119 String courses in Edinburgh delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for Authors Overview Please refer to course overview This course provides authors with an introduction to build reports using Cognos Analytics. Techniques to enhance, customize, and manage reports will be explored. Activities will illustrate and reinforce key concepts during this learning opportunity. What is IBM Cognos Analytics - Reporting The Welcome page Consume report content Interactive filtering Working with reports Dimensionally modeled relational dataUse personal data sources and data modules Upload personal data Upload custom images Using navigation paths in a data module Examine list reports Group data Format columns Include headers and footers Aggregate fact data Identify differences in aggregation Multiple facts and repeated information Use shared dimensions to create multi-fact queries Present repeated information Add repeated information to reports Create a mailing list report Create crosstab reports Add measures to a crosstab Data sources for a crosstab Create complex crosstab reports Add items as peers Create crosstab nodes and crosstab members Work with crosstab data Format, sort, and aggregate a crosstab Create discontinuous crosstab reportsCreate visualization reports Visualization categories Customize visualizations Client side visualizations Enhanced map visualizations Focus reports using filters Create filters to narrow the focus Use advanced detail filters Apply a filter with aggregation Use summary filters Focus reports using prompts Examine parameters and prompts Create a parameter for a report item Add a prompt page Add a prompt item to a report Identify a prompt type Create a cascading prompt Use calculations What are calculations Add Date and Time functions Add string functions Display prompt selections in report titles Customize reports with conditional formatting Three steps for conditional formatting Create a variable Assign the variable to a report object Format based on the conditional value Conditionally render report objects Drill-through definitions Navigate to related data Enhance report layout View the structure of a report Use Guided report layout Force page breaks Create horizontal pagination Modify the report structure Format objects across reports Use additional report-building techniques Enhance a report design Add objects to reports Convert a list to a crosstab Explore reuse Additional course details: Nexus Humans B6258 IBM Cognos Analytics - Author Reports Fundamentals V11.1.x 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 B6258 IBM Cognos Analytics - Author Reports Fundamentals V11.1.x 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 basic course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of the fundamentals of coding and basics of Java and object-oriented programming concepts. Attendees might include: Technically-minded attendees who want or who want to begin the process of becoming an OO application developer Technical team members from non-development roles, re-skilling to move into software and application development roles within an organization Recent college graduates looking to apply their college experience to programming skills in a professional environment, or perhaps needing to learn the best practices and standards for programming within their new organization Technical managers tasked with overseeing programming teams, or development projects, where basic coding knowledge and exposure will be useful in project oversight or communications needs Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in basic coding with Java, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn: The steps involved in the creation and deployment of a computer program What OO programming is and what the advantages of OO are in today's world To work with objects, classes, and OO implementations The basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction The basic constructs that all programming languages share The basic Java constructs supporting processing as well as the OO orientation How to use Java exception handling About and how to use classes, inheritance and polymorphism About use collections, generics, autoboxing, and enumerations How to take advantage of the Java tooling that is available with the programming environment being used in the class Getting Started with Programming, OO and Java Basics for Non-Developers is a skills-focused, hands-on coding course that teaches students the fundamentals of programming object oriented (OO) applications with Java to a basic level, using sound coding skills and best practices for OO development. This course is presented in a way that enables interested students to embrace the fundamentals of coding as well as an introduction to Java, in a gentle paced environment that focuses on coding basics.Students are introduced to the application development cycle, structure of programs, and specific language syntax. The course introduces important algorithmic constructs, string and character manipulation, dynamic memory allocation, standard I/O, and fundamental object-oriented programming concepts. The course explains the use of inheritance and polymorphism early on so the students can practice extensively in the hands-on labs. Structured programming techniques and error handling are emphasized. The course includes the processing of command line arguments and environment variables, so students will be able to write flexible, user-friendly programs. Students will leave this course armed with the required skills to begin their journey as a Java programmer using modern coding skills and technologies. Introduction to Computer Programming Introduction to Programming Programming Tools Programming Fundamentals Thinking About Objects Program Basics Programming Constructs Java: A First Look The Java Platform Using the JDK The Eclipse Paradigm Writing a Simple Class OO Concepts Object-Oriented Programming Inheritance, Abstraction, and Polymorphism Getting Started with Java Adding Methods to the Class Language Statements Using Strings Specializing in a Subclass Essential Java Programming Fields and Variables Using Arrays Java Packages and Visibility Advanced Java Programming Inheritance and Polymorphism Interfaces and Abstract Classes Exceptions Java Developer's Toolbox Utility Classes Enumerations and Static Imports Formatting Strings Collections and Generics Introduction to Generics Collections

Duration 3 Days 18 CPD hours This course is intended for System administrators System integrators Overview By the end of the course, you should be able to meet the following objectives: Discuss Horizon Connection Server advanced configurations List troubleshooting techniques for Horizon Connection Server common issues Interpret Horizon 8 Connection Server logs Identify Unified Access Gateway configuration and certificate issues List troubleshooting steps for Unified Access Gateway common issues Describe BLAST configuration verification using logs and settings Describe BLAST optimization recommendations for different use cases Describe Horizon 8 Connections and how to troubleshoot related issues Describe Horizon 8 certificates List troubleshooting steps for common issues with Horizon 8 certificates Leverage Horizon infrastructure troubleshooting steps to resolve issues This three-day, hands-on training provides you with the advanced knowledge, skills, and abilities to troubleshoot VMware Horizon© 8 infrastructure. This workshop teaches the required skill and competence for troubleshooting VMware Horizon© Connection Server?, VMware Unified Access Gateway?, protocols, connections, and certificates Course Introduction Introduction and course logistics Course objectives Horizon Connection Server Troubleshooting Discuss Horizon Connection Server general troubleshooting techniques Identity Horizon Connection Server common issues through logs Describe AD LDS replication Discuss Horizon Connection Server replication common issues Review and Interpret Horizon Connection Server logs Compare successful and unsuccessful logs from everyday infrastructure administration tasks Unified Access Gateway Troubleshooting List and identify common Unified Access Gateway deployment issues Monitor the Unified Access Gateway deployment to identify health and issues Identify and troubleshoot Unified Access Gateway certificate issues Monitor, test, and troubleshoot network problems Discuss general Unified Access Gateway troubleshooting processes BLAST Configuration Verification Discuss BLAST Codecs and Encoder Switch settings. Describe how to verify BLAST configuration using logs and settings BLAST Optimization List general BLAST optimization recommendations Summarize BLAST tuning recommendations that apply to WAN connections Summarize BLAST tuning recommendations that apply to work-from-home and home-office-to-cloud use cases Describe recommended tuning options to increase display protocol quality for all use cases and applications. VMware Horizon Connections Troubleshooting Explain Horizon connections Describe the role of Primary and Secondary protocols in Horizon connections Describe HTML client access connections Describe Horizon connections load balancing Describe timeout settings, supported health monitoring string, and suitable load balancer persistence values Identify troubleshooting steps for failing Horizon load balancer connections List troubleshooting steps for Horizon connections VMware Horizon Certificates Troubleshooting List Horizon certificate functions Describe Horizon certificates scenarios. Discuss potential challenges related to certificates in Horizon Describe the troubleshooting approach to Horizon certificate issues VMware Horizon Challenge Lab Leverage Horizon infrastructure troubleshooting steps to resolve issue Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Horizon 8: Infrastructure 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: Infrastructure 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 5 Days 30 CPD hours This course is intended for Experienced Programmers and Systems Administrators. Overview Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review. This course is ?skills-centric?, designed to train attendees in core Python and web development skills beyond an intermediate level, coupling the most current, effective techniques with best practices. Working within in an engaging, hands-on learning environment, guided by our expert Python practitioner, students will learn to: ? Create working Python scripts following best practices ? Use python data types appropriately ? Read and write files with both text and binary data ? Search and replace text with regular expressions ? Get familiar with the standard library and its work-saving modules ? Use lesser-known but powerful Python data types ? Create 'real-world', professional Python applications ? Work with dates, times, and calendars ? Know when to use collections such as lists, dictionaries, and sets ? Understand Pythonic features such as comprehensions and iterators ? Write robust code using exception handling An introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features. An Overview of Python What is python? 1 -- An overview of Python What is python? Python Timeline Advantages/Disadvantages of Python Getting help with pydoc The Python Environment Starting Python Using the interpreter Running a Python script Python scripts on Unix/Windows 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 White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences 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 files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Converting binary data with struct Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Parameters Global and local scope Nested functions Returning values Sorting The sorted() function Alternate keys Lambda functions Sorting collections Using operator.itemgetter() Reverse sorting Errors and Exception Handling Syntax errors Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages The import statement Module search path Creating Modules Using packages Function and Module aliases Classes About o-o programming Defining classes Constructors Methods Instance data Properties Class methods and data Regular Expressions RE syntax overview RE Objects Searching and matching Compilation flags Groups and special groups Replacing text Splitting strings The standard library The sys module Launching external programs Math functions Random numbers The string module Reading CSV data Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Working with the file system Paths, directories, and filenames Checking for existence Permissions and other file attributes Walking directory trees Creating filters with fileinput Using shutil for file operations 17 ? Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Advanced data handling Defaultdict and Counter Prettyprinting data structures Compressed archives (zip, gzip, tar, etc.) Persistent data Network services Grabbing web content Sending email Using SSH for remote access Using FTP Writing real-life applications Parsing command-line options Detecting the current platform Trapping signals Implementing logging Python Timeline Advantages/Disadvantages of Python Getting help with pydoc

Duration 5 Days 30 CPD hours This course is intended for This is a basic-level programming course designed for attendees with prior development experience in another language, such as COBOL, 4GL, Mainframe or other non-object oriented languages. This course is not geared for non-developers. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core OO coding and Java development skills, coupling the most current, effective techniques with the soundest industry practices. 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 learn to: Understand what OO programming is and what the advantages of OO are in today's world Work with objects, classes, and OO implementations Understand the basic concepts of OO such as encapsulation, inheritance, polymorphism, and abstraction Understand not only the fundamentals of the Java language, but also its importance, uses, strengths and weaknesses Understand the basics of the Java language and how it relates to OO programming and the Object Model Work with the Modular system (Project Jigsaw) Understand and use classes, inheritance and polymorphism Understand and use collections, generics, autoboxing, and enumerations Process large amount of data using Lambda expressions and the Stream API Abstract, static and private methods in interfaces Take advantage of the Java tooling that is available with the programming environment being used in the class Java 11 features covered: Using the Local Variable Type in Lambda expressions; Updates made to the String API This course provides hands-on Java 11 training for developers who have little or no prior working knowledge of object-oriented programming languages such as C, COBOL, and 4GL. You will learn the best practices for writing great object-oriented programs in Java 11, using sound development techniques, new improved features for better performance, and new capabilities for addressing rapid application development. Special emphasis is placed on object oriented concepts and best practices. A First Look The Java Platform Using the JDK The Eclipse Paradigm Getting Started with Java Writing a Simple Class Adding Methods to the Class OO Concepts Object-Oriented Programming Inheritance, Abstraction, and Polymorphism Essential Java Programming Language Statements Using Strings Specializing in a Subclass Fields and Variables Using Arrays Local-Variable Type Inference Java Packages and Visibility Object Oriented Development Inheritance and Polymorphism Interfaces and Abstract Classes Introduction to Exception Handling Exceptions Java Developer's Toolboxÿ Utility Classes Java Date/Time Advanced Java Programming Introduction to Generics Lambda Expressions and Functional Interface Working with Collections Collections Using Collections Stream APIÿ Streams Collectors The Java Module System Introduction to the Module System Time Permitting Formatting Strings Introduction to Annotations Java 12 and beyond Additional course details: Nexus Humans Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 Basic Java 11 and OO Programming for Developers New to OO (TT2120-J11) 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 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 2.5 Days 15 CPD hours This course is intended for This course is intended for those with a basic understanding of Tableau who want to pursue mastery of the advanced features. Overview The goal of this course is to present essential Tableau concepts and its advanced functionalities to help better prepare and analyze data. This course will use Tableau Hyper, Tableau Prep and more. Getting Up to Speed ? a Review of the Basics Connecting Tableau to your data Connecting to Tableau Server Connecting to saved data sources Measure Names and Measure Values Three essential Tableau concepts Exporting data to other devices Summary All About Data ? Getting Your Data Ready Data mining and knowledge discovery process models CRISP?DM All About Data ? Joins, Blends, and Data Structures All About Data - Joins, Blends, and Data Structures Introduction to joins Introduction to complex joins Exercise: observing join culling Introduction to join calculations Introduction to spatial joins Introduction to unions Understanding data blending Order of operations No dimensions from a secondary source Introduction to scaffolding Introduction to data structures Exercise: adjusting the data structure for different questions Summary Table Calculations Table Calculations A definition and two questions Introduction to functions Directional and non-directional table calculations Application of functions Summary Level of Detail Calculations Level of Detail Calculations Building playgrounds Playground I: FIXED and EXCLUDE Playground II: INCLUDE Practical application Exercise: practical FIXED Exercise: practical INCLUDE Exercise: practical EXCLUDE Summary Beyond the Basic Chart Types Beyond the Basic Chart Types Improving popular visualizations Custom background images Tableau extensions Summary Mapping Mapping Extending Tableau's mapping capabilities without leaving Tableau Extending Tableau mapping with other technology Exercise: connecting to a WMS server Exploring the TMS file Exploring Mapbox Accessing different maps with a dashboard Creating custom polygons Converting shape files for Tableau Exercise: polygons for Texas Heatmaps Summary Tableau for Presentations Tableau for Presentations Getting the best images out of Tableau From Tableau to PowerPoint Embedding Tableau in PowerPoint Animating Tableau Story points and dashboards for Presentations Summary Visualization Best Practices and Dashboard Design Visualization Best Practices and Dashboard Design Visualization design theory Formatting rules Color rules Visualization type rules Compromises Keeping visualizations simple Dashboard design Dashboard layout Sheet selection Summary Advanced Analytics Advanced Analytics Self-service Analytics Use case ? Self-service Analytics Use case ? Geo-spatial Analytics Summary Improving Performance Improving Performance Understanding the performance-recording dashboard Exercise: exploring performance recording in Tableau desktop Performance-recording dashboard events Behind the scenes of the performance- recording dashboard Hardware and on-the-fly techniques Hardware considerations On-the-fly-techniques Single Data Source > Joining > Blending Three ways Tableau connects to data Using referential integrity when joining Advantages of blending Efficiently working with data sources Tuning data sources Working efficiently with large data sources Intelligent extracts Understanding the Tableau data extract Constructing an extract for optimal performance Exercise: summary aggregates for improved performance Optimizing extracts Exercise: materialized calculations Using filters wisely Extract filter performance Data source filter performance Context filters Dimension and measure filters Table-calculation filters Efficient calculations Boolean/Numbers > Date > String Additional performance considerations Avoid overcrowding a dashboard Fixing dashboard sizing Setting expectations Summary Additional course details: Nexus Humans Advanced Tableau 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 Advanced Tableau 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 appropriate for advanced users, system administrators and web site administrators who want to use Python to support their server installations, as well as anyone else who wants to automate or simplify common tasks with the use of Python scripts. Students can apply the course skills to use Python in basic web development projects or automate or simplify common tasks with the use of Python scripts. Overview This skills-focused course is about 50% hands-on lab to lecture ratio, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert instructor, you'll learn how to: Create working Python scripts following best practices Use python data types appropriately Read and write files with both text and binary data Search and replace text with regular expressions Work with with the standard library and its work-saving modules Create 'real-world', professional Python applications Know when to use collections such as lists, dictionaries, and sets Work with Pythonic features such as comprehensions and iterators Write robust code using exception handling Introduction to Python Programming Basics is a hands-on Python programming course that teaches you the key skills you?ll need to get started with programming in Python to a solid foundational level. The start of the course will lead you through writing and running basic Python scripts, and then guide you through how to use more advanced features such as file operations, regular expressions, working with binary data, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as tuples, array slices, and output formatting. This course provides you with an excellent kick start for users new to Python and scripting, enabling you to quickly use basic Python skills on the job in a variety of ways. You?ll be able use Python in basic web development projects, or use it to automate or simplify common tasks with the use of Python scripts. The course also serves as a solid primer course / foundation for continued Python study in support for next level web development with Python, using Python in DevOps, Python for data science / machine learning or Python for systems admin or networking support. Python Quick View What is Python? Python timeline Advantages/disadvantages Installing Python Getting help The Python Environment Starting Python Using the interpreter Running a Python script Editors and IDEs Getting Started with Python Using variables Builtin functions String data Numberic data Converting types Console input/output Command line parameters Flow Control About flow control The if statement Relational and Boolean operators while loops Exiting from loops Array Types About array types Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions and generators Working with Files File overview Opening a text file Reading a text file Writing to a text file Dictionaries and Sets About dictionaries Creating dictionaries Iterating through a dictionary About sets Creating sets Working with sets Functions Defining functions Returning values Parameters and arguments Variable scope Sorting The sorted() function Custom sort keys Lambda functions Sorting in reverse Using min() and max() Errors and Exception Handling Exceptions Using try/catch/else/finally Handling multiple exceptions Ignoring exceptions Modules and Packages Creating Modules The import statement Module search path Using packages Function and module aliases Getting Started with Object Oriented Programming and Classes About object-oriented programming Defining classes Constructors Understanding self Properties Instance Methods and data Class methods and data Inheritance Additional course details: Nexus Humans Introduction to Python Programming Basics (TTPS4800) 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 Introduction to Python Programming Basics (TTPS4800) 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 New or junior administrators and operators; system managers accountable for staffing and training Horizon operators and administrators. 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 Discuss Horizon Connection Server advanced configurations List troubleshooting techniques for Horizon Connection Server common issues Interpret Horizon 8 Connection Server logs Identify Unified Access Gateway configuration and certificate issues List troubleshooting steps for Unified Access Gateway common issues Describe BLAST configuration verification using logs and settings Describe BLAST optimization recommendations for different use cases Describe Horizon 8 Connections and how to troubleshoot related issues Describe Horizon 8 certificates List troubleshooting steps for common issues with Horizon 8 certificates Leverage Horizon infrastructure troubleshooting steps to resolve issues  This five-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 and provides you with the advanced knowledge, skills, and abilities to troubleshoot VMware Horizon© 8 infrastructure related issues. This workshop teaches the required skill and competence for troubleshooting VMware Horizon© Connection Server?, VMware Unified Access Gateway?, protocols, connections, and certificates 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 Only applicable for Horizon 7.x environments 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 Clones 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 Horizon Connection Server Troubleshooting Discuss Horizon Connection Server general troubleshooting techniques Identity Horizon Connection Server common issues through logs Describe AD LDS replication Discuss Horizon Connection Server replication common issues Review and Interpret Horizon Connection Server logs Compare successful and unsuccessful logs from everyday infrastructure administration tasks Unified Access Gateway Troubleshooting List and identify common Unified Access Gateway deployment issues Monitor the Unified Access Gateway deployment to identify health and issues Identify and troubleshoot Unified Access Gateway certificate issues Monitor, test, and troubleshoot network problems Discuss general Unified Access Gateway troubleshooting processes BLAST Configuration Verification Discuss BLAST Codecs and Encoder Switch settings. Describe how to verify BLAST configuration using logs and settings BLAST Optimization List general BLAST optimization recommendations Summarize BLAST tuning recommendations that apply to WAN connections Summarize BLAST tuning recommendations that apply to work-from-home and home-office-to-cloud use cases Describe recommended tuning options to increase display protocol quality for all use cases and applications. VMware Horizon Connections Troubleshooting Explain Horizon connections Describe the role of Primary and Secondary protocols in Horizon connections Describe HTML client access connections Describe Horizon connections load balancing Describe timeout settings, supported health monitoring string, and suitable load balancer persistence values Identify troubleshooting steps for failing Horizon load balancer connections List troubleshooting steps for Horizon connections VMware Horizon Certificates Troubleshooting List Horizon certificate functions Describe Horizon certificates scenarios. Discuss potential challenges related to certificates in Horizon Describe the troubleshooting approach to Horizon certificate issues VMware Horizon Challenge Lab Leverage Horizon infrastructure troubleshooting steps to resolve issues

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm