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Introducing Celebrity Therapist London Package: Discreet and Customized Counseling for Public Figures Are you a public figure seeking confidential and personalized counseling in London? Miss Date Doctor’s Celebrity Therapist London Package offers you discreet and specialized therapy services tailored to meet the unique needs and challenges faced by individuals in the public eye. Being a public figure can come with its own set of stressors and pressures. Our experienced celebrity therapists are dedicated to providing you with a safe and non-judgmental space to address personal concerns, manage stress, and find support for emotional well-being. Here’s how the Celebrity Therapist London Package can support you: Confidentiality: Our celebrity therapists are well-versed in maintaining confidentiality and respecting your privacy at all times. Specialized Support: We offer customized counseling, recognizing the specific challenges that public figures may encounter in their personal and professional lives. Emotional Regulation: Therapy can assist you in managing emotions related to public scrutiny, criticism, and constant attention. Stress Management: We’ll work on stress management techniques to help you navigate the demands of your public role. Coping Strategies: Our therapists will equip you with effective coping strategies to manage the unique stressors you may face. Balancing Personal and Professional Life: Therapy can help you find a balance between your personal life and the demands of your public career. Building Resilience: We’ll focus on developing resilience to handle the challenges of public life with strength and grace. Self-Care and Well-being: Our celebrity therapists emphasize self-care practices to support your emotional and mental well-being. The Celebrity Therapist London Package at Miss Date Doctor is designed to cater to your specific needs as a public figure, offering you a supportive and understanding space to navigate challenges and enhance your overall well-being. Invest in your emotional health and take the first step towards confidential support with the Celebrity Therapist London Package. Embrace the opportunity to receive specialized therapy services tailored to your unique experiences and demands as a public figure. Let our experienced celebrity therapists guide you towards greater emotional resilience, balance, and well-being. 6×1 hour sessions https://relationshipsmdd.com/product/celebrity-therapist-london-package/

Duration 3 Days 18 CPD hours This course is intended for Organizations today demand a professional-level cybersecurity threat intelligence analyst who can extract the intelligence from data by implementing various advanced strategies. Such professional-level programs can only be achieved when the core of the curricula maps with and is compliant to government and industry published threat intelligence frameworks. Ethical Hackers Security Practitioners, Engineers, Analysts, Specialist, Architects, and Managers Threat Intelligence Analysts, Associates, Researchers, Consultants Threat Hunters SOC Professionals Digital Forensic and Malware Analysts Incident Response Team Members Any mid-level to high-level cybersecurity professionals with a minimum of 2 years of experience. Individuals from the information security profession and who want to enrich their skills and knowledge in the field of cyber threat intelligence. Individuals interested in preventing cyber threats. Overview This program will benefit students who are looking to build effective threat intelligence for their organization in order to combat modern-day cyber-attacks and prevent future attacks. Certified Threat Intelligence Analyst (C|TIA) is designed and developed in collaboration with cybersecurity and threat intelligence experts across the globe to help organizations identify and mitigate business risks by converting unknown internal and external threats into known threats. It is a comprehensive, specialist-level program that teaches a structured approach for building effective threat intelligence. Introduction to Threat Intelligence Understanding Intelligence Understanding Cyber Threat Intelligence Overview of Threat Intelligence Lifecycle and Frameworks Cyber Threats and Kill Chain Methodology Understanding Cyber Threats Understanding Advanced Persistent Threats (APTs) Understanding Cyber Kill Chain Understanding Indicators of Compromise (IoCs) Requirements, Planning, Direction, and Review Understanding Organization?s Current Threat Landscape Understanding Requirements Analysis Planning Threat Intelligence Program Establishing Management Support Building a Threat Intelligence Team Overview of Threat Intelligence Sharing Reviewing Threat Intelligence Program Data Collection and Processing Overview of Threat Intelligence Data Collection Overview of Threat Intelligence Collection Management Overview of Threat Intelligence Feeds and Sources Understanding Threat Intelligence Data Collection and Acquisition Understanding Bulk Data Collection Understanding Data Processing and Exploitation Data Analysis Overview of Data Analysis Understanding Data Analysis Techniques Overview of Threat Analysis Understanding Threat Analysis Process Overview of Fine-Tuning Threat Analysis Understanding Threat Intelligence Evaluation Creating Runbooks and Knowledge Base Overview of Threat Intelligence Tools Intelligence Reporting and Dissemination Overview of Threat Intelligence Reports Introduction to Dissemination Participating in Sharing Relationships Overview of Sharing Threat Intelligence Overview of Delivery Mechanisms Understanding Threat Intelligence Sharing Platforms Overview of Intelligence Sharing Acts and Regulations Overview of Threat Intelligence Integration

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Eliminate bad relationship and dating behaviour Improve confidence Understand people better Effective communication skills training Eliminate regressive dating patterns Address poor dating habits Introspection in your character and behavioural patterns Be a better partner 1 month Course 1 hr once a week Dating advice for singles https://relationshipsmdd.com/product/improve-my-relationship-behaviour-package/

Many people have a misconception about networking events, and lose out on new business opportunities as a result. They either don't appreciate the real benefits and techniques of networking and don't attend events, or they attempt to 'sell on the first date', causing resentment. You can either attempt to make a sale for a quick buck (which is particularly likely to backfire at a networking event), or you can try to open a long-term relationship, creating new opportunities and a high lifetime value customer (which is how it's meant to be done). Networking, when done properly, is an excellent tool for referrals. But you have to appreciate that it's done on the basis of giving rather than receiving and this doesn't always come naturally to sales professionals. The old saying that it's about getting to 'know, like and trust' is still true. This workshop is about having your prospects and customers getting to know, like and trust you, and building that lifetime value as a result. By the end of this programme, participants will be able to: Understand what networking is - networking etiquette Know how and where to network Clarify their objectives - why network Use the 4 basic questions to start a conversation Build rapport quickly and easily Answer the question 'What do you do?' effectively in a few seconds Deliver a 60-second pitch Break into a group Prepare for a network meeting Identify opportunities Use tools to assist in networking 1 Introduction Aims and objectives 2 What is networking? Why network - objectives and goal setting Networking etiquette Preparation - online and offline tools to use Identify networking opportunities - where to network Know what you have to offer 'Know, like and trust' - the process 3 What do you do? Answer in 5-10 seconds Create and deliver a 60-second pitch Who is your target market? 4 Starting a conversation Breaking into a group Building rapport The 4 questions to start a conversation Moving on 5 Communicate and engage LISTEN - 4 types of listening skill Ask powerful questions Influence - don't sell What can you do to help others - give to get 6 Power of referrals Who can give you referrals? When to give or ask for referrals Have a referral system Showing appreciation 7 Social media and other online tools Using LinkedIn and other social media Online directories 8 Next steps Following up Arranging one-to-one meetings Developing relationships

Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings

Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

Learn how to use this powerful tool to import and clean data and create some amazing visuals. Course overview Duration: 2 days (13 hours) Power BI Desktop is a powerful tool for working with your data. It enables you to import multiple data sources and create effective visualisations and reports. This course is an introduction to Power BI to get you started on creating a powerful reporting capability. You should have a good working knowledge of Excel and managing data before attending. Objectives  By the end of the course you will be able to: Import data from multiple data sources Edit and transform data before importing Create reports Create different visualisations Create data models Build data relationships Use the drill down features Create measures Use the Power BI Service Build dashboards Use the mobile app Content Essentials Importing Data Power BI Overview Data sources Importing data Transforming Your Data Editing your data Setting data types Removing columns/rows Choosing columns to keep Setting header rows Splitting columns Creating Reports Creating and saving reports Adding pages Renaming pages Interactivity Refreshing your data Adding Columns Columns from example Custom columns Conditional columns Append Queries Importing folders Setting up and using append queries Creating Chart Visualisations Adding chart elements Choosing chart types Setting properties Setting values, axis and legends Using tooltips Visual filters Setting page and report filters Creating Tables, Cards, Gauges and Maps Adding table elements Adding maps Working with cards Working with matrices KPIs and Gauges Conditional Formatting Setting rules Removing conditional formatting   Working with Data Models Merge Queries Setting up and using merge queries Merging in columns of data Creating a Data Model The data model Multiple data tables Connecting tables Building relationships Relationship types Building visuals from multiple tables Unpivoting Data Working with summary data Unpivoting data Using Hierarchies Using built in hierarchies Drill down Drill up See next level Expand a hierarchy Create a new hierarchy Grouping Grouping text fields Grouping date and number fields Creating Measures DAX functions DAX syntax Creating a new measure Using quick measures Using the PowerBI Service Shared workspaces My workspace Dashboards Reports Datasets Drill down in dashboards Focus mode Using Q&A Refreshing data Using Quick Insights Power BI Mobile App Using the Power BI Mobile App

Take your sales people from average to high performance. Motivate and develop experienced sales professionals with some new insights and learning. Applying NLP principles, techniques and models, this workshop will introduce the core attitudes and behaviours that differentiate the excellent sales person from the average one. The programme will help participants: Understand and adopt the mindset and beliefs needed for sales excellence Build rapport and connect with buyers at a deeper and more personal level Recognise some of the thinking and language patterns that make each individual unique Ask powerful questions to further understand the unique world of the individual and how they make decisions Apply tools and techniques to empathise with clients - seeing things from their perspectives Tailor their sales approach to the individual buyer's style, and talk in their language Influence with integrity and sell to organisations and individuals successfully 1 Introduction Aims and objectives of the programme Personal introductions and objectives Workshop overview 2 An introduction to NLP and sales excellence with NLP An overview of NLP and applying it to selling The pillars of NLP The NLP model of communication The difference that makes the difference 3 Building enhanced rapport Defining rapport and why it is important when selling Going beyond the initial small talk Building relationships with individual decision-makers Matching and mirroring Levels of rapport 4 Understanding the buyer's personal buying map How we take in, filter and process information How we judge others based on our own experiences of the world The different ways in which we communicate when selling Recognising and understanding the language and thinking patterns of others Adapting your sales communication style to different buyers 5 Making sense of the buying process How we filter information through our senses Understanding how we see, hear and experience the world Visual, auditory and kinaesthetic buyers Listening for key insights What different buyers want from you to help them to buy Applying sensory awareness to the sales process 6 Successful sales mindset The connection between thoughts and actions The sales beliefs of excellence Identifying negative thoughts and beliefs that are holding you back How to change your mindset Adopting the sales beliefs of excellence 7 Powerful questions Reviewing and honing your questioning skills Understanding the questions that great sales people ask Avoiding assumptions Clean language questions Getting to the bottom of it - precision questions Turbo-charging how you qualify 8 Influencing with integrity Understanding empathy Stepping into the buyer's shoes Speaking the buyer's language Tailoring your sales approach to the individual Match, pace, lead - how to take your buyer with you 9 Putting it all together Personal learning summary and action plans