15162 AI courses

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Duration 2 Days 12 CPD hours This course is intended for The primary audience for this course is any IT, facilities or data centre professional who works in and around the data centre and who has the responsibility to achieve and improve the availability and manageability of the data centre. Overview After completion of the course the participant will be able to:? Choose an optimum site for mission-critical data centre based on current and future needs? Describe all components that are important for high availability in a data centre and how to effectively setup the data centre? Name and apply the various industry standards? Describe the various technologies for UPS, fire suppression, cooling, monitoring systems, cabling standards, etc, and to select and apply them effectively to cost-efficiently enhance the high-availability of the data centre.? Review the electrical distribution system to avoid costly downtime? Enhance cooling capabilities and efficiency in the data centre by using existing and new techniques and technologies for the increased cooling requirements of the future? Design a highly reliable and scalable network architecture and learn how to ensure installers apply proper testing techniques? Create effective maintenance contracts with equipment suppliers ensuring the best return on investment? Setup effective data centre monitoring ensuring the right people get the right message? Ensure proper security measures, both procedural and technical, are established to safeguard your company's valuable information in the data centre The course will address how to setup and improve key aspects such as power, cooling, security, cabling, safety, etc., to ensure a high available data centre. It will also address key operations and maintenance aspects. The Data Centre, it?s Importance and Causes for DowntimeData Centre Standards and Best PracticesData Centre Location, Building and Construction Selecting appropriate sites and buildings and how to avoid pitfalls Various components of an effective data centre and supporting facilities setup Raised Floor/Suspended Ceiling Uniform, concentrated and rolling load definitions Applicable standards Raised Floor guidelines Signal Reference Grid, grounding of racks Disability act and regulations Suspended ceiling usage and requirements Light Standards Light fixture types and placement Emergency lighting, Emergency Power Supply (EPS) Power Infrastructure Power infrastructure layout from generation to rack level ATS and STS systems Redundancy levels and techniques Three-phase and single-phase usage Power distribution options within the computer room Power cabling versus bus bar trunking Bonding versus grounding Common Mode Noise and isolation transformers Distribution boards, form factors and IP-protection grades Power quality guidelines Real power versus apparent power How to size and calculate load in the data centre Generators Static and dynamic UPS systems, selection criteria, how they operate and energy efficiency option Battery types, correct selection and testing Thermo-graphics Electro Magnetic Fields Electrical fields and magnetic fields definitions and units of measurements Sources of EMF Effects of EMF on human health and equipment (H)EMP Standards EMF shielding solutions Equipment Racks Rack standards, properties and selection criteria Security considerations Power rail/strip options Cooling Infrastructure Temperature and humidity recommendations Cooling measurement units and conversion rates Sensible and latent heat definitions Differences between comfort and precision cooling Overview of different air conditioner technologies Raised floor versus non-raised floor cooling Placement of air conditioner units and limitations to be observed Supplemental cooling options Cold aisle/hot aisle containment Water Supply Importance of water supply and application areas Backup water supply techniques Designing a Scalable Network Infrastructure The importance of a Structured Cabling System Planning considerations Copper and Fiber cable technology and standards ANSI/TIA-942 Cabling hierarchy and recommendations Testing and verification SAN storage cabling Network redundancy Building-to-building connectivity Network monitoring system requirements Fire Suppression Standards for fire suppression Detection systems Various total flooding fire suppression techniques and systems, their benefits and disadvantages Handheld extinguishers Signage and safety Regulatory requirements and best practices Data Centre Monitoring Data centre monitoring requirements EMS versus BMS Water leak detection systems Notification options and considerations Operational Security and Safety Practices Data centre security layers Physical, infrastructure and organisational security Safety measures and essential signage Labelling Choosing a labelling scheme Recommended labelling practices Network labelling Documentation How to setup proper documentation Document management policies and procedures Cleaning Cleaning practices for the data centre MTBF/MTTR Standards and definitions Calculation models The ?real? value Maintenance Contracts/SLA/OLAEXAM: Certified Data Centre Professional Additional course details: Nexus Humans Certified Data Centre Professional (CDCP) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Certified Data Centre Professional (CDCP) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

This comprehensive course covers all Scrum principles and frameworks necessary to help participants understand how to guide a team and manage projects in a fast-paced agile environment. The course is meant for professionals who want to attain the certification of Scrum Master with deep insight into how AI can be utilized in increasing the effectiveness of agile practices. In addition to mastery of the core Scrum methodology, participants will be taken through state-of-the-art advancements in AI and machine learning in order to understand how these technologies can automate routine tasks, enhance decision-making, and continuous improvement. Real-world case studies and hands-on exercises will illustrate how to practically apply AI within Scrum to realize high efficiency and innovation for teams. Whether for enhancing one's career as a Scrum Master or the integration of AI into Agile practices, this course provides that ideal combination of conceptual theory and practical skills, assuring success in today's technology-driven world. Key Highlights: Certified Scrum Master training with AI applications Case studies in the real world about integrating AI in Scrum Hands-on projects to implement AI-driven tools and methodologies Workflow optimization techniques that ensure better collaboration of agile teams, with speeding up project delivery by the power of AI. Ideal for Scrum Masters, Agile Coaches, Product Owners, and tech pros looking to stay ahead.

Are you fascinated with Netflix and YouTube recommendations and how they accurately recommend content that you would like to watch? Are you looking for a practical course that will teach you how to build intelligent recommendation systems? This course will show you how to build accurate recommendation systems in Python using real-world examples.

Duration 1 Days 6 CPD hours This course is intended for To gain the most from attending this course you should possess the following incoming skills: Basic knowledge of programming concepts and syntax in Python. Familiarity with common data formats such as CSV, JSON, and XML. Experience using command-line interfaces and basic text editing tools. Understanding of basic machine learning concepts and algorithms. Overview Working in an interactive learning environment, led by our engaging expert, you will: Gain a solid understanding of prompt engineering concepts and their applications in software development and AI-driven solutions. Master the techniques for preprocessing and cleaning text data to ensure high-quality inputs for AI models like GPT-4. Develop expertise in GPT-4 tokenization, input formatting, and controlling model behavior for various tasks and requirements. Acquire the ability to design, optimize, and test prompts effectively, catering to diverse business applications and use cases. Learn advanced prompt engineering techniques, such as conditional text generation and multi-turn conversations, to create more sophisticated AI solutions. Practice creating prompts to generate, run, and test code in a chosen programming language using GPT-4 and OpenAI Codex. Understand the ethical implications and best practices in responsible AI deployment, ensuring fair and unbiased AI applications in software development. Prompt Engineering offers coders and software developers a competitive edge by empowering them to develop more effective and efficient AI-driven solutions in their projects. By harnessing the capabilities of cutting-edge AI models like GPT-4, coders can automate repetitive tasks, enhance natural language understanding, and even generate code suggestions, boosting productivity and creativity. In addition, mastering prompt engineering can contribute to improved job security, as professionals with these in-demand skills are highly sought after in the rapidly evolving tech landscape. Quick Start to Prompt Engineering for Coders and Software Developers is a one day course designed to get you quickly up and running with the prompting skills required to out AI to work for you in your development efforts. Guided by our AI expert, you?ll explore key topics such as text preprocessing, data cleansing, GPT-4 tokenization, input formatting, prompt design, and optimization, as well as ethical considerations in prompt engineering. In the hands-on labs you?ll explore tasks such as formatting inputs for GPT-4, designing and optimizing prompts for business applications, and implementing multi-turn conversations with AI. You?ll work with innovative tools like the OpenAI API, OpenAI Codex, and OpenAI Playground, enhancing your learning experience while preparing you for integrating prompt engineering into your professional toolkit. By the end of this immersive course, you?ll have the skills necessary to effectively use prompt engineering in your software development projects. You'll be able to design, optimize, and test prompts for various business tasks, integrate GPT-4 with other software platforms, and address ethical concerns in AI deployment. Introduction to Prompt Engineering Overview of prompt engineering and its importance in AI applications Major applications of prompt engineering in business Common challenges faced in prompt engineering Overview of GPT-4 and its role in prompt engineering Key terminology and concepts in prompt engineering Getting Things Ready: Text Preprocessing and Data Cleansing Importance of data preprocessing in prompt engineering Techniques for text cleaning and normalization Tokenization and n-grams Stop word removal and stemming Regular expressions and pattern matching GPT-4 Tokenization and Input Formatting GPT-4 tokenization and its role in prompt engineering Understanding and formatting GPT-4 inputs Context windows and token limits Controlling response length and quality Techniques for handling out-of-vocabulary tokens Prompt Design and Optimization Master the skills to design, optimize, and test prompts for various business tasks. Designing effective prompts for different tasks Techniques for prompt optimization GPT-4 system and user parameters for controlling behavior Importance of prompt testing and iteration Best practices for prompt engineering in business applications Advanced Techniques and Tools in Prompt Engineering Learn advanced techniques and tools for prompt engineering and their integration in business applications. Conditional text generation with GPT-4 Techniques for handling multi-turn conversations Overview of tools for prompt engineering: OpenAI API, OpenAI Codex, and OpenAI Playground Integration of GPT-4 with other software platforms and tools Monitoring and maintaining prompt performance Code Generation and Testing with Prompt Engineering Develop the skills to generate, integrate, and test AI-generated code effectively, enhancing productivity and creativity in software development projects. Introduction to code generation with AI models like GPT-4 Designing prompts for code generation across programming languages Techniques for specifying requirements and constraints in prompts Generating and interpreting code snippets using AI-driven solutions Integrating generated code into existing projects and codebases Best practices for testing and validating AI-generated code Ethics and Responsible AI Understand the ethical implications of prompt engineering and the importance of responsible AI deployment in business. Ethical considerations in prompt engineering Bias in AI systems and its impact on prompt engineering Techniques to minimize bias and ensure fairness Best practices for responsible AI deployment in business applications Monitoring and addressing ethical concerns in prompt engineering

Duration 5 Days 30 CPD hours This course is intended for This course is intended for entry-level computer support professionals with a basic knowledge of computer hardware, software, and operating systems who wish to increase their knowledge and understanding of networking concepts and acquire the required skills to prepare for a career in network support or administration, or who wish to prepare for the CompTIA Network+ certification. CompTIA Network+ is the first certification IT professionals specializing in network administration and support should earn. Network+ is aimed at IT professionals with job roles such as network administrator, network technician, network installer, help desk technician, and IT cable installer. This course is also designed for students who are seeking the CompTIA Network+ certification and who want to prepare for the CompTIA Network+ N10-008 Certification Exam. Overview In this course, you will describe the major networking technologies and systems of modern networks and configure, manage, and troubleshoot modern networks. Explain the OSI and TCP/IP Models. Explain properties of network traffic. Install and configure switched networks. Configure IP networks. Install and configure routed networks. Configure and monitor ports and protocols. Explain network application and storage issues. Monitor and troubleshoot networks. Explain network attacks and mitigations. Install and configure security devices. Explain authentication and access controls. Deploy and troubleshoot cabling solutions. Implement and troubleshoot wireless technologies. Compare and contrast WAN technologies. Use remote access methods. Identify site policies and best practices. CompTIA's Network+ certification is a foundation-level certification designed for IT professionals with around one year of experience, whose job role is focused on network administration. The CompTIA Network+ exam will certify the successful candidate has the knowledge and skills required to troubleshoot, configure, and manage common network devices; establish basic network connectivity; understand and maintain network documentation; identify network limitations and weaknesses; and implement network security, standards, and protocols. The candidate will have a basic understanding of enterprise technologies, including cloud and virtualization technologies. The Official CompTIA© Network+© (Exam N10-008): will teach you the fundamental principles of installing, configuring, and troubleshooting network technologies and help you to progress a career in network administration. In this course, you will build on your existing user-level knowledge and experience with personal computer operating systems and networks to master the fundamental skills and concepts that you will need to use on the job in any type of networking career. Prerequisites CompTIA A+ Certification (Exams 220-1001 and 220-1002) 1 - Explaining the OSI and TCP/IP Models Topic A: Explain OSI Model Layers Topic B: Explain the TCP/IP Suite 2 - Explaining Properties of Network Traffic Topic A: Explain Media Types and Access Methods Topic B: Deploy Ethernet Standards Topic C: Configure and Monitor Network Interfaces 3 - Installing and Configuring Switched Networks Topic A: Install and Configure Hubs and Bridges Topic B: Install and Configure Switches Topic C: Compare and Contrast Network Topologies Topic D: Compare and Contrast Network Types 4 - Configuring IP Networks Topic A: Configure IPv4 Addressing Components Topic B: Test IP Interfaces with Command Line Tools Topic C: Configure IPv4 Subnets Topic D: Configure Private and Public IPv4 Addressing Schemes Topic E: Configure IPv6 Addressing Components Topic F: Configure DHCP Services 5 - Installing and Configuring Routed Networks Topic A: Explain Characteristics of Routing Topic B: Install and Configure Routers 6 - Configuring and Monitoring Ports and Protocols Topic A: Explain the Uses of Ports and Protocols Topic B: Use Port Scanners and Protocol Analyzers Topic C: Explain the Use of Name Resolution Services Topic D: Configure DNS and IPAM Services 7 - Explaining Network Application and Storage Services Topic A: Explain the Uses of Network Applications Topic B: Explain the Uses of Voice Services and Advanced Networking Devices Topic C: Explain the Uses of Virtualization and Network Storage Services Topic D: Summarize the Concepts of Cloud Services 8 - Monitoring and Troubleshooting Networks Topic A: Monitor Network Interfaces and Logs Topic B: Explain Network Troubleshooting Methodology Topic C: Troubleshoot Common Network Services Issues 9 - Explaining Networking Attacks and Mitigations Topic A: Summarize Common Networking Attacks Topic B: Explain the Characteristics of VLANs Topic C: Explain the Characteristics of NAT and Port Forwarding 10 - Installing and Configuring Security Devices Topic A: Install and Configure Firewalls and Proxies Topic B: Explain the Uses of IDS/IPS and UTM 11 - Explaining Authentication and Access Controls Topic A: Explain Authentication Controls and Attacks Topic B: Explain the Uses of Authentication Protocols and Directory Services Topic C: Explain the Uses of Port Security and NAC Topic D: Implement Network Device Hardening Topic E: Explain Patch Management and Vulnerability Scanning Processes 12 - Deploying and Troubleshooting Cabling Solutions Topic A: Deploy Structured Cabling Systems Topic B: Deploy Twisted Pair Cabling Solutions Topic C: Test and Troubleshoot Twisted Pair Cabling Solutions Topic D: Deploy Fiber Optic Cabling Solutions 13 - Implementing and Troubleshooting Wireless Technologies Topic A: Install and Configure Wireless Technologies Topic B: Troubleshoot Wireless Performance Issues Topic C: Secure and Troubleshoot Wireless Connectivity 14 - Comparing and Contrasting WAN Technologies Topic A: Compare and Contrast WAN Core Service Types Topic B: Compare and Contrast WAN Subscriber Service Types Topic C: Compare and Contrast WAN Framing Service Types Topic D: Compae and Contrast Wireless and IoT WAN Technologies 15 - Using Remote Access Methods Topic A: Use Remote Access VPNs Topic B: Use Remote Access Management Methods 16 - Identifying Site Policies and Best Practices Topic A: Manage Networks with Documentation and Diagrams Topic B: Summarize the Purposes of Physical Security Devices Topic C: Compare and Contrast Business Continuity and Disaster Recovery Concepts Topic D: Identify Policies and Best Practices

This course is designed to explore creative potential and hone artistic skills using ChatGPT. It covers how to use ChatGPT, generate ideas, research for a novel, create comics, and use other AI tools. Additionally, the course introduces ChatGPT for storytelling by providing prompts and refining its output to generate story ideas and characters.

About Course ChatGPT CrashCourse This course will teach you the basics of ChatGPT, a powerful AI language model that you can use for a variety of tasks, including customer service, content creation, and education. Unlock the Power of AI Conversations with ChatGPT CrashCourse. Are you ready to take your conversations to the next level? Join our Course and learn how to use this powerful AI language model to create engaging and informative conversations. What is ChatGPT? ChatGPT is a large language model chatbot developed by OpenAI. Launched in November 2022, it's based on the GPT-3.5 and GPT-4 language models, and is capable of carrying on conversations with humans in a way that simulates real human interaction. One can use this tool for a variety of purposes, including: Having casual conversations on a variety of topics Getting help with creative writing tasks Learning about new things In this course, you will: Learn the basics of ChatGPT Understand how it works Explore its different applications Get hands-on experience using ChatGPT See real-world examples of how ChatGPT is being used By the end of this course, you will be able to: Use ChatGPT to create chatbots Generate text, translate languages, and answer questions Automate tasks and improve your productivity Apply ChatGPT to your own projects This course is perfect for anyone who wants to learn more about AI conversations or who wants to use ChatGPT to improve their work or personal life. Sign up today and start unlocking the power of ChatGPT! What Will You Learn? Explain what ChatGPT is and how it works Identify the different applications of ChatGPT Get started with ChatGPT and create your own account Use ChatGPT for productivity tasks, such as writing emails, generating reports, and creating presentations Apply ChatGPT to your own projects Course Content Introduction to ChatGPT What is ChatGPT? ChatGPT for Productivity ChatGPT for Office and Administrative Management ChatGPT for regular tasks ChatGPT for Marketing ChatGPT for Marketing ChatGPT prompts Real-world examples of how ChatGPT is being used Prompt engineering More into ChatGPT Lesson - One Lesson - Two Lesson - Three Lesson - Four Lesson - Five Lesson - Six Lesson - Seven Lesson - Eight Lesson - Nine Lesson - Ten Lesson - Eleven Lesson - Twelve Lesson - Thirteen Lesson - Fourteen Lesson - Fifteen Lesson - Sixteen Lesson - Seventeen Lesson - Eighteen Lesson - Nineteen Lesson - Twenty A course by Xpert Learning RequirementsNo specific Requirement. Audience This course is suitable for anyone who is interested in learning about ChatGPT or who wants to use it to improve their productivity. No prior knowledge of AI or ChatGPT is required. Audience This course is suitable for anyone who is interested in learning about ChatGPT or who wants to use it to improve their productivity. No prior knowledge of AI or ChatGPT is required.

This course starts with the basics of data science and gradually moves towards explaining the concepts of machine learning and various data science algorithms.

🚀 AI & Project Management Masterclass 🚀 Curious about AI in project management but not sure where to start? This fun, no-nonsense masterclass, led by Nadege Minois, will guide you through 7 key questions to ask before diving into AI. Learn how to integrate AI smoothly, avoid common pitfalls, and understand the ethics of using it in your projects—all without needing to code! Perfect for project managers ready for the future. 💡 Ready to level up? Join us and find out if AI is the game-changer your projects need! 👉 Book your spot now!