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Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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 in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

Duration 3.75 Days 22.5 CPD hours This course is intended for New systems administrators Overview When you complete this course, you will be able to:Customize your application, including page layouts, fields, tabs, and business processes in Lightning Experience.Learn how security settings created in Salesforce Classic are applied in Lightning.Maintain and import clean data in Lightning.Use Lightning features to create high-value reports and dashboards.Understand how workflow automation complies with Lightning This course is the core training that ensures your success with Salesforce Lightning. It?s a must for new administrators, and we recommend completing this course before starting a Salesforce deployment or when taking over an existing deployment. Getting Around the App Data Model and Navigation Lightning Experience Help & Training Getting Your Organization Ready for Users Setting Up the Company Profile Configuring the User Interface Setting Up Activities and Calendars Configuring Search Settings Setting Up Chatter Groups Mobile Access with Salesforce1 Setting Up & Managing Users Managing User Profiles Managing Users Setting Up Chatter Free Users and Invites Troubleshooting Login Issues Security & Data Access Restricting Logins Determining Object Access Setting Up Record Access Creating a Role Hierarchy Dealing with Record Access Exceptions Managing Field-level Security Object Customizations Administering Standard Fields Creating New Custom Fields Creating Selection Fields: Picklists and Lookups Creating Formula Fields Working with Page Layouts Working with Record Types and Business Processes Maintaining Data Quality Managing Data Import Wizards Data Loader Data.com Mass Transfer Backing Up Data Mass Delete and Recycle Bin Reports & Dashboards Running and Modifying Reports Creating New Reports with the Report Builder Working with Report Filters Summarizing with Formulas and Visual Summaries Printing, Exporting, and Emailing Reports Building Dashboards Automation Email Templates Workflow Rules Process Builder Lead Automation Managing the Support Process Managing and Resolving Cases Customizing a Support Process Automating Support Understanding the Salesforce Console for Service Collaborating in the Service Cloud Analyzing Support Data Additional course details: Nexus Humans Salesforce Administration Essentials for New Admins in Lightning Experience (ADX201) 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 Salesforce Administration Essentials for New Admins in Lightning Experience (ADX201) 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.

R&D work is often carried out in entrepreneurial companies with the aim of developing solutions to scientific or technological problems for a wide range of customers. Projects can include longer term 'frontiers of science' research, medium term product development/manufacturing or more immediate troubleshooting or contract research assignments. In all these contexts, the ability to create innovative solutions in a timely and cost-effective manner is the essence of successful R&D. Whilst R&D groups typically excel in technical expertise, those involved often recognise that there is scope for improving the way that projects are managed. The aim of this training programme is to address this need whilst ensuring that the creative, entrepreneurial spirit that is fundamental to good R&D continues to flourish. MODULE 1: Creating the foundations for success Off-line video tutorials and exercises Total time ~ 1 - 1.5 hours Video 1: Making the most of project management in R&D Characterising R&D projects Applying project management to R&D work Exploiting the potential of project management in R&D Video 2: Promoting success in R&D project management Modelling successful project management Evaluating performance and promoting success The role and skills of the project manager/leader MODULE 2: Initiating and defining R&D projects Live interactive sessions (via Zoom): Session 1: 10:00 - 12:00 Session 2: 14:00 - 15:30 Session 1: Selecting and initiating projects Recognising worthwhile opportunities; initiating projects Identifying stakeholders and their goals Characterising and engaging stakeholders Session 2: Defining goals and agreeing deliverables Establishing the full scope of the project Clarifying and prioritising project deliverables Defining and agreeing deliverable specifications MODULE 3: Planning R&D projects Live interactive sessions (via Zoom): Session 1: 10:00 - 12:00 Session 2: 14:00 - 15:30 Session 1: Identifying and organising activities Creating effective plans; avoiding planning pitfalls Identifying tasks and assigning responsibilities Sequencing tasks and estimating durations Session 2: Developing the timeline and resource plan Identifying the 'critical path'; creating a resource plan Dealing with estimating uncertainty Accelerating the programme MODULE 4: Leadership and teamwork in R&D projects Off-line video tutorials and exercises Total time ~ 1 - 1.5 hours Video 1: Working effectively in project teams Building teamwork in contemporary organisations Recognising each other's skills; building synergy Building good working relationships; handling conflict Video 2: The role of the R&D project team leader Building teamwork: the role of leadership Creating an effective team culture Delegating work and motivating team members MODULE 5: Managing uncertainty in R&D projects Live interactive sessions (via Zoom): Session 1: 10:00 - 12:00 Session 2: 14:00 - 15:30 Session 1: Characterising uncertainty; identifying risks Exploring uncertainty; applying risk management Focusing the risk management process Identifying and defining risk events Session 2: Managing and controlling risks to the project Evaluating risk events Selecting between risk strategies; setting contingencies Updating and controlling exposure to risk MODULE 6: Implementing and controlling R&D projects Live interactive sessions (via Zoom): Session 1: 10:00 - 12:00 Session 2: 14:00 - 15:30 Session 1: Initiating assignments and managing changes Creating a pro-active implementation and control culture Establishing effective implementation and control procedures Assigning work and managing changes Session 2: Monitoring, managing and developing performance Adopting meaningful monitoring techniques Responding to problems; building performance Managing and controlling multiple project assignments

Self-understanding is a prerequisite for leading and managing others responsibly and honourably. The field of Neuro Linguistic Programming has helped us to gain a better insight into how we all think and behave. Upon completion of this course participants will be able to: Gain an insight into the purpose and functions of the unconscious mind Develop flexibility to increase their for behaviours in different circumstances Appreciate how different people experience the world Create and set effective goals and direction Understand the NLP Model of Communication Adapt their communication style to maximise effectiveness Influence and persuade others by connecting with people Understand how empowerment can make life easier Appreciate how creativity works Learn creativity techniques to tap into the power of the team 1 Self-awareness Autopilot - your unconscious mind Developing flexibility How identify, values & beliefs shape our behaviour Models of the world 2 Creating direction Describing present and desired state Designing your direction Making it happen Self-mastery 3 Communication The NLP Model of Communication Insights to the way people think Understanding representation systems Reframing the way people think about negative experiences Using metaphor 4 Influence and persuasion Building trust Connecting with people Purpose intention and outcomes The difference empowerment makes 5 Creativity and innovation Hindrances to creativity and innovation Your natural state of creativity Getting unblocked Creativity techniques 6 Action plan Course summary and presentation of action plans

Duration 2 Days 12 CPD hours This course is intended for Software Test Engineers and Test Leaders with minimum two years of experience. Specialists who have experience in software testing and want to deepen both their theoretical and practical knowledge. Overview Please refer to Overview. Practical training that you will learn how to apply additional tools in your work which will help you to optimize it. You will be able to analyze requirements better and to prioritize your tasks. Requirements analysis Effective approaches in requirements analyze What does 'Good Requirement' mean? Change Management Subsystems and actors Practice - Analysis of an actual functional specification Applicable Models and Priorities Specifications of the extraordinary models software projects Prioritizing the tasks of the test team Practice case - Iteration and sprint specifications Test planning Test design approaches Applicable techniques Practice cases with different techniques Defects management Defect status management Applicable metrics Best practices Practical examples of extraordinary applications Additional course details: Nexus Humans Modern approaches and practical tips in software testing 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 Modern approaches and practical tips in software testing 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.

Leading People through Change (Virtual) Research shows that 70% of change initiatives fail in large organizations. The largest factor contributing to this failure rate is leadership - the inability to plan and lead people through change. In many change situations, tremendous focus is put on strategy, processes, and systems, while the issue of changing people's behavior is assumed it will 'just happen'. In this interactive course, you will learn why the people side of change is crucial. We will begin by understanding why and how people resist change, and how important it is to become strong and effective change champions. Next, we will focus on critical change management practices - creating our vision of the future state, planning for acceptance in our change audience and stakeholders, mitigating threats, and capitalizing on opportunities. We will use metrics to plan, show progress, and confirm success. Lastly, we will focus on the need to reinforce and sustain change, and to prevent relapse to old ways and methods. What you will Learn At the end of this program, you will be able to: Realize the nature of change and describe how resistance manifests in people Compare prevalent change models and categorize their similarities Identify and rate the skills, traits, and behaviors of effective change champions Envision the future state and assess stakeholders Plan for change communication, training, and risks Evaluate change effectiveness using feedback and metrics Develop reinforcement practices for benefits and communication Getting Started Foundation Concepts What is Change? Resistance to Change Common Change Management Theories Becoming a Change Champion Plan Envisioning the future state Planning for people Change management plan Do Change communication Training Piloting Risks Study Feedback Metrics Variance analysis Act Benefits realization Change sustainment Reinforcement messaging and communications Summary and Next Steps

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The MindGYM is a brain training App that works scientifically to develop the neuroplasticity of your mind, so you can become a creative and innovative genius, thinking quicker in super-states of creativity and creative people-solving, whilst in gamma and theta brain waves of flow state and hemispheric synchronisation. You will be able to tap into boundless energy, and develop your physical and mental capabilities. In effect, the app gives you the mind and the body, to manifest into your life of your greatest desire.