AI-Powered Cybersecurity: Threat Detection & Response Training Course

This instructor-led, live training in Finland (online or onsite) is aimed at 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 Finland (online or onsite) is aimed at data scientists as well as less technical persons who wish to use Auto-Keras to automate the process of selecting and optimizing a machine learning model.

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

• Automate the process of training highly efficient machine learning models.
• Automatically search for the best parameters for deep learning models.
• Build highly accurate machine learning models.
• Use the power of machine learning to solve real-world business problems.

This instructor-led, live training in Finland (online or onsite) is aimed at technical persons with a background in machine learning who wish to optimize the machine learning models used for detecting complex patterns in big data.

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

• Install and evaluate various open source AutoML tools (H2O AutoML, auto-sklearn, TPOT, TensorFlow, PyTorch, Auto-Keras, TPOT, Auto-WEKA, etc.)
• Train high quality machine learning models.
• Efficiently solve different types of supervised machine learning problems.
• Write just the necessary code to initiate the automated machine learning process.

This instructor-led, live training in Finland (online or onsite) is aimed at participants with varying levels of expertise who wish to leverage Google's AutoML platform to build customized chatbots for various applications.

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

• Understand 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 Finland (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 Finland (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 Finland (online or onsite) is aimed at data scientists and data 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 instructor-led, live training in Finland (online or onsite) is aimed at beginner to intermediate-level data analysts and data scientists who wish to use Weka to perform data mining tasks.

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

• Install and configure Weka.
• Understand the Weka environment and workbench.
• Perform data mining tasks using Weka.

This class will immerse the students into an interactive environment where they will be shown how to scan, test, hack and secure their own systems. The lab intensive environment gives each student in-depth knowledge and practical experience with the current essential security systems. Students will begin by understanding how perimeter defenses work and then be lead into scanning and attacking their own networks, no real network is harmed. Students then learn how intruders escalate privileges and what steps can be taken to secure a system. Students will also learn about Intrusion Detection, Policy Creation, Social Engineering, DDoS Attacks, Buffer Overflows and Virus Creation. When a student leaves this intensive 5 day class they 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 those working in positions 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 Finland (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 sought-after cybersecurity certification around the world.

This program incorporates instruction and practice to get students ready to take the CEH certification exam as well as the CEH Practical Exam. Candidates who successfully pass both exams earn the CEH Master credential as well as their CEH certification.

Students are given the choice to add either the CPENT or the CHFI course to their package.

Training for either the Certified Penetration Testing Professional (CPENT) course or the Computer Hacking Forensic Investigator (CHFI) course will be given to each student via EC-Council’s online, self-paced, streaming video program.

CPENT (Pen-test):
Teaches students how to apply the concepts and tools taught in the CEH program to a pen-test methodology in a live cyber range.

CHFI (Computer Forensics):
Teaches students a methodological approach to computer forensics including searching and seizing, chain-of-custody, acquisition, preservation, analysis and reporting of digital evidence.

Course Description

CEH provides an in-depth understanding of ethical hacking phases, various attack vectors, and preventative countermeasures. It will teach you how hackers think and act maliciously so you will be better positioned to set up your security infrastructure and defend against future attacks. An understanding of system weaknesses and vulnerabilities helps organizations strengthen their system security controls to minimize the risk of an incident.

CEH was built to incorporate a hands-on environment and systematic process across each ethical hacking domain and methodology, giving you the opportunity to work towards proving the required knowledge and skills needed to achieve the CEH credential. You will be exposed to an entirely different posture toward the responsibilities and measures required to be secure.

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. The CEH Practical Exam was designed to give students a chance to prove they can execute the principals taught in the CEH course. The practical exam requires you to demonstrate the application of ethical hacking techniques such as threat vector identification, network scanning, OS detection, vulnerability analysis, system hacking, and more.

The CEH Practical does not contain simulations. Rather, you will be challenging a live range which was designed to mimic a corporate network through the use of live virtual machines, networks, and applications.

Successfully completing the challenges found in the CEH Practical Exam is the next step after attaining the Certified Ethical Hacker (CEH) certification. Successfully passing both the CEH exam and the CEH Practical will earn you the additional certification of CEH Master.

About the Certified Ethical Hacker Practical

To prove that you are skilled in ethical hacking, we test your abilities with real-world challenges in a real-world environment, using labs and tools requiring you to complete specific ethical hacking challenges within a time limit, just as you would face in the real world.

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

About CPENT

EC-Council’s Certified Penetration Tester (CPENT) program is all about the pen test and will teach you to perform in an enterprise network environment that must be attacked, exploited, evaded, and defended. If you have only been working in flat networks, CPENT’s live practice range will teach you to take your skills to the next level by teaching you to pen test IoT systems, OT systems, as well as how to write your own exploits, build your own tools, conduct advanced binaries exploitation, double pivot to access hidden networks, and customization of scripts and exploits to get into 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. CHFI is a comprehensive course covering major forensic investigation scenarios and enabling students to acquire necessary hands-on experience with various forensic investigation techniques and standard forensic tools necessary to successfully carry out a computer forensic investigation.

This instructor-led, live training in (online or onsite) is aimed at developers who wish to use Google’s ML Kit to build machine learning models that are optimized for processing on 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.

This instructor-led, live training in Finland (online or onsite) is aimed at 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 Finland (online or onsite) 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 for rapid application prototyping and development. It includes an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics. 

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

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.