deployment.

Pattern matching is a technique employed to identify specific patterns within an image. It can be used to determine the existence of specified characteristics within a captured image, for example the expected label on a defective product in a factory line or the specified dimensions of a component. It is different from "Pattern Recognition" (which recognizes general patterns based on larger collections of related samples) in that it specifically dictates what we are looking for, then tells us whether the expected pattern exists or not.

Format of the Course

• This course introduces the approaches, technologies and algorithms used in the field of pattern matching as it applies to Machine Vision.

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

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

• Establish the necessary development environment to commence building machine learning models with Random Forest.
• Comprehend the advantages of Random Forest and apply it to solve classification and regression problems.
• Learn techniques for handling large datasets and interpreting the multiple decision trees inherent in Random Forest.
• Evaluate and optimize machine learning model performance by fine-tuning hyperparameters.

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

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

• Learn 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 utilize analytical tools for time series forecasting.

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

In this instructor-led live training, participants will learn how to utilize RapidMiner Studio for data preparation, machine learning, and the deployment of predictive models.

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

• Install and configure RapidMiner
• Prepare and visualize data with RapidMiner
• Validate machine learning models
• Mashup data and create predictive models
• Operationalize predictive analytics within a business process
• Troubleshoot and optimize RapidMiner

Audience

• Data scientists
• Engineers
• Developers

Format of the Course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

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