1098 Operator courses

Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Network administrators Network engineers with little or no programming or Python experience Network managers Systems engineers Overview After taking this course, you should be able to: Create a Python script Describe data types commonly used in Python coding Describe Python strings and their use cases Describe Python loops, conditionals, operators, and their purposes and use cases Describe Python classes, methods, functions, namespaces, and scopes Describe the options for Python data manipulation and storage Describe Python modules and packages, their uses, and their benefits Explain how to manipulate user input in Python Describe error and exception management in Python Describe Python code debugging methods The Programming for Network Engineers (PRNE) v2.0 course is designed to equip you with fundamental skills in Python programming. Through a combination of lectures and lab experience in simulated network environments, you will learn to use Python basics to create useful and practical scripts with Netmiko to retrieve data and configure network devices. Upon completion of this course, you should have a basic understanding of Python, including the knowledge to create, apply, and troubleshoot simple network automation scripts. Course Outline Introducing Programmability and Python for Network Engineers Scripting with Python Examining Python Data Types Manipulating Strings Describing Conditionals, Loops, and Operators Exploring Classes, Methods, Functions, Namespaces, and Scopes Exploring Data Storage Options Exploring Python Modules and Packages Gathering and Validating User Input Analyzing Exceptions and Error Management Examining Debugging Methods

Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Network administrators Network engineers with little or no programming or Python experience Network managers Systems engineers Overview After taking this course, you should be able to: Create a Python script Describe data types commonly used in Python coding Describe Python strings and their use cases Describe Python loops, conditionals, operators, and their purposes and use cases Describe Python classes, methods, functions, namespaces, and scopes Describe the options for Python data manipulation and storage Describe Python modules and packages, their uses, and their benefits Explain how to manipulate user input in Python Describe error and exception management in Python Describe Python code debugging methods The Programming for Network Engineers (PRNE) v2.0 course is designed to equip you with fundamental skills in Python programming. Through a combination of lectures and lab experience in simulated network environments, you will learn to use Python basics to create useful and practical scripts with Netmiko to retrieve data and configure network devices. Upon completion of this course, you should have a basic understanding of Python, including the knowledge to create, apply, and troubleshoot simple network automation scripts. Course Outline Introducing Programmability and Python for Network Engineers Scripting with Python Examining Python Data Types Manipulating Strings Describing Conditionals, Loops, and Operators Exploring Classes, Methods, Functions, Namespaces, and Scopes Exploring Data Storage Options Exploring Python Modules and Packages Gathering and Validating User Input Analyzing Exceptions and Error Management Examining Debugging Methods Course Summary

Duration 5 Days 30 CPD hours This course is intended for This course is intended for new and experienced programmers that want to learn how to write and troubleshoot Python code. This is the Microsoft recommended course for preparing for the 98-381 test. Previous programming experience is not required but recommended. Overview By the end of this course, you will be able to: Create Operations using Data Types and Operators Create Control Flow Operations Create Input and Output Operations Write and Document code to solve a specified problem Troubleshoot Problems and Write Error Handling Operations Perform Operations Using Modules and Tools This five-day instructor-led course (three-day boot camp) is intended for students who want to learn how to write, debug and document Python code Module 1: Perform Operations Using Data Types and Operators Assign data types to variables Perform data and data type operations Perform Arithmetic, Comparison and Logical Operations Review Module 2: Control Flow with Decisions and Loops Construct and analyze code segments that use branching statements Construct and analyze code segments that perform iterations Review Module 3: Perform Input and Output Operations Create Python code segments that perform file input and output operations Create Python code segments that perform console input and output operations Review Module 4: Document and Structure Code Construct and analyze code segments Document code segments using comments and documentation strings Review Module 5: Perform Troubleshooting and Error Handling Analyze, Detect and Fix code segments that have errors Analyze and construct code segments that handle exceptions Review Module 6: Perform Operations Using Modules and Tools Use Built-In Modules to perform basic operations Use Built-In Modules to perform complex operations Review

Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Network administrators Network engineers with little or no programming or Python experience Network managers Systems engineers Overview After taking this course, you should be able to: Create a Python script Describe data types commonly used in Python coding Describe Python strings and their use cases Describe Python loops, conditionals, operators, and their purposes and use cases Describe Python classes, methods, functions, namespaces, and scopes Describe the options for Python data manipulation and storage Describe Python modules and packages, their uses, and their benefits Explain how to manipulate user input in Python Describe error and exception management in Python Describe Python code debugging methods The Programming for Network Engineers (PRNE) v2.0 course is designed to equip you with fundamental skills in Python programming. Through a combination of lectures and lab experience in simulated network environments, you will learn to use Python basics to create useful and practical scripts with Netmiko to retrieve data and configure network devices. Upon completion of this course, you should have a basic understanding of Python, including the knowledge to create, apply, and troubleshoot simple network automation scripts. Course outline Introducing Programmability and Python for Network Engineers Scripting with Python Examining Python Data Types Manipulating Strings Describing Conditionals, Loops, and Operators Exploring Classes, Methods, Functions, Namespaces, and Scopes Exploring Data Storage Options Exploring Python Modules and Packages Gathering and Validating User Input Analyzing Exceptions and Error Management Examining Debugging Methods Course Summary Lab outline Execute Your First Python Program Use the Python Interactive Shell Explore Foundation Python Data Types Explore Complex Python Data Types Use Standard String Operations Use Basic Pattern Matching Reformat MAC Addresses Use the if-else Construct Use for Loops Use while Loops Create and Use Functions Create and Use Classes Use the Python main() Construct Traverse the File Structure Read Data in Comma-Separated Values (CSV) Format Read, Store, and Retrieve Data in XML Format Read, Store, and Retrieve Date in JavaScript Object Notation (JSON) Format Read, Store, and Retrieve Data in a Raw or Unstructured Format Import Modules from the Python Standard Library Import External Libraries Create a Python Module Prompt the User for Input Use Command-Line Arguments Manage Exceptions with the try-except Structure Manage Exceptions with the try-except-finally Structure Use Assertions Use Simple Debugging Methods Use the Python Debugger Code a Practical Debugging Script

Duration 2 Days 12 CPD hours This course is intended for Experienced system operators, administrators, and integrators responsible for managing and maintaining VMware Horizon solutions Overview By the end of the course, you should be able to meet the following objectives: Implement a structured approach to troubleshooting Resolve common issues that occur in a VMware Horizon environment Troubleshoot issues with linked and instant clones Configure the Windows client Identify the correct log level for gathering logs Optimize protocols for best end-user experience This two-day course builds your skills in resolving common issues that occur in a VMware Horizon© environment. You engage in a series of lab exercises to bring existing environment issues to resolution. The exercises mirror real-world troubleshooting use cases. These exercises equip learners with the knowledge and practical skills to manage typical challenges faced by virtual desktop administrators and operators. Course Introduction Introductions and course logistics Course objectives Overview of Virtual Desktop Troubleshooting Structured approach to troubleshooting configuration and operational problems Applying troubleshooting methods Documenting the steps to resolving the problem Command-Line Tools and Backup Options Using command-line tools Backing-up and restoring VMware Horizon databases Troubleshooting Horizon Linked Clone Desktops Describe the components that make up a VMware Horizon desktop Explain how the View Agent Direct-Connection plug-In is useful for diagnosing problems Highlight the best practice for optimizing a VMware Horizon desktop Troubleshoot common problems with VMware Horizon desktops Troubleshooting Instant Clone Discuss how instant clones are created Discuss what gets logged when an instant clone is created Discuss the keywords to look for in the logs when troubleshooting instant clones Discuss how to troubleshoot problems with instant clones Windows Client Correctly configure the Windows Client Identify the correct log level for gathering logs Enable the required SSL configuration level for the environment Ports and Protocols Discuss the key ports on a Horizon Environment Discuss protocols used in the Horizon Environment Understand the benefit of optimizing Blast Become familiar with the optimization features for Blast Implement GPO changes for Blast Become familiar with the causes for Black Screens Discuss how to troubleshoot Black Screen problems Identify problems encountered when applying GPOs Discuss how to troubleshoot GPO-related problems Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Horizon 8: Virtual Desktop Troubleshooting 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 VMware Horizon 8: Virtual Desktop Troubleshooting 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 2 Days 12 CPD hours This course is intended for This course is intended for network administrators, operators, and engineers responsible for managing the normal day-to-day operation and administration of a BIG-IP application delivery network. This course presents the prerequisite knowledge for many other of F5's BIG-IP instructor-led training courses. Overview Getting started with the BIG-IP system Traffic processing with BIG-IP Local Traffic Manager (LTM) Using the TMSH (TMOS Shell) command line interface Using NATs and SNATs Monitoring application health and managing object status Modifying traffic behavior with profiles, including SSL offload and re-encryption Modifying traffic behavior with persistence, including source address affinity and cookie persistence Troubleshooting the BIG-IP system, including logging (local, high-speed, and legacy remote logging), and using tcpdump User roles and administrative partitions vCMP concepts Customizing application delivery with iRules This course gives network administrators, network operators, and network engineers a functional understanding of the BIG-IP system as it is commonly deployed in an application delivery network. The course introduces students to the BIG-IP system, its configuration objects, how it processes traffic, and how typical administrative and operational activities are performed. The course includes lecture, hands-on labs, interactive demonstrations, and discussions. Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Configuring the Management Interface Activating the Software License Provisioning Modules and Resources Importing a Device Certificate Specifying BIG-IP Platform Properties Configuring the Network Configuring Network Time Protocol (NTP) Servers Configuring Domain Name System (DNS) Settings Configuring High Availability Options Archiving the BIG-IP Configuration Leveraging F5 Support Resources and Tools Traffic Processing Building Blocks Identifying BIG-IP Traffic Processing Objects Configuring Virtual Servers and Pools Load Balancing Traffic Viewing Module Statistics and Logs Using the Traffic Management Shell (TMSH) Understanding the TMSH Hierarchical Structure Navigating the TMSH Hierarchy Managing BIG-IP Configuration State and Files BIG-IP System Configuration State Loading and Saving the System Configuration Shutting Down and Restarting the BIG-IP System Saving and Replicating Configuration Data (UCS and SCF) Using NATs and SNATs Address Translation on the BIG-IP System Mapping IP Addresses with NATs Solving Routing Issues with SNATs Configuring SNAT Auto Map on a Virtual Server Monitoring for and Mitigating Port Exhaustion Monitoring Application Health Introducing Monitors Types of Monitors Monitor Interval and Timeout Settings Configuring Monitors Assigning Monitors to Resources Managing Pool, Pool Member, and Node Status Using the Network Map Modifying Traffic Behavior with Profiles Introducing Profiles Understanding Profile Types and Dependencies Configuring and Assigning Profiles Introducing SSL Offload and SSL Re-Encryption Managing Object State Modifying Traffic Behavior with Persistence Understanding the Need for Persistence Introducing Source Address Affinity Persistence Managing Object State Administering the BIG-IP System Configuring Logging Legacy Remote Logging Introducing High Speed Logging (HSL) High-Speed Logging Filters HSL Configuration Objects Configuring High Speed Logging Using TCPDUMP on the BIG-IP System Leveraging the BIG-IP iHealth System Viewing BIG-IP System Statistics Defining User Roles and Administrative Partitions Leveraging vCMP Configuring High Availability Introducing Device Service Clustering (DSC) Preparing to Deploy a DSC Configuration Configuring DSC Communication Settings Establishing Device Trust Establishing a Sync-Failover Device Group Synchronizing Configuration Data Exploring Traffic Group Behavior Understanding Failover Managers and Triggers Achieving Stateful Failover with Mirroring

Duration 5 Days 30 CPD hours This course is intended for This introductory-level Python course is geared for experienced web developers new to Python who want to use Python and Django for full stack web development projects. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Develop full-stack web sites based on content stored in an RDMS Use python data types appropriately Define data models Understand the architecture of a Django-based web site Create Django templates for easy-to-modify views Map views to URLs Take advantage of the built-in Admin interface Provide HTML form processing Geared for experienced web developers new to Python, Introduction to Full Stack Web Development with Python and Django is a five-day hands-on course that teaches students how to develop Web applications using the Django framework. Students will explore the basics of creating basic applications using the MVC (model-view-controller) design pattern, as well as more advanced topics such as administration, session management, authentication, and automated testing. This comprehensive, practical course provides an in-depth exploration of working with the programming language, not an academic overview of syntax and grammar. Students will immediately be able to use Python to complete tasks in the real world. The Python Environment Starting Python Using the interpreter Running a Python script Getting help Editors and IDEs Getting Started Using variables Built in functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control Conditional expressions Relational and Boolean operators while loops Lists and Tuples About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Working with Files File overview The with statement Opening a file Reading/writing files Dictionaries and Sets About dictionaries Creating and using dictionaries About sets Creating and using sets Functions Returning values Function parameters Variable Scope Sorting with functions Errors and Exception Handling Exception overview Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages Creating Modules The import statement Module search path Creating packages Classes About OO programming Defining classes Constructors Properties Instance methods and data Class/static methods and data Inheritance Django Architecture Django overview Sites and apps Shared configuration Minimal Django layout Built in flexibility Configuring a Project Executing manage.py Starting the project Generating app files App configuration Database setup The development server Using cookiecutter Creating models Defining models Related objects SQL Migration Simplel model access Login for Nothing and Admin for Free Setting up the admin user Using the admin interface Views What is a view HttpResponse URL route configuration Shortcut: get_object_or_404() Class-based views Templates About templates Variable lookups The url tag Shortcut: render() Querying Models QuerySets Field lookups Chaining filters Slicing QuerySets Related fields Q objects Advanced Templates Use Comments Inheritance Filters Escaping HTML Custom filters Forms Forms overview GET and POST The Form class Processing the form Widgets Validation Forms in templates Automated Testing Why create tests? When to create tests Using Django's test framework Using the test client Running tests Checking code coverage

Duration 2 Days 12 CPD hours This course is intended for This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. An Overview of Python Why Python? Python in the Shell Python in Web Notebooks (iPython, Jupyter, Zeppelin) Demo: Python, Notebooks, and Data Science Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences, Arrays, Dictionaries and Sets About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with Dictionaries Working with Sets Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Functions Defining functions Parameters Global and local scope Nested functions Returning values Essential Demos Sorting Exceptions Importing Modules Classes Regular Expressions The standard library Math functions The string module Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Python and Data Science Data Science Essentials Pandas Overview NumPy Overview SciKit Overview MatPlotLib Overview Working with Python in Data Science Additional course details: Nexus Humans Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 The course content is aimed at operators of devices running the Junos OS in a NOC environment. These operators include network engineers, administrators, support personnel, and reseller support personnel. Overview After successfully completing this course, you should be able to: Reduce the time it takes to identify and isolate the root cause of an issue impacting your network. Gain familiarity with Junos products as they pertain to troubleshooting. Become familiar with online resources valuable to Junos troubleshooting. Gain familiarity with Junos tools used in troubleshooting. Identify and isolate hardware issues. Troubleshoot problems with the control plane. Troubleshoot problems with interfaces and other data plane components. Describe the staging and acceptance methodology. Troubleshoot routing protocols. Describe how to monitor your network with SNMP, RMON, Junos Traffic Vision (formerly known as JFlow), and port mirroring. Become familiar with JTAC procedures. This instructor-led four-day course is designed to provide introductory troubleshooting skills for engineers in a network operations center (NOC) environment. Chapter 1: Course Introduction Course Introduction Chapter 2: Troubleshooting as a Process Before You Begin The Troubleshooting Process Challenging Network Issues The Troubleshooting Process Lab Chapter 3: Junos Product Families The Junos OS Control Plane and Data Plane Field-Replaceable Units Junos Product Families Lab: Identifying Hardware Components Chapter 4: Troubleshooting Toolkit Troubleshooting Tools Best Practices Lab: Using Monitoring Tools and Establishing a Baseline Chapter 5: Hardware and Environmental Conditions Hardware Troubleshooting Overview Memory and Storage Boot Monitoring Hardware-Related System Logs Chassis and Environmental Monitoring Lab: Monitoring Hardware and Environmental Conditions Chapter 6: Control Plane Control Plane Review System and User Processes Monitoring Routing Tables and Protocols Monitoring Bridging Monitoring the Address Resolution Protocol Lab: Control Plane Monitoring and Troubleshooting Chapter 7: Control Plane Protection Protection Overview DDOS Protection Loopback Filter Lab: Control Plane Monitoring and Troubleshooting Chapter 8: Data Plane ? Interfaces Interface Properties General Interface Troubleshooting Ethernet Interface Troubleshooting Lab: Monitoring and Troubleshooting Ethernet Interfaces Chapter 9: Data Plane ? Other Components Definition of a Data Plane Problem Data Plane Components Data Plane Forwarding Load-Balancing Behavior Firewall Filters and Policers Data Plane Troubleshooting Case Study Lab: Isolate and Troubleshoot PFE Issues Chapter 10: Staging and Acceptance Testing Initial Inspection and Power-on General System Checks Interface Testing Chapter 11: Troubleshooting Routing Protocols Troubleshooting OSPF Troubleshooting BGP Troubleshooting Routing Loops and Route Oscillation Lab: Troubleshooting Routing Protocols Chapter 12: High Availability High Availability Overview Graceful Routing Engine Switchover Graceful Restart Nonstop Active Routing and Bridging Unified In-Service Software Upgrade Chapter 13: Network Monitoring SNMP RMON Telemetry Flow Monitoring Lab: Monitoring the Network Chapter 14: vMX Troubleshooting vMX Overview Troubleshooting Lab: Monitoring vMX Chapter 15: JTAC Procedures Opening a Support Case Customer Support Tools The Content of a PR Transferring Files to JTAC Chapter 16: Automated Support and Prevention Overview Service Now Service Insight Lab: Automated Support and Prevention Additional course details: Nexus Humans JTNOC - Junos Troubleshooting in the NOC 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 JTNOC - Junos Troubleshooting in the NOC 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.