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Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS 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 The Machine Learning Pipeline on AWS 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.

Learn how to develop your emotional intelligence to become a more effective leader.

Effective communication is a skill. This half-day workshop is very interactive - participants can practise their communication skills in a positive, supportive environment. 1 Welcome, introductions and objectives The definition of effective communication Exercise: sending a message 2 Verbal communications Effective communicators - who are they? What skills or attributes do they have? Listening skills, clear use of words, presence, eye contact, body language 3 How good a listener are you? Exercise: listening skills questionnaire and evaluation 4 Impact versus intent - what did you really mean to say? Attitudes influence behaviour and behaviour breeds behaviour Exercise: 'I never said she stole money' The need to avoid misunderstanding or misinterpretation 5 The 5 key principles to effective communication Exercise: 'What would you say?' 6 Written communication What makes an effective written communication? Kipling's 6 Honest Men: who, what, where, when, why and how Planning to write an email 7 Fuzzy meanings Probabilities for misunderstandings and misinterpretations 8 Practical exercise Hone written communication skills and put into practice hints and tips from the session 9 Review of key learning points and objectives

This course aims to assist adult learners in improving their pronunciation skills and reducing their accents to enhance their overall communication in English. Through a variety of exercises and activities, participants will focus on specific sounds, stress patterns, intonation, and rhythm to develop clearer and more fluent speech. Course Duration: 10 weeks (20 sessions) Course Objectives: By the end of this course, participants will: 1. Identify and produce accurate sounds, stress patterns, and intonation in English. 2. Develop awareness of their own pronunciation challenges and strategies for improvement. 3. Reduce their native accent to improve overall intelligibility. 4. Enhance their listening skills and ability to distinguish between different sounds. 5. Increase their confidence in spoken English communication. Course Outline: Week 1: Introduction to Pronunciation and Accent Reduction - Assessing participants' pronunciation strengths and areas for improvement - Understanding the importance of pronunciation in effective communication - Introduction to key concepts: sounds, stress, intonation, and rhythm Week 2: Vowel Sounds - Identifying and producing English vowel sounds - Practice exercises and drills for accurate vowel pronunciation - Common pronunciation challenges and strategies for improvement Week 3: Consonant Sounds - Identifying and producing English consonant sounds - Focus on challenging consonant sounds and their correct articulation - Practice exercises and drills for accurate consonant pronunciation Week 4: Word Stress and Sentence Stress - Understanding the concept of stress and its role in English pronunciation - Practice exercises for placing stress on the correct syllables in words and sentences - Intonation patterns in different sentence types Week 5: Rhythm and Linking - Developing a sense of rhythm in English speech - Practice exercises for linking words together and maintaining flow - Awareness of connected speech phenomena Week 6: Intonation Patterns - Recognizing and producing different intonation patterns in English - Practice exercises for conveying meaning through intonation - Intonation in questions, statements, and emotions Week 7: Pronunciation of Commonly Mispronounced Words - Identification and correction of commonly mispronounced words - Practice exercises for improving pronunciation of specific words - Strategies for self-correction and continued improvement Week 8: Accent Reduction Techniques - Understanding the impact of native accents on English pronunciation - Techniques for reducing native accents and improving intelligibility - Practice exercises for adopting a more neutral accent Week 9: Listening Skills and Discrimination - Enhancing listening skills to better distinguish between sounds - Practice exercises for recognising and discriminating between similar sounds - Developing an ear for correct pronunciation through listening activities Week 10: Review and Fluency Practice - Reviewing course content and addressing individual needs - Fluency practice exercises and activities - Final evaluation and feedback session Note: This syllabus is a guideline and can be customised based on the specific needs and preferences of the participants. You can opt in and out of different modules. 

Duration 4 Days 24 CPD hours This course is intended for Designed for individuals interested in obtaining information about the CBAP and CCBA exam process especially potential exam candidates interested in pursuing business analysis certification from IIBA in the next 3 to 6 months. Overview Review the 6 Knowledge Areas of the BABOK Guide and discuss the business analysis tasks performed in each. Understand the relationships between the business analysis processes and how each defines an important aspect of the business analysis discipline. Review key terms, business analysis techniques, and competencies important to business analysis. Discuss the 5 business analysis Perspectives presented in BABOK Guide, v3. Complete simulated exam questions to assess personal readiness for taking the exam. Obtain key tips and techniques for effectively preparing for and successfully completing the CBAP or CCBA exam. This course provides you with a clear and detailed understanding of the concepts covered within the CBAP© and CCBA© exams. You will gain valuable tips and techniques to help prepare, study, and assess your personal readiness. In addition, you will earn valuable professional development hours toward meeting the exam criteria. CBAP© and CCBA© Overview Discuss the benefits of professional certification Present the CBAP©/CCBA© eligibility requirements Explain the exam process Discuss the exam blueprints Understand the recertification process Introduction to BABOK© Guide v3 Define the purpose of A Guide to the Business Analysis Body of Knowledge© (BABOK© Guide) Present the structure/components of the BABOK© Guide Identify the six business analysis Knowledge Areas Discuss the supporting areas of the BABOK© Guide BABOK© Guide Key Concepts Define key concepts from the BABOK© Guide Present the Business Analysis Core Concept Model? Discuss the requirements classification scheme Explain Requirements and Designs Present the 5 Business Analysis Perspectives Business Analysis Planning and Monitoring Identify the 5 tasks in Business Analysis Planning and Monitoring Understand the work performed in each of these tasks Explain the significance of the outputs produced within this knowledge area Elicitation and Collaboration Identify the 5 tasks in Elicitation and Collaboration Understand the work performed in each of these tasks Explain the significance of the outputs produced within this knowledge area Requirements Life Cycle Management Identify the 5 tasks in Requirements Life Cycle Management Understand the work performed in each of these tasks Explain the significance of the outputs produced within this knowledge area Strategy Analysis Identify the 5 tasks in Strategy Analysis Understand the work performed in each of these tasks Explain the significance of the outputs produced within this knowledge area Requirements Analysis and Design Definition Identify the 6 tasks in Requirements Analysis and Design Definition Understand the work performed in each of these tasks Explain the significance of the outputs produced within this knowledge area Solution Evaluation Identify the 6 tasks in Solution Evaluation Understand the work performed in each of these tasks Explain the significance of the outputs produced within this knowledge area Underlying Competencies Describe and understand the importance of the underlying competencies (UCs) Understand how to prepare for questions about UCs on the exam Business Analysis Techniques More clearly understand the 50 techniques presented in the BABOK© Guide Understand how to study techniques for the exam Assess Your Readiness 1 hour mock-exam to assess personal readiness Strategies for Success Utilize 8 strategies for preparing for the CBAP© or CCBA© certification exams Develop study tools and a plan to assist you in preparing for the exams Understand the tools and resources available to help you be successful Wrap-up Take Your Questions Next Steps Additional course details: Nexus Humans BACP02 - Certified Business Analysis Professional (CBAP) Exam Preparation 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 BACP02 - Certified Business Analysis Professional (CBAP) Exam Preparation 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 IS Security Officers IS Managers Risk Managers Auditors Information Systems Owners IS Control Assessors System Managers Government Employees Overview Upon completion, Certified Information Systems Risk Manager students will be prepared to pass the CISRM exam.  Certified Information Systems Risk Manager, CISRM, course is made for IT and IS professionals who are involved with all aspects of risk management. Requests for this particular area of certification is growing fast in the employment sector. Recent high-profile breaches in both the public and private sectors have increased awareness for the need for Risk Management professionals. Mile2?s CISRM certification exam will test your knowledge in all areas of risk management. If you would like some training and test preparation before taking the Certified Information System Risk Manager Exam we offer the CISRM course as both a live class and a self-study combo. First, you will learn to assess a system, then implement risk controls. Finally, you will be able to monitor and maintain risk procedures. With this training, you will be able to identify risks associated with specific industries. After course completion, you will be able to design, implement, monitor and maintain risk-based, efficient and effective IS controls. Knowledge of all of these areas will be required to pass the CISRM exam. Course Outline The Big Picture Domain 1 ? Risk Identification Assessment and Evaluation Domain 2 ? Risk Response Domain 3 ? Risk Monitoring Domain 4 ? IS Control Design and Implementation

This workshop-based bite-size will provide space to explore some practical tools and ideas on how to be more resilient when faced with challenging and tough situations. There is an opportunity to do a self assessment and bring it to the day as a means to identify areas to work on and begin to master skills that will enhance resilient thinking. There will be time to explore what resilience is and understand the range of practical tools and techniques available that can be used beyond the workshop itself. By the end of the workshop participants will be able to: Discuss and evaluate their personal strengths and areas for development in being more resilient at work Understand what resilience involves and how to identify and challenge their own beliefs that undermine resilience Understand the four aspects of resilience - confidence, adaptability, building support and maintaining a clear perspective Understand how to use resiliency tools to help to cope better with the challenge of change Review and evaluate their learning and have an action plan to take back and implement in the workplace 1 Welcome, introductions and objectives Breaking the ice 2 Identifying current challenges in relation to work How we handle these challenges 3 Defining resilience and how and why it helps our personal effectiveness and thinking 4 Resilience skills and how to develop them 5 Learning a resilience tool that promotes new ways of thinking / working 6 Review and evaluation of learning Action planning

This workshop is very practical in its nature and aims to give delegates an opportunity to not only learn about the key aspects of successful bid writing, but to also put them into practice. The workshop helps delegates understand what is most important to buyers and how to successfully convey they proposition to them. 1 Welcome and introductions 2 The mindset of successful bid writing The mindset needed for successful bid writing Thinking from the buyer's perspective and not your own 3 Decision making The way buyers make decisions - rational and emotional Understanding buying motives Looking at how to present ideas against those motives The idea of cognitive fluency How to pitch an idea in a way that leads to a positive decision 4 To bid or not to bid? Writing a bid is a big commitment; a clear understanding of the chances of winning is required Understanding of the implications of winning and the impact it will have on the organisation 5 Understanding your value proposition Framework to help identify unique proposition and how that fits in with the requirements of the bid 6 The tender process Understanding the process to enable a successful chance of winning the bid Different types of tender processes Evaluation of criteria and the impact on bid writing 7 Writing skills Different ways of writing and structuring bids to ensure their messages gets across well in a way that will be looked on favourably by the buyer 8 Summarise 9 Close

We all tend to have challenges throughout our lives that cause varying levels of pressure. It is healthy and essential that people experience such challenges because up to a certain point an increase in pressure improves performance and quality of life. Too much pressure can be harmful and affect our health and wellbeing. This participative half-day workshop will explore the causes and impact of stress and provide an opportunity to learn some new ideas and techniques to cope with it. Practical tasks and exercises will be used to promote discussion and participants will be encouraged to share their own experiences and approaches. By the end of the workshop participants will be able to: Understand the causes and symptoms of stress and how to spot them Become more aware of personal habitual behaviours and approaches that get in the way of dealing with stress productively Learn ideas and approaches that help you to cope with the thoughts, emotions and physical feelings that happen in stressful and difficult situations Review and evaluate learning and have an action plan to take back and put into practice at work 1 Welcome, introductions and objectives Breaking the ice 2 Stress Its sources and effects on you Defining stress, its signs and symptoms 3 Exploring your 'default' habits Their consequences in stressful situations 4 Dealing with perception Strategies and approaches for coping with stress 5 Setting goals with positive outcomes Review and evaluation of learning Action planning

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.