1763 Master courses delivered Live Online

Understand what is meant by the term burnout to be able to identify and understand its impact on the individual and the organisation. Learn to utilise practical strategies to prevent and manage burnout.

Learn about common mental health concerns for women, the factors that can influence their wellbeing, and how to support our female colleagues.

Understand why it is difficult for us to accept changes when they occur - both in our personal and professional lives. Outline the emotional stages of the change curve which maps out distinct stages all individuals go through after a change, and learn to utilise a range of strategies to cope with changes.

Understand what is meant by the term mental health and the factors that can influence it. Know how to take care of your mental health, actively manage illness, and where to find additional help should you need it.

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

Advanced Certified Scrum Product Owner® (A-CSPO®): In-House Training All Advanced CSPO courses are taught by Educators approved by the Scrum Alliance. Taking an Advanced CSPO course, meeting the learning objectives, and accepting the license agreement designates you as an Advanced Certified Scrum Product Owner. Please review your trainer's course description below to determine which learning objectives this course satisfies. What you will Learn You'll learn to: Manage multiple business initiatives from competing stakeholders Clearly order and express Product Backlog items Define a clear product vision that ensures your product remains focused on the features your customers and end users will actually use Communicate effectively with various stakeholder groups to achieve alignment Identify the crucial opportunities and avoid wasting time Define and validate business value Increase your credibility as a product expert and become recognized as a person who delivers real business results Benefits Build on your foundational knowledge with enhanced implementation skills Distinguish yourself in the global marketplace Stand out in your industry as a member of the Scrum Alliance globally-recognized community Show advanced value to your employer (or potential employer) as a highly trained Agile professional

Regular expressions training course description Regular expressions are an extremely powerful tool for manipulating text and data. They are now standard features in a wide range of languages and popular tools, including Python and MySQL. Regular expressions allow you to code complex and subtle text processing that you never imagined could be automated. Once you've mastered regular expressions, they'll become an invaluable part of your toolkit. You will wonder how you ever got by without them. What will you learn Use Regular Expressions. Troubleshoot Regular Expressions. Compare RE features among different versions. Explain how the regular expression engine works. Optimize REs. Match what you want, not what you don't want. Regular expressions training course details Who will benefit: Anyone looking to use regular expressions. Prerequisites: None. Duration 1 day Regular expressions training course contents Introduction to Regular Expressions Solving real problems, REs as a language, the filename analogy, language analogy, RE frame of mind, searching text files: egrep, egrep metacharacters, start and end of the line, character classes, matching any character with dot, alternation, ignoring differences in capitalization, word boundaries, optional items, other quantifiers: repetition, parentheses and backreferences, the great escape, expanding the foundation, linguistic diversification, the goal of a RE, more examples, RE nomenclature, Improving on the status quo. Extended introductory examples A short introduction to Perl, matching text with regular expressions, toward a more real-world example, side effects of a successful match, Intertwined regular expression, intermission, modifying text with regular expressions, example: form letter, example: prettifying a stock price, automated editing, a small mail utility, adding commas to a number with lookaround, text-to-HTML conversion, that doubled-word thing. Regular expression features and flavours The regex landscape, origins of REs, care and handling of REs, Integrated handling, procedural and object-oriented handling, search-and-replace example. strings character encodings and modes, strings as REs, character-encoding issues, unicode, regex modes and match modes, common metacharacters and features, character representations, character classes and class-like constructs, anchors and other 'zero-width assertions', comments and mode modifiers, grouping capturing conditionals and control. The mechanics of expression processing Two kinds of engines, new standards, regex engine types, from the department of redundancy department, testing the engine type, match basics, about the examples, rule 1: the match that begins earliest wins, engine pieces and parts, rule 2: the standard quantifiers are greedy, regex-directed versus text-directed, NFA engine: regex-directed, DFA engine: text-directed, first thoughts: NFA and DFA in comparison, backtracking, two important points on backtracking, saved states, backtracking and greediness, more about greediness and backtracking, problems of greediness, multi-character 'quotes', lazy quantifiers, greediness and laziness, laziness and backtracking, possessive quantifiers and atomic grouping, possessive quantifiers ?, +, *+, ++ and {m,n}+, the backtracking of lookaround, is alternation greedy? taking advantage of ordered alternation, NFA DFA and posix, the longest-leftmost', posix and the longest-leftmost rule, speed and efficiency. Practical regex techniques Continuation lines, matching an IP address, working with filenames, matching balanced sets of parentheses, watching out for unwanted matches, matching delimited text, knowing your data and making assumptions, stripping leading and trailing whitespace, matching and HTML tag, matching an HTML link, examining an HTTP URL, validating a hostname, plucking a hostname, plucking a URL, parsing CSV files. Crafting an efficient expression Efficiency vs. correctness, localizing greediness, global view of backtracking, more work for POSIX NFA, work required during a non-match, being more specific, alternation can be expensive, benchmarking, know what you re measuring, benchmarking with Python, common optimisations, the mechanics of regex application, pre-application optimizations, optimizations with the transmission, optimization of the regex itself, techniques for faster expressions, common sense techniques, expose literal text, expose anchors, lazy versus greedy: be specific, split into multiple REs, mimic initial-character discrimination, use atomic grouping and possessive quantifiers, lead the engine to a match, unrolling the loop, observations, using atomic grouping and possessive quantifiers, short unrolling examples, unrolling C comments, the free flowing regex, a helping hand to guide the match, a well-guided regex is a fast regex.

Learn about the many benefits of supporting mental health in the workplace, identify the signs that an employee may be struggling with their mental health, and know how to have an effective conversation with them about it.

Duration 2 Days 12 CPD hours This course is intended for This course is for IT network or security professionals who have practical experience with the ProxySG in the field and wish to master the advanced network security of the ProxySG. Overview Solve common authentication and SSL issuesUnderstand the underlying architecture of SGOSMonitor and analyze ProxySG performanceUse policy tracing as a troubleshooting tool The ProxySG 6.6 Advanced Administration course is intended for IT professionals who wish to learn to master the advanced features of the ProxySG. Using Authentication Realms Describe the benefits of enabling authentication on the ProxySG Describe, at a high level, the ProxySG authentication architecture Understand the use of IWA realms, with both IWA Direct and IWA BCAAA connection methods Understanding Authentication Credentials Describe how NTLM and Kerberos authentication work in both IWA direct and IWA BCAAA deployments Configure the ProxySG to use Kerberos authentication Understanding Authentication Modes Describe authentication surrogates and authentication modes Describe ProxySG authentication in both explicit and transparent deployment mode Understanding HTTPS Describe key components of SSL encryption Describe how the SSL handshake works Describe some of the legal and security considerations related to use of the SSL proxy Managing SSL Traffic on the ProxySG Describe how the SSL proxy service handles SSL traffic Describe the standard keyrings that are installed by default on the ProxySG Identify the types of security certificates that the ProxySG uses Optimizing SSL Interception Performance Configure the ProxySG to process SSL traffic according to best practices for performance SGOS Architecture Identify key components of SGOS Explain the interaction among client workers and software workers in processing client requests Explain the significance of policy checkpoints Describe key characteristics of the SGOS storage subsystem Explain the caching behavior of the ProxySG Caching Architecture Describe the benefits of object caching on the ProxySG Explain the caching-related steps in a ProxySG transaction Identify and describe the HTTP request and response headers related to caching Describe, in general terms, how the ProxySG validates cached objects to ensure freshness Explain how the ProxySG uses cost-based deletion, popularity contests, and pipelining to improve object caching System Diagnostics Describe the use of the health monitor and health checks Explain the use of the event and access logs Describe the information available in advanced URLs and sysinfo files Describe the function of policy tracing and packet captures Introduction to Content Policy Language (CPL) Describe the fundamental concepts and purposes of ProxySG policy transactions Understand the relationship of layers, rules, conditions, properties, and triggers Describe the two types of actions in CPL Describe how to write, edit, and upload CPL code Using Policy Tracing for Troubleshooting Identify the two main types of ProxySG policy traces Describe the various sections of a policy trace result Configure a global and policy-driven trace Access and interpret policy trace results ProxySG Integration Identify other Symantec products that can be used as part of a complete security solution

An 8 week coaching programme like no other. Discover how to build your business, free your time all the while making more money and doing more of the stuff you love. Stop not-earning when you're off on holiday, off for the weekend or off sick... Create a business that works for you, even when you're not there.