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Duration 4 Days 24 CPD hours This course is intended for This course is for technical professionals who need to know how to deploy open source intrusion detection systems (IDS) and intrusion prevention systems (IPS), and how to write Snort rules. Security administrators Security consultants Network administrators System engineers Technical support personnel Channel partners and resellers Overview After taking this course, you should be able to: Describe Snort technology and identify resources available for maintaining a Snort deployment Install Snort on a Linux-based operating system Describe the Snort operation modes and their command-line options Describe the Snort intrusion detection output options Download and deploy a new rule set to Snort Describe and configure the snort.conf file Configure Snort for inline operation and configure the inline-only features Describe the Snort basic rule syntax and usage Describe how traffic is processed by the Snort engine Describe several advanced rule options used by Snort Describe OpenAppID features and functionality Describe how to monitor Snort performance and how to tune rules The Securing Cisco Networks with Open Source Snort (SSFSNORT) v2.1 course shows you how to deploy a network intrusion detection system based on Snort. You?ll learn how to install, configure, operate, and manage a Snort system, rules writing with an overview of basic options, advanced rules writing, how to configure Pulled Pork, and how to use OpenAppID to provide protection of your network from malware. You will learn techniques of tuning and performance monitoring, traffic flow through Snort rules, and more Course outline Introduction to Snort Technology Snort Installation Snort Operation Snort Intrusion Detection Output Rule Management Snort Configuration Inline Operation and Configuration Snort Rule Syntax and Usage Traffic Flow Through Snort Rules Advanced Rule Options OpenAppID Detection Tuning Snort Additional course details: Nexus Humans Cisco Securing Cisco Networks with Open Source Snort v2.1 (SSFSNORT) 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 Cisco Securing Cisco Networks with Open Source Snort v2.1 (SSFSNORT) 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.

Duration 5 Days 30 CPD hours This course is intended for This course is designed for network and software engineers interested in automation and programmability and who hold job roles such as: Account manager Consulting systems engineer Network administrator Network engineer Network manager Sales engineer Systems engineer Technical solutions architect Wireless design engineer Wireless engineer Overview This course will help you: Gain the high-demand knowledge and skills to implement automation, streamline container orchestration, and enhance scalability Learn the skills to maximize the lightweight design of containers to scale more quickly and allow more responsiveness to website traffic load Prepare for the 300-910 DEVOPS exam What to expect in the exam The 300-910 DEVOPS exam certifies your knowledge and skills with DevOps. Key DevOps practices include deployment automation that enables configuration, management, and scalability of cloud microservices and infrastructure processes on Cisco platforms. This course teaches you how to automate application deployment, enable automated configuration, enhance management, and improve scalability of cloud microservices and infrastructure processes on Cisco© platforms. You will also learn how to integrate Docker and Kubernetes to create advanced capabilities and flexibility in application deployment. This course prepares you for the 300-910 Implementing DevOps Solutions and Practices Using Cisco Platforms (DEVOPS) certification exam. Course Outlines ITRODUCING THE DEVOPS MODEL INTRODUCING CONTAINERS PACKAGING AN APPLICATION USING DOCKER DEPLOYING A MULTITIER APPLICATION INTRODUCING CI/CD BUILDING THE DEVOPS FLOW VALIDATING THE APPLICATION BUILD PROCESS BUILDING AN IMPROVED DEPLOYMENT FLOW EXTENDING DEVOPS PRACTICES TO THE ENTIRE INFRASTRUCTURE IMPLEMENTING ON-DEMAND TEST ENVIRONMENTS AT THE INFRASTRUCTURE LEVEL MONITORING IN NETDEVOPS ENGINEERING FOR VISIBILITY AND STABILITY SECURING DEVOPS WORKFLOWS EXPLORING MULTICLOUD STRATEGIES EXAMINING APPLICATION AND DEPLOYMENT ARCHITECTURES DESCRIBING KUBERNETES INTEGRATING MULTIPLE DATA CENTER DEPLOYMENTS WITH KUBERNETES MONITORING AND LOGGING IN KUBERNETES Additional course details: Nexus Humans Cisco Implementing DevOps Solutions and Practices Using Cisco Platforms (DevOps) 1.0 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 Cisco Implementing DevOps Solutions and Practices Using Cisco Platforms (DevOps) 1.0 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.

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for system and network administrators responsible for installation, setup, configuration, and administration of BIG-IP DNS systems. This course gives networking professionals a functional understanding of the BIG-IP DNS system as it is commonly used. The course covers configuration and ongoing management of the BIG-IP DNS system, and includes a combination of lecture, discussion, and hands-on labs. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP Configuration Leveraging F5 Support Resources and Tools Provision the BIG-IP System and Confirm Network Configuration Module 2: Introducing the Domain Name System (DNS) and BIG-IP DNS Understanding the Domain Name System (DNS) Reviewing the Name Resolution Process Implementing BIG-IP DNS Using DNS Resolution Diagnostic Tools Module 3: Accelerating DNS Resolution Introducing DNS Resolution with BIG-IP DNS BIG-IP DNS Resolution Decision Flow Configuring BIG-IP DNS Listeners Resolving DNS Queries in the Labs (Lab Zone Records) Load Balancing Queries to a DNS Server Pool Accelerating DNS Resolution with DNS Cache Accelerating DNS Resolution with DNS Express Introducing Wide IPs Using Other Resolution Methods with BIG-IP DNS Integrating BIG-IP DNS into Existing DNS Environments Module 4: Implementing Intelligent DNS Resolutions Introducing Intelligent DNS Resolution Identifying Physical Network Components Identifying Logical Network Components Collecting Metrics for Intelligent Resolution Configuring Data Centers Configuring a BIG-IP DNS System as a Server Configuring a BIG-IP LTM System as a Server Establishing iQuery Communication between BIG-IP Systems Configuring a Non-F5 Server Defining Links and Routers Configuring Wide IP Pools Configuring Wide IPs Managing Object Status Using the Traffic Management Shell (TMSH) Module 5: Using LDNS Probes and Metrics Introducing LDNS Probes and Metrics Types of LDNS Probes Excluding an LDNS from Probing Configuring Probe Metrics Collection Module 6: Load Balancing Intelligent DNS Resolution Introducing Load Balancing on BIG-IP DNS Using Static Load Balancing Methods Round Robin Ratio Global Availability Static Persist Other Static Load Balancing Methods Using Dynamic Load Balancing Methods Round Trip Time Completion Rate CPU Hops Least Connections Packet Rate Kilobytes per Second Other Dynamic Load Balancing Methods Virtual Server Capacity Virtual Server Score Using Quality of Service Load Balancing Persisting DNS Query Responses Configuring GSLB Load Balancing Decision Logs Using Manual Resume Using Topology Load Balancing Module 7: Monitoring Intelligent DNS Resources Exploring Monitors Configuring Monitors Assigning Monitors to Resources Monitoring Best Practices Module 8: Advanced BIG-IP DNS Topics Implementing DNSSEC Setting Limits for Resource Availability Using iRules with Wide IPs Introducing Other Wide IP Types Implementing BIG-IP DNS Sync Groups Module 9: Final Configuration Projects Final Configuration Projects

Duration 5 Days 30 CPD hours This course is intended for Technology ConsultantSystem AdministratorSystem ArchitectHelp Desk / COE Support Overview Explain the architecture of SAP NetWeaver AS JavaStart and stop SAP NetWeaver AS JavaCarry out basic configurations for SAP NetWeaver AS JavaClassify network security conceptsSet up SSL encryption for SAP NetWeaver AS JavaExplain the architecture of the User Management EngineConfigure the User Management EngineCarry out user and authorization maintenanceUnderstand and change the standard logon procedure of SAP NetWeaver AS JavaMaintain destinations and the JCo RFC ProviderUnderstand the architecture and the tasks of the SAP NetWeaver Development InfrastructureExplain the process flow of the development process using the SAP NetWeaver Development InfrastructureSpecify the options for monitoring SAP NetWeaver AS JavaConnect SAP NetWeaver AS Java to a central Monitoring systemDisplay Monitoring and logging data using the SAP NetWeaver AdministratorImplement corrections for SAP NetWeaver AS Java In this course, students learn how to explain the architecture of SAP NetWeaver AS Java, carry out basic configurations for SAP NetWeaver AS Java, and much more. Fundamental Concepts of Java Describing the Fundamental Concepts of Java Describing the Architecture of the SAP NetWeaver Application Server (SAP NetWeaver AS) Outlining the Java Cluster Architecture Describing the Internal Structure of SAP NetWeaver AS for Java SAP NetWeavear AS for Java Start and Stop Procedures Starting and Stopping Procedures in SAP NetWeaver AS for Java Evaluating the Tools for Starting and Stopping an SAP System Evaluating Load Balancing Options in SAP NetWeaver AS for Java Operating the Java Startup and Control Framework Analyzing the Logs of Start and Stop Processes in SAP NetWeaver AS for Java Basic Configuration of SAP NetWeaver AS for Java Identifying the Administration Tools Used in Configuration Maintaining the Basic Configuration of SAP NetWeaver AS for Java with the Config Tool Configuring SAP NetWeaver AS for Java with SAP NetWeaver Administrator Configuring the Properties of the Central Services Instance Administering the Internet Communication Manager (ICM) Process Infrastructure Security Describing Network Security Setting Up the Secure Sockets Layer (SSL) User and Authorization Administration Configuring the SAP User Management Engine (UME) Maintaining Users and Groups Managing Java Authorization Administrating Special Principles Configuring the Logon Procedure in SAP NetWeaver AS for Java Java Connectors and Destinations Creating Connections to Other Systems Creating Connections to Other Systems with J2EE Connector Architecture (JCA) Change Management and Software Logistics Structuring the Java Development Approach Describing the Components of SAP NetWeaver Development Infrastructure Developing and Releasing Java Changes with SAP NetWeaver Development Infrastructure Transporting Java Developments Monitoring Monitoring SAP NetWeaver AS for Java Connecting to a Central Monitoring System (CEN) Configuring Availability Monitoring Configuring the Log and Trace Files Monitoring a System with SAP Solution Manager Software Maintenance Preparing for Software Maintenance Describing Java Support Packages, Stacks, and Patches Deploying Corrections with Software Update Manager (SUM) in SAP NetWeaver AS for Java Deploying Java Archives with Alternative Tools Outlining the Backup Strategy in SAP NetWeaver AS for Java

Duration 3 Days 18 CPD hours This course is intended for This course is primarily for Developers, Developer Consultants, Help Desk/COE Support, Program/Project Manager, System Administrators, System Architects, and Technology Consultants. Overview Explaining scenarios and processes in SAP NetWeaver process integrationIdentify the technical communications modes and processesExplain business scenarios and the business hierarchy used by SAP In this course, students learn how to explain scenarios & processes in SAP NetWeaver process integration. They learn how to identify the technical communications modes & processes, as well as explain business scenarios & the business hierarchy used by SAP. Integration Basics Explaining Scenarios and Processes in SAP NetWeaver Process Integration Explaining Technical Communication Modes and Processes Explaining Business Scenarios Classical System-to-System Communication Communicating Between Two SAP Systems Communicating Between Two Non-SAP Systems Communicating Using Business Application Programming Interfaces (BAPIs) Communicating Using IDocs Processing IDocs Web Services Processing HTTP Requests Describing Simple Object Access Protocol (SOAP) Basics Analyzing Different Web Services Describing Inside-Out and Outside-In Web Services Explaining Service Oriented Architecture (SOA) Integration Technologies: On-Premise Process Integration (Design Time) Processing Integration Middleware Tools (PI Dual Stack) Installing Dual-Stack or Single-Stack Options Securing Objects Creating PI Objects Explaining Design Objects Modeling PI Scenarios Creating an Integration Scenario Configuring an Integration Scenario Displaying the Configuration Objects in the Integration Directory Integration Technologies: On-Premise Process Integration (Runtime) Connecting SAP NetWeaver PI with Proxies Creating File Adapters Executing Configuration Objects Monitoring Tools Integration Technologies: On-Premise Process Orchestration (PO) Explaining Business Process Management (BPM) Explaining Process Orchestration (PO) Explaining Advanced Adapter Engine Extended (AEX) Explaining Business Rules Management (BRM) Integration Technologies: On Demand Explaining SAP HANA Cloud Integration (HCI) Describing Eclipse-Based Access Using the Web UI to Access HCI SAP NetWeaver Gateway Explaining the SAP NetWeaver Gateway Scenario Explaining the SAP NetWeaver Gateway Development View Accessing an Open Data (OData) Service Additional course details: Nexus Humans BIT100 SAP NetWeaver Integration Technology Overview 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 BIT100 SAP NetWeaver Integration Technology Overview 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.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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.

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Duration 3 Days 18 CPD hours This course is intended for This course is appropriate for anyone needing to interface with an Oracle database or those needing a general understanding of Oracle database functionality. That would include end users, business analysts, application developers and database administrators. Overview Working in a hands-on learning environment led by our expert pracitioner you'll learn how to: Add Data, Retrieve, Sort and Organize a SQL Database Combine Data, Set Operators and Subqueries Manipulate Data and Data Definition Languages in SQL Work with Data Dictionary Views and Create Sequences, Indexes and Views Use Database Objects and Subqueries Perform Data and access control Perform other Advanced Level Database operations. Oracle 19C SQL Programming Fundamentals Is a three-day, hands-on course designed to equip you with the fundamental skills needed to set up, run and manage SQL databases using Oracle Database Technology. You will also be discovering all the tools and concepts required to organize data efficiently. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment, guided by our expert team, attendees will develop a practical approach to Oracle Database Technology. Throughout the course, you will learn the key elements of a database, and the way Oracle systems facilitate their induction in the system. You?ll also learn the tools and strategies you can implement to store, retrieve, compare and organize data according to your requirements. You?ll also explore the process of creating simple to complex reports from existing data. By the end of this course, you will also have hands-on knowledge of SQL systems that are required to proceed to other advanced to professional programs. Adding Data, Retrieving, Sorting and Organizing a SQL Database The building blocks of a database. How to add data to the database. The process of retrieving data using SQL functions. Multiple methods of sorting and organizing data. Using SQL functions to get the required simple to complex output. Various strategies for using functions and conditions to organize data. Combining Data, Set Operators And Subqueries Consolidating data using multiple functions and group operators. Fetching intelligent data reports using simple functions. Fetching data from multiple sources in the tables. Using Subqueries to compile data as required. Using Set operators to create smart data reports. Data Manipulation and Data Definition Languages in SQL Describing and managing data transaction using Data Definition Language. Categorize and review data tables using Data Definition Language. Data Dictionary Views and Creating Sequences, Indexes and Views How to manage and query Data Dictionary Views. The process of creating and using Sequences. How to create various types of Synonyms and Indexes. Creating simple and complex views and retrieving data. Understanding and using Database Objects and Subqueries Core concept and application of Schema Objects. Fetching required data with Subqueries. Using Subqueries to organize Data in SQL. Data and access control Assigning and revoking data access. Managing data access control according to user levels. Performing Advanced Level Database operations. Using advanced functions and performing data queries. Creating and managing time zone-based databases.

Duration 5 Days 30 CPD hours This course is intended for This course is for wireless engineers who work in the following roles: Consulting systems engineer Network administrator Network engineer Network manager Sales engineer Systems engineer Technical solutions architect Wireless design engineer Wireless engineer Overview After taking this course, you should be able to: Describe and implement a Cisco-recommended structured design methodology Describe and implement industry standards, amendments, certifications, and Requests For Comments (RFCs) Describe and implement Cisco enhanced wireless features Describe and implement the wireless design process Describe and implement specific vertical designs Describe and implement site survey processes Describe and implement network validation processes The Designing Cisco Enterprise Wireless Networks (ENWLSD) v1.1 course gives you the knowledge you need to design Cisco© wireless networks. The course covers design specifics from scenario design concepts through the installation phase and into post-deployment validation.This course, including the self-paced material, helps prepare you to take the exam, Designing Cisco Enterprise Wireless Networks (300-425 ENWLSD), which leads to to the new CCNP© Enterprise and Cisco Certified Specialist ? Enterprise Wireless Design certifications. Describing and Implementing a Structured Wireless Design Methodology Importance of Planning Wireless Design with a Structured Methodology Cisco Structured Design Model Cisco Design Guides and Cisco Validated Designs for Wireless Networks Role of the Project Manager When Designing Wireless Networks Describing and Implementing Industry Protocols and Standards Wireless Standards Bodies Institute of Electrical and Electronics Engineers (IEEE) 802.11 Standard and Amendments Wi-Fi Alliance (WFA) Certifications Relevant Internet Engineering Task Force (IETF) Wireless RFCs Practice Activity Describing and Implementing Cisco Enhanced Wireless Features Hardware and Software Choices for a Wireless Network Design Cisco Infrastructure Settings for Wireless Network Design Cisco Enhanced Wireless Features Examining Cisco Mobility and Roaming Mobility and Intercontroller Mobility in a Wireless Network Optimize Client Roaming in a Wireless Network Cisco Workgroup Bridge (WGB) and WGB Roaming in a Wireless Network Describing and Implementing the Wireless Design Process Overview of Wireless Design Process Meet with the Customer to Discuss the Wireless Network Design Customer Information Gathering for a Wireless Network Design Design the Wireless Network Deployment of the Wireless Network Validation and Final Adjustments of the Wireless Network Wireless Network Design Project Documents and Deliverables Describing and Implementing Specific Vertical Designs Designs for Wireless Applications Wireless Network Design Within the Campus Extend Wireless Networks to the Branch Sites Examining Special Considerations in Advanced Wireless Designs High-Density Designs in Wireless Networks Introducing Location and Cisco Connected Mobile Experiences (CMX) Concepts Design for Location FastLocate and HyperLocation Bridges and Mesh in a Wireless Network Design Redundancy and High Availability in a Wireless Network Describing and Implementing the Site Survey Processes Site Survey Types Special Arrangements Needed for Site Surveys Safety Aspects to be Considered During Site Surveys Site Survey Tools in Cisco Prime Infrastructure Third-Party Site Survey Software and Hardware Tools Describing and Implementing Wireless Network Validation Processes Post-installation Wireless Network Validation Making Post-installation Changes to a Wireless Network Wireless Network Handoff to the Customer Installation Report