AI-Powered Cybersecurity: Threat Detection & Response Training Course

This instructor-led, live training in Botswana (online or onsite) is designed for data scientists and software engineers who wish to utilise 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 programme explores the application of AI—focusing on Machine Learning and Deep Learning—within the automotive industry. It guides learners in identifying technologies that can be applied across various automotive scenarios, ranging from basic automation and image recognition to autonomous decision-making.

This instructor-led, live training in Botswana (online or onsite) is aimed at biologists who wish to understand how AlphaFold works and use AlphaFold models as guides in their experimental studies.

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

• Understand the basic principles of AlphaFold.
• Learn how AlphaFold works.
• Learn how to interpret AlphaFold predictions and results.

This instructor-led live training in Botswana (online or onsite) is targeted at participants with varying levels of expertise who aim to utilise Google's AutoML platform to construct tailored chatbots for a wide array of applications.

Upon completion of this training, participants will be capable of:

• Grasping the fundamentals of chatbot development.
• Navigating the Google Cloud Platform and accessing AutoML.
• Preparing data for training chatbot models.
• Training and assessing custom chatbot models using AutoML.
• Deploying and integrating chatbots into various platforms and channels.
• Monitoring and optimising chatbot performance over time.

This instructor-led live training in Botswana (available online or onsite) covers various aspects of enterprise security, spanning from artificial intelligence to database security. The programme also encompasses the cutting-edge tools, processes, and strategic approaches necessary to defend against attacks.

This instructor-led, live training in Botswana (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 Botswana (online or on-site) is targeted at data scientists and analysts seeking to automate, evaluate, and manage predictive models leveraging DataRobot's machine learning features.

Upon completion of this training, participants will be capable of:

• Loading datasets into DataRobot to analyse, assess, and perform quality checks on data.
• Constructing and training models to pinpoint key variables and achieve prediction objectives.
• Interpreting models to derive valuable insights that aid in business decision-making.
• Monitoring and managing models to sustain optimal prediction performance.

This instructor-led, live training in Botswana (online or onsite) is targeted at intermediate-level developers, data scientists, and AI practitioners who wish to leverage TensorFlow Lite for Edge AI applications.

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

• Understand the fundamentals of TensorFlow Lite and its role in Edge AI.
• Develop and optimize AI models using TensorFlow Lite.
• Deploy TensorFlow Lite models on various edge devices.
• Utilize tools and techniques for model conversion and optimization.
• Implement practical Edge AI applications using TensorFlow Lite.

This instructor-led, live training in Botswana (online or onsite) is designed for 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.

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

• Explore the AutoML product suite to implement diverse services for various data types.
• Prepare and label datasets to generate custom ML models.
• Train and manage models to ensure the production of accurate and fair machine learning outcomes.
• Utilize trained models to make predictions that align with business objectives and needs.

Kubeflow is an open-source platform designed to streamline building, training, and deploying machine learning workloads on Kubernetes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to build reliable ML workflows using Kubeflow.

Upon completion of this training, attendees will gain the skills to:

• Navigate the Kubeflow ecosystem and core components.
• Build reproducible workflows with Kubeflow Pipelines.
• Run scalable training jobs on Kubernetes.
• Serve machine learning models efficiently using Kubeflow Serving.

Format of the Course

• Guided presentations and collaborative discussions.
• Hands-on labs with real Kubeflow components.
• Practical exercises to build end-to-end ML workflows.

Course Customization Options

• Customized versions of this training can be arranged to align with your team’s technology stack and project requirements.

This instructor-led, live training in Botswana (online or onsite) is aimed at developers and data scientists who wish to build, deploy, and manage machine learning workflows on Kubernetes.

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

• Install and configure Kubeflow on premise and in the cloud.
• Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
• Run entire machine learning pipelines on diverse architectures and cloud environments.
• Using Kubeflow to spawn and manage Jupyter notebooks.
• Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.

Why should you attend?

The Certified Lead Ethical Hacker training course empowers you to develop the essential expertise required to conduct information system penetration tests. By applying recognised principles, procedures, and penetration testing techniques, you will learn to identify potential threats within computer networks. Throughout this training, you will acquire the knowledge and skills necessary to manage a penetration testing project or team, as well as to plan and execute internal and external pentests in compliance with various standards, such as the Penetration Testing Execution Standard (PTES) and the Open Source Security Testing Methodology Manual (OSSTMM). Furthermore, you will gain a comprehensive understanding of how to draft reports and propose countermeasures. Additionally, through practical exercises, you will master penetration testing techniques and acquire the skills needed to manage a pentest team, handle customer communication, and resolve conflicts.

The Certified Lead Ethical Hacking training course provides a technical perspective on information security through ethical hacking, utilising common techniques such as information gathering and vulnerability detection, both within and outside of a business network.

The training is also aligned with the NICE (The National Initiative for Cybersecurity Education) Protect and Defend framework.

Upon mastering the requisite knowledge and skills in ethical hacking, you can sit for the exam and apply for the "PECB Certified Lead Ethical Hacker" credential. By holding a PECB Lead Ethical Hacker certificate, you will demonstrate that you have acquired the practical skills for performing and managing penetration tests in accordance with best practices.

Who should attend?

• Individuals interested in IT Security, particularly in Ethical Hacking, who wish to learn more about the topic or initiate a process of professional reorientation.
• Information security officers and professionals seeking to master ethical hacking and penetration testing techniques.
• Managers or consultants wishing to learn how to oversee the penetration testing process.
• Auditors wishing to perform and conduct professional penetration tests.
• Persons responsible for maintaining the security of information systems within an organisation.
• Technical experts who want to learn how to prepare a pentest.
• Cybersecurity professionals and information security team members.

This instructor-led live training, accessible online or onsite, is intended for developers who wish to utilise Google’s ML Kit to build machine learning models optimised for mobile device processing.

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

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

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

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

• Set up the necessary development environment to begin 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 optimise machine learning model performance by tuning the hyperparameters.

This instructor-led live training in Botswana (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.