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Gain practical skills in influencing and decision-making, perfect for anyone working in team-based or project-focused environments, with interactive, hands-on learning. Course overview Duration: 1 day (6.5 hours) This is a highly interactive and practical course which will help you to use influencing and decision making techniques. This workshop has been specifically designed to give you an opportunity to learn and test a range of influencing and decision making models and techniques. The course is aimed at anyone who interacts with others on a regular basis, especially those in project management disciplines, multi disciplinary, matrix type organisations where healthy debate and challenge are key to achieving optimum resolutions. Objectives By the end of the course you will be able to: Utilise a variety of new techniques to enhance your influencing skills Recognise the impact of non-verbal communication and use it to enhance influencing behaviours Use language skills necessary to get your message across in an influential way Apply different techniques for dealing with aggression Understand VUCA – Volatility, Uncertainty, Complexity & Ambiguous Use Perception, Bias, Decision Making and Judgement Understand personal preferences and approaches to Decision Making Speed read others approach to decision making Apply Mindsets, Skillsets and Toolsets for decision making Content What is influencing? Sources of power Influencing skills Choosing the right approach Developing Skills Communication skills – the language of influence Different influencing techniques and when to use them Having the confidence to challenge Dealing with confrontation and challenges in a confident manner The Decision Lifecycle – Personal Preferences Understand the human facts that influence decision making Understanding personal preferences and approaches to Decision Making Understand the impact of Perception, Bias and judgement in decision making Speed reading others approach to decision making Frameworks to provide context for decision making Understand the business factors that influence decision making - VUCA The Cynefin Framework – decision making in complex situations Understanding which business context, you operate in – simple, complicated, complex or chaotic Understanding how to decide in complexity Practical Practical exercises Case studies Personal action planning
Supporting and engaging with different parts of the organisation and interact with internal or external customer.
Course Overview: This Dyslexia Awareness course provides a comprehensive understanding of dyslexia, focusing on its impact, challenges, and effective support strategies. Designed for individuals and professionals alike, this course addresses dyslexia from multiple angles, including educational settings and cognitive theories. By the end of the course, learners will be equipped with essential knowledge to support those with dyslexia, identify potential barriers, and create inclusive learning environments. This course is ideal for anyone seeking to expand their understanding of dyslexia and its implications in various sectors. Course Description: The course covers a broad range of topics, including the definition of dyslexia, its connection with other learning difficulties, and its presence in educational contexts. Learners will explore cognitive theories, such as the phonological processing difficulties that underpin dyslexia, and delve into legal rights and accommodations for dyslexics. The modules guide learners through effective approaches for identifying and supporting individuals with dyslexia in both academic and professional settings. Upon completion, participants will gain valuable insights into enhancing accessibility and inclusion for dyslexic individuals in various environments. Course Modules: Module 01: Introduction to Dyslexia Module 02: Dyslexia and Learning Difficulties Module 03: Dyslexia in the School Module 04: Cognitive Approaches in Dyslexia Module 05: The Legal Rights of Dyslexics (See full curriculum) Who is this course for? Individuals seeking to understand dyslexia and its impact Professionals aiming to enhance their knowledge in supporting dyslexic individuals Beginners with an interest in inclusive education and learning difficulties Anyone working with individuals affected by learning differences Career Path: Special Education Teacher Educational Psychologist Learning Support Assistant Disability Support Coordinator Inclusion Officer Education Consultant
Duration 3 Days 18 CPD hours Overview The goal of this course is to enable technical students new to Cassandra to begin working with Cassandra in an optimal manner. Throughout the course students will learn to: Understand the Big Data needs that C* addresses Be familiar with the operation and structure of C* Be able to install and set up a C* database Use the C* tools, including cqlsh, nodetool, and ccm (Cassandra Cluster Manager) Be familiar with the C* architecture, and how a C* cluster is structured Understand how data is distributed and replicated in a C* cluster Understand core C* data modeling concepts, and use them to create well-structured data models Be familiar with the C* eventual consistency model and use it intelligently Be familiar with consistency mechanisms such as read repair and hinted handoff Understand and use CQL to create tables and query for data Know and use the CQL data types (numerical, textual, uuid, etc.) Be familiar with the various kinds of primary keys available (simple, compound, and composite primary keys) Be familiar with the C* write and read paths Understand C* deletion and compaction The Cassandra (C*) database is a massively scalable NoSQL database that provides high availability and fault tolerance, as well as linear scalability when adding new nodes to a cluster. It has many powerful capabilities, such as tunable and eventual consistency, that allow it to meet the needs of modern applications, but also introduce a new paradigm for data modeling that many organizations do not have the expertise to use in the best way.Introduction to Cassandra is a hands-on course designed to teach attendees the basics of how to create good data models with Cassandra. This technical course has a focus on the practical aspects of working with C*, and introduces essential concepts needed to understand Cassandra, including enough coverage of internal architecture to make good decisions. It is hands-on, with labs that provide experience in core functionality. Students will also explore CQL (Cassandra Query Language), as well as some of the ?anti-patterns? that lead to non-optimal C* data models and be ready to work on production systems involving Cassandra. Session 1: Cassandra Overview Why We Need Cassandra - Big Data Challenges vs RDBMS High level Cassandra Overview Cassandra Features Optional: Basic Cassandra Installation and Configuration Session 2: Cassandra Architecture and CQL Overview Cassandra Architecture Overview Cassandra Clusters and Rings Nodes and Virtual Nodes Data Replication in Cassandra Introduction to CQL Defining Tables with a Single Primary Key Using cqlsh for Interactive Querying Selecting and Inserting/Upserting Data with CQL Data Replication and Distribution Basic Data Types (including uuid, timeuuid) Session 3: Data Modeling and CQL Core Concepts Defining a Compound Primary Key CQL for Compound Primary Keys Partition Keys and Data Distribution Clustering Columns Overview of Internal Data Organization Overview of Other Querying Capabilities ORDER BY, CLUSTERING ORDER BY, UPDATE , DELETE, ALLOW FILTERING Batch Queries Data Modeling Guidelines Denormalization Data Modeling Workflow Data Modeling Principles Primary Key Considerations Composite Partition Keys Defining with CQL Data Distribution with Composite Partition Key Overview of Internal Data Organization Session 4: Additional CQL Capabilities Indexing Primary/Partition Keys and Pagination with token() Secondary Indexes and Usage Guidelines Cassandra collections Collection Structure and Uses Defining and Querying Collections (set, list, and map) Materialized View Overview Usage Guidelines Session 5: Data Consistency In Cassandra Overview of Consistency in Cassandra CAP Theorem Eventual (Tunable) Consistency in C* - ONE, QUORUM, ALL Choosing CL ONE Choosing CL QUORUM Achieving Immediate Consistency Overview of Other Consistency Levels Supportive Consistency Mechanisms Writing / Hinted Handoff Read Repair Nodetool repair Session 6: Internal Mechanisms Ring Details Partitioners Gossip Protocol Snitches Write Path Overview / Commit Log Memtables and SSTables Write Failure Unavailable Nodes and Node Failure Requirements for Write Operations Read Path Overview Read Mechanism Replication and Caching Deletion/Compaction Overview Delete Mechanism Tombstones and Compaction Session 7: Working with IntelliJ Configuring JDBC Data Source for Cassandra Reading Schema Information Querying and Editing Tables. Additional course details: Nexus Humans Introduction to Cassandra (TTDS6776) 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 Cassandra (TTDS6776) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.
Duration 1 Days 6 CPD hours This course is intended for This course is designed for a non-technical audience and doesn't require any prior coding or technical experience. The handson exercises will be done using pre-built OpenAI tools and interfaces that are user-friendly and easy to use. Overview Working in an interactive learning environment, led by our engaging expert, you will: Get comfortable with the basics of prompt engineering and discover how it can make a difference in various business tasks, such as enhancing customer support, creating content, and fine-tuning sales pitches. Develop the knack for crafting, refining, and perfecting prompts suited to specific business situations by understanding context, user intent, and what makes a prompt great. Learn how to smoothly incorporate prompt engineering solutions into your existing business workflows, including pinpointing the right processes, integrating with your current software, and keeping data privacy and security in check. Become proficient in advanced techniques and best practices in prompt engineering, like making use of APIs, customizing language models, and collaborating with your teammates across different departments. Keep up with the latest developments in prompt engineering and be ready to adapt to changing business needs and trends, ensuring that you stay relevant and continue to grow in the dynamic business world. Prompt engineering is the process of designing and refining input prompts to get desired output from advanced language models, such as OpenAI Codex or GPT-4. It involves creating effective questions or statements that guide the AI model to generate useful responses for a specific task or purpose, like enhancing customer support, generating content, and fine-tuning sales pitches, making it an essential skill set for a wide range of business applications. Quick Start to Prompt Engineering for Everyday Business Users is a one-day, workshop style hands-on course that where you'll learn how to create effective prompts, integrate prompt engineering solutions into existing workflows, and uncover advanced techniques and best practices. Guided by our engaging, expert instructor, you?ll experiment with innovative tools and develop practical skills that can be immediately applied to a variety of projects. Whether you're aiming to enhance customer interactions, simplify content creation, or refine internal communication, this immersive learning experience will equip you with the knowledge to make a meaningful impact on your organization. Introduction to Prompt Engineering Understand the fundamentals of prompt engineering and its applications in the business world. What is prompt engineering? Importance of prompt engineering in business Key concepts and terminology Examples of prompt engineering in business scenarios Overview of popular prompt engineering tools (e.g., OpenAI Codex, GPT-4) Activity: Hands-on exploration of prompt engineering tools: Participants will engage in a fun scavenger hunt activity, where they will experiment with different prompt engineering tools to answer a set of questions. Developing Effective Prompts Learn how to create and refine prompts for a variety of business applications. Anatomy of a good prompt Understanding context and user intent Techniques for prompt iteration and optimization Generating specific and creative responses Handling sensitive information and biases Activity: Prompt development workshop: Participants will practice developing and refining prompts in a collaborative, game-like environment, where they will compete to create the most effective prompts for given business scenarios. Integrating Prompt Engineering into Business Processes Discover how to incorporate prompt engineering solutions into existing workflows. Identifying business processes that can benefit from prompt engineering Integrating prompt engineering with existing software and tools Evaluating the success and impact of prompt engineering solutions Ensuring data privacy and security Scaling prompt engineering solutions across an organization Activity: Business process integration simulation: Participants will work in teams to create a plan for integrating a prompt engineering solution into a simulated business process, with a focus on creativity and practicality. Advanced Techniques and Best Practices Gain insights into advanced techniques and best practices for prompt engineering in a business context. Leveraging APIs for prompt engineering Customizing and fine-tuning language models Adapting to changing business requirements and trends Collaborating with cross-functional teams Staying up-to-date with prompt engineering advancements Activity: Advanced prompt engineering challenge: Participants will take part in a friendly competition, using advanced techniques to solve complex business-related prompt engineering challenges. Additional course details: Nexus Humans QuickStart to Prompt Engineering for Everyday Business Users (TTAI2009) 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 QuickStart to Prompt Engineering for Everyday Business Users (TTAI2009) 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.