1668 Summary courses

Duration 5 Days 30 CPD hours This course is intended for Channel Partner / Reseller Customer Employee Overview At course completion students will be able to: - Explain the need for QoS, describe the fundamentals of QoS policy, and identify and describe the different models that are used for ensuring QoS in a network - Explain the use of MQC and AutoQoS to implement QoS on the network and describe some of the mechanisms used to monitor QoS implementations - Given a converged network and a policy defining QoS requirements, classify and mark network traffic to implement the policy - Use Cisco QoS queuing mechanisms to manage network congestion - Use Cisco QoS congestion avoidance mechanisms to reduce the effects of congestion on the network - Use Cisco QoS traffic policing and traffic shaping mechanisms to effectively limit the rate of network traffic - Given a low speed WAN link, use Cisco link efficiency mechanisms to improve the badwidth efficiency of the link - Describe the recommended best practices and methods used for end-to-end QoS deployment in the enterprise This course provides students with knowledge of IP QoS requirements, conceptual models such as best effort, IntServ, and DiffServ, and the implementation of QoS on Cisco platforms. Introduction to QoS Review Converged Networks Understand QoS Describe Best-Effort and Integrated Services Models Describe the Differentiated Services Model Module Summary Module Self-Check Implement and Monitor QoS MQC Introduction Monitor QoS Define Campus AutoQoS Define WAN AutoQoS Module Summary Module Self-Check Lab 2-1: IP SLA Setup and QoS Baseline Measurement Lab 2-2: Configuring QoS with Cisco AutoQoS Classification and Marking Classification and Marking Overview Case Study 3-1: Classification and Marking MQC for Classification and Marking NBAR for Classification Use of QoS Preclassify Campus Classification and Marking Module Summary Module Self-Check Lab 3-1: Classification and Marking Using MQC Lab 3-2: Using NBAR for Classification Lab 3-3: Configuring QoS Preclassify Lab 3-4: Campus Classification and Marking Using MQC Congestion Management Queuing Introduction Configure WFQ Configure CBWFQ and LLQ Configure Campus Congestion Management Module Summary Module Self-Check Lab 4-1: Configuring Fair Queuing Lab 4-2: Configuring LLQ-CBWFQ Lab 4-3: Configuring Campus-Based Queuing Mechanisms Congestion Avoidance Congestion Avoidance Introduction Configure Class-Based WRED Case Study 5-1: WRED Traffic Profiles Configure ECN Describe Campus-Based Congestion Avoidance Module Summary Module Self-Check Lab 5-1: Configuring DSCP-Based WRED Lab 5-2: Configuring WTD Thresholds Traffic Policing and Shaping Traffic Policing and Shaping Overview Configure Class-Based Policing Campus Policing Configure Class-Based Shaping Configure Class-Based Shaping on Frame Relay Interfaces Configure Frame Relay Voice-Adaptive Traffic Shaping and Fragmentation Module Summary Module Self-Check Lab 6-1: Configuring Class-Based Policing Lab 6-2: Configuring Class-Based Shaping Link Efficiency Mechanisms Link Efficiency Mechanisms Overview Configure Class-Based Header Compression Configure LFI Module Summary Module Self-Check Lab 7-1: Configuring Class-Based Header Compression Lab 7-2: Configuring LFI Deploying End-to-End QoS Apply Best Practices for QoS Policy Design End-to-End QoS Deployments Module Summary Module Self-Check Lab 8-1: Mapping Enterprise QoS Policy to the Service Provider Policy Additional course details: Nexus Humans Cisco Implementing Cisco Quality of Service v2.5 (QOS) 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 Cisco Implementing Cisco Quality of Service v2.5 (QOS) 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.

This course will walk you through a whole real-world scenario for developing and deploying an ecommerce website with Blazor, and we will tackle numerous obstacles along the way. You will learn how to create a .NET 6 API from scratch and deploy .NET API, Blazor WASM, and Server to Azure in this course.

Classroom/in-person IAM Diploma course in Central Manchester UK. Get trained in Advanced Asset Management.

Facilitating Effective Meetings (Virtual) Billions of dollars and exorbitant amounts of time are wasted annually across the globe because of organizations' meeting practices. This contributes to serious performance problems for both organizations and employees, and it has a serious impact on culture and morale. But despite the costs and consequences, every-day people in any role have the ability to change that. They can reduce cost, improve productivity, and enhance their workplace cultures by improving their meeting facilitation skills. And that is because facilitation skills start in the planning stage, not in the live meeting stage. In this course, participants will learn that their responsibility as a facilitator is to be a steward of time, money, relationships, and performance. To do that, they will learn to estimate costs of meetings and practice a variety of strategic thinking and analysis tasks to effectively plan results-aligned meetings. They will also apply several techniques and strategies to proactively prevent and deal with conflict in meetings, as well as give objective, constructive feedback to others in order to create behavior change during meetings. Participants must bring laptops with them and have internet access during the course (both virtual classroom and traditional classroom). The laptops are needed for specific activities. Also note that this course pairs well with IIL's Conflict Resolution Skills and Decision Making and Problem Solving courses, which go much deeper into related skills and tools that support effective meeting facilitation. What you will Learn At the end of this program, you will be able to: Estimate the financial and time costs of attendance for real-world meetings Use a performance formula to define the purpose of meetings Describe the responsibilities and qualities of an effective facilitator Analyze situations to determine when a meeting is necessary Articulate performance-driven meeting goals and results Align meeting goals and results Strategize to invite, involve, and exclude appropriate attendees Explain research-based best practices for meeting decisions and agenda development Create an effective agenda for a results-driven meeting Apply proactive tools and strategies for relationship-building dealing with meeting conflict Give constructive behavioral feedback using the Situation-Behavior-Impact® technique Getting Started The Business Case for Effective Facilitation Embracing the research on meetings Estimating the real costs of meetings Determining a meeting's performance value Clarifying the meeting facilitator's role Facilitating the Meeting Plan Determining if a meeting is necessary Aligning meeting goals with meeting types Identifying the right attendees Creating a strategically effective agenda Facilitating the Live Meeting Building relationships from the start Dealing with conflict proactively Giving feedback on unproductive behavior Summary and Next Steps

Grateful Leadership™ - Using the Power of Acknowledgment­® to Engage All Your People and Achieve Superior Results: On-Demand Effective leaders must find ways to enhance people's level of engagement, commitment, and support, especially during the difficult periods of time that all organizations may face. Grateful Leaders can tap into the power of personal commitment and dedication by acknowledging people in an authentic and heartfelt manner. Those leaders who model true acknowledgment behavior will inspire others to do the same and to want to dramatically increase their levels of contribution to the organization, making the power of acknowledgment transformational. What You Will Learn You'll learn how to: Understand and develop the capability to act upon the need for Grateful Leadership to create a culture of appreciation in the workplace Understand the potentially huge benefits of Grateful Leadership in the workplace Overcome the barriers to using acknowledgment Demonstrate the language and subtleties of authentic and heartfelt acknowledgement behavior Describe the Seven Principles of Acknowledgment for "High-Interest Benefits" in the context of participant's personal leadership style Describe how to coach teams, managers, and other corporate stakeholders in using Grateful Leadership to produce breakthrough results Getting Started Introductions Course goals and objectives Introspection on the practice of Grateful Leadership The Workforce Engagement Sustainability Challenge Employees who are engaged, not engaged, and actively disengaged The costs of non-engagement Meeting the workforce engagement challenge Acknowledgment, Engagement, and Leadership Acknowledgment and its benefits Recognition versus acknowledgment 'Challenging people' case study Blanchard, Covey, Keith (Servant Leadership): how acknowledgment fits into these leadership models Leadership and acknowledgment The 5 C's - Consciousness, Courage, Choice, Communication, Commitment Employing the Power of Acknowledgment Overcoming barriers to acknowledgment The Seven High-Interest Benefits Principles of Acknowledgment Exploring the acknowledgment process Applying the Principles of Acknowledgment within the Context of Your Personal Leadership Style Case study The ROI of Grateful Leadership Creating your Grateful Leadership Personal Action Plan™ Creating a Vision Statement for your organization that incorporates Grateful Leadership into your corporate culture The 360° Grateful Leadership Competency Assessment Summary What did we learn, and how can we implement this in our work environments?

NPORS MEWP Supervisor Awareness (N035)

Online Asset Management Diploma course. Sit the IAM Diploma anywhere in the world. February to March 2024

Highlights of the Course Course Type: Online Learning Duration: 1 Hour Tutor Support: Tutor support is included Customer Support: 24/7 customer support is available Quality Training: The course is designed by an industry expert Recognised Credential: Recognised and Valuable Certification Completion Certificate: Free Course Completion Certificate Included Instalment: 3 Installment Plan on checkout What you will learn from this course? Gain comprehensive knowledge about General Data Protection Regulation or GDPR Understand the core competencies and principles of General Data Protection Regulation or GDPR Explore the various areas of General Data Protection Regulation or GDPR Know how to apply the skills you acquired from this course in a real-life context Become a confident and expert data controller or data protection officer GDPR - How to apply the General Data Protection Regulation Course Master the skills you need to propel your career forward in General Data Protection Regulation or GDPR. This course will equip you with the essential knowledge and skillset that will make you a confident data controller or data protection officer and take your career to the next level. This comprehensive GDPR course is designed to help you surpass your professional goals. The skills and knowledge that you will gain through studying this GDPR course will help you get one step closer to your professional aspirations and develop your skills for a rewarding career. This comprehensive course will teach you the theory of effective General Data Protection Regulation or GDPR practice and equip you with the essential skills, confidence and competence to assist you in the General Data Protection Regulation or GDPR industry. You'll gain a solid understanding of the core competencies required to drive a successful career in General Data Protection Regulation or GDPR. This course is designed by industry experts, so you'll gain knowledge and skills based on the latest expertise and best practices. This extensive course is designed for data controller or data protection officer or for people who are aspiring to specialise in General Data Protection Regulation or GDPR. Enrol in this GDPR course today and take the next step towards your personal and professional goals. Earn industry-recognised credentials to demonstrate your new skills and add extra value to your CV that will help you outshine other candidates. Who is this Course for? This comprehensive GDPR course is ideal for anyone wishing to boost their career profile or advance their career in this field by gaining a thorough understanding of the subject. Anyone willing to gain extensive knowledge on this General Data Protection Regulation or GDPR can also take this course. Whether you are a complete beginner or an aspiring professional, this course will provide you with the necessary skills and professional competence, and open your doors to a wide number of professions within your chosen sector. Entry Requirements This GDPR course has no academic prerequisites and is open to students from all academic disciplines. You will, however, need a laptop, desktop, tablet, or smartphone, as well as a reliable internet connection. Assessment This GDPR course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner could grasp from each section. In the assessment pass mark is 60%. Advance Your Career This GDPR course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. Course Curriculum Introduction Trainer Introduction and Course Outline 00:02:00 Why Data Protection? What Exactly is Why Deal with Data Protection Anyway. 00:02:00 How is the Protection of Data Guaranteed. 00:04:00 The Five Basic Principles of Data Protection Introduction 00:01:00 Principle 1: Prohibition of Data Processing and Exceptions to Consent 00:01:00 Principle 2: Purpose of Data Collection 00:03:00 Principle 3: Data Collection Limits 00:02:00 Principle 4: Data Security 00:01:00 Principle 5: Transparency 00:02:00 Summary 00:02:00 The Foundations of Data Processing introduction 00:01:00 Data Processing with Consent 00:03:00 Data Processing without Consent 00:03:00 Rights of Data Subjects Rights of Data Subjects 00:05:00 Responsibility of Data Controller or Processor Introduction 00:01:00 Maintaining a Record of Processing Activities 00:03:00 Technical and Organizational Measures (TOM) 00:01:00 Data Processing 00:02:00 Data Breaches 00:02:00 Summary 00:01:00 The Data Protection Officer The Data Protection Officer 00:02:00 Summary Summary 00:02:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

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

Scrum Product Owner Exam Prep: In-House Training: Virtual In-House Training This workshop prepares you for the Scrum.org PSPO™ I certification. A voucher for the exam and the access information you will need to take the exam will be provided to you via email after you have completed the course. NOTE: If you have participated in any of IIL's other Scrum workshops, you can bypass this program and focus on reading/studying the Scrum Guide and taking practice exams from Scrum.org The Product Owner is responsible for maximizing the value of the product and the work of the Development Team. The Product Owner must be knowledgeable, available, and empowered to make decisions quickly in order for an Agile project to be successful. The Product Owner's key accountability is the Product Backlog. Managing, maintaining, and evolving the Product Backlog involves: Establishing a clear vision that engages the Development Team and stakeholders Clearly expressing Product Backlog items Ordering the items in the Product Backlog to best achieve the vision and goals Ensuring that the Product Backlog is visible, transparent, and clear to all Working with the Development Team throughout the project to create a product that fits the customer's need The Professional Scrum Product Owner™ I (PSPO I) certificate is a Scrum.org credential that enables successful candidates to demonstrate a fundamental level of Scrum mastery. PSPO I credential holders demonstrate an intermediate understanding of the Scrum framework, and how to apply it to maximize the value delivered with a product. They will exhibit a dedication to continued professional development, and a high level of commitment to their field of practice. Scrum.org does not require that you take their own sponsored or any preparatory training. However, training can facilitate your preparation for this credential. And this course is based on IIL's Scrum Product Owner Workshop, which is aligned with The Scrum Guide™. It will provide you with the information you need to pass the exam and IIL will make the arrangements for your online exam. You will be provided with an exam code and instructions, so that you can take the exam at your convenience, any time you are ready after the course. Passwords have no expiration date, but they are valid for one attempt only. See additional exam details on the next page. What you will Learn You'll learn how to: Successfully prepare for the Scrum.org PSPO I exam Identify the characteristics of a successful Product Owner Create a powerful vision statement Apply techniques to understand your customers and the market Manage and engage stakeholders Write effective user stories with acceptance criteria Utilize techniques to visualize and prioritize the Product Backlog Participate in the 5 Scrum events as the Product Owner Understand the Product Owner's role in closing a Scrum project Getting Started Introductions Workshop orientation Exam prep preview Fundamentals Recap Agile Manifesto, values, and mindset Product Owner characteristics Good vs. great Product Owner Product Ownership Product ownership Project vision Understand your customers and market Personas Stakeholder management and engagement The Product Backlog User Stories and Acceptance Criteria Preparing User Stories for a Sprint The Product Backlog Visualizing the Product Backlog Product Backlog Prioritization Technical Debt Sprint Planning and Daily Standups Sprint Planning Planning Poker Team Engagement Daily Standups Sprint Review, Retrospectives, and Closing Sprint Reviews Key Agile Patterns Retrospectives Closing the Project Summary and Next Steps Review of course goals, objectives, and content Exam prep next steps