Emotional Intelligence: In-House Training Emotional Intelligence is a set of emotional and social skills that collectively establish how well we: Perceive and express ourselves Develop and maintain social relationships Cope with challenges Use emotional information in an effective and meaningful way It is a skill set that transfers across all categories of relationships. It is also a predictor of success - both in life and at work. This highly-interactive course delivers a practical approach to developing, improving, and sustaining effective and mutually beneficial relationships. The design of the course involves individual reflection and paired activities, interwoven with small and large group interactions. The EQ-i 2.0® assessment reports will be debriefed over the course of the two days. In addition, participants will delve into their personal strengths and blind spots, and will explore topics including: the neuroscience of emotion, the connection between empathy and performance, and how communication styles impact our perceptions of self and other. Role-play activities give participants the opportunity to try out new behaviors and techniques. The program includes: A personal behavioral profile, the results of which you will bring to your training 2-day highly interactive workshop and experiential learning Optional professional coaching activities initiated in class that can continue over the four months after class ends What you will Learn Recognize your interpersonal strengths and potential blind spots regarding Emotional Intelligence Identify the five domains within the EQ-i 2.0 assessment model Summarize what neuroscience research has discovered about emotions and actions Recognize ways that human beings are physiologically impacted by stress Articulate ways to develop and maintain strong working relationships Describe how emotional intelligence translates into high performance Make use of the EI model and associated competencies Employ strategies for enhancing leadership through Emotional Intelligence Foundation Concepts The biology of emotion Why Emotional Intelligence matters The impact of EI on performance The EQ-I 2.0 Model Overview of the EQ-i 2.0 framework Exploring your report Balancing your EI domains Self: Awareness and Sensitivity Self-awareness and empathy Perception vs. reality Acting by choice, not impulse Other: Communication and Relationship-Building Elements of effective communication Communication styles Communication techniques Neuroscience and Behavioral Change Insights from social neuroscience Making a change
Risk Management for IT Projects IT projects may have direct bottom-line impact on the organization, cost millions of dollars, cause organizational change and change the way the organization is perceived by clients. Many IT projects are notoriously hard to predict and are filled with risk. IT Risk Management takes a comprehensive look at IT project risk management using PMI's PMBOK® Guide Risk Management Model in the context of IT Project Life Cycle phases. The goal of this course is to arm the practitioner with a rigorous, common-sense approach to addressing uncertainty in projects. This approach includes the ability to influence project outcomes, avoid many potential project risks, and be ready to calmly and efficiently respond to unavoidable challenges. What you will Learn You'll learn how to: Describe the risk management process, using the PMBOK® Guide's standard models and terminology Discuss the potential barriers to managing risk effectively in IT project organizations Develop an effective risk management plan for IT projects Identify project risks using IT-specific, practical tools Analyze individual risk events and overall project risk using IT-specific, practical approaches Plan effective responses to IT-specific risk based on the results of risk analysis and integrate risk responses into project schedules and cost estimates Manage and control risk throughout the IT project life cycle Implement selected elements of IT project risk management on your next project Foundation Concepts Basic concepts and purpose Risk and project constraints Risk and corporate cultures Risk management and IT PLC standards Plan Risk Management for IT Projects Plan Risk management process Plan Risk management activities Design a standard template Assess the project-specific needs Tailor the template Produce a project-specific risk management plan Gain consensus and submit as part of overall project plan A risk management plan of IT projects Identify Risks for IT Projects Identify risk process overview Risk categories and examples Risk identification tools Risk events by project life-cycle phases Perform Risk Analysis for IT Projects Perform qualitative risk analysis overview Core qualitative tools for IT projects Auxiliary qualitative tools for cost and schedule estimates When to use quantitative analysis for IT projects Plan Risk Response for IT Projects Plan risk response overview Active risk response strategies for IT projects (Threat and Opportunity) Acceptance and contingency reserves Contingency planning for IT projects Plan risk responses for IT projects Implement Risk Response for IT Projects Implement Risk Responses Executing Risk Response Plans Techniques and Tools Used Continuous Risk Management Monitor Risks for IT Projects Monitor risks overview Monitor risks tips for IT projects Technical performance measurement systems Risk management implementation for IT projects
Risk Management for IT Projects: In-House Training IT projects may have direct bottom-line impact on the organization, cost millions of dollars, cause organizational change and change the way the organization is perceived by clients. Many IT projects are notoriously hard to predict and are filled with risk. IT Risk Management takes a comprehensive look at IT project risk management using PMI's PMBOK® Guide Risk Management Model in the context of IT Project Life Cycle phases. The goal of this course is to arm the practitioner with a rigorous, common-sense approach to addressing uncertainty in projects. This approach includes the ability to influence project outcomes, avoid many potential project risks, and be ready to calmly and efficiently respond to unavoidable challenges. What you will Learn You'll learn how to: Describe the risk management process, using the PMBOK® Guide's standard models and terminology Discuss the potential barriers to managing risk effectively in IT project organizations Develop an effective risk management plan for IT projects Identify project risks using IT-specific, practical tools Analyze individual risk events and overall project risk using IT-specific, practical approaches Plan effective responses to IT-specific risk based on the results of risk analysis and integrate risk responses into project schedules and cost estimates Manage and control risk throughout the IT project life cycle Implement selected elements of IT project risk management on your next project Foundation Concepts Basic concepts and purpose Risk and project constraints Risk and corporate cultures Risk management and IT PLC standards Plan Risk Management for IT Projects Plan Risk management process Plan Risk management activities Design a standard template Assess the project-specific needs Tailor the template Produce a project-specific risk management plan Gain consensus and submit as part of overall project plan A risk management plan of IT projects Identify Risks for IT Projects Identify risk process overview Risk categories and examples Risk identification tools Risk events by project life-cycle phases Perform Risk Analysis for IT Projects Perform qualitative risk analysis overview Core qualitative tools for IT projects Auxiliary qualitative tools for cost and schedule estimates When to use quantitative analysis for IT projects Plan Risk Response for IT Projects Plan risk response overview Active risk response strategies for IT projects (Threat and Opportunity) Acceptance and contingency reserves Contingency planning for IT projects Plan risk responses for IT projects Implement Risk Response for IT Projects Implement Risk Responses Executing Risk Response Plans Techniques and Tools Used Continuous Risk Management Monitor Risks for IT Projects Monitor risks overview Monitor risks tips for IT projects Technical performance measurement systems Risk management implementation for IT projects
Emotional Intelligence (In-Person) Emotional Intelligence is a set of emotional and social skills that collectively establish how well we: Perceive and express ourselves Develop and maintain social relationships Cope with challenges Use emotional information in an effective and meaningful way It is a skill set that transfers across all categories of relationships. It is also a predictor of success - both in life and at work. This highly-interactive course delivers a practical approach to developing, improving, and sustaining effective and mutually beneficial relationships. The design of the course involves individual reflection and paired activities, interwoven with small and large group interactions. The EQ-i 2.0® assessment reports will be debriefed over the course of the two days. In addition, participants will delve into their personal strengths and blind spots, and will explore topics including: the neuroscience of emotion, the connection between empathy and performance, and how communication styles impact our perceptions of self and other. Role-play activities give participants the opportunity to try out new behaviors and techniques. The program includes: A personal behavioral profile, the results of which you will bring to your training 2-day highly interactive workshop and experiential learning Optional professional coaching activities initiated in class that can continue over the four months after class ends What you will Learn Recognize your interpersonal strengths and potential blind spots regarding Emotional Intelligence Identify the five domains within the EQ-i 2.0 assessment model Summarize what neuroscience research has discovered about emotions and actions Recognize ways that human beings are physiologically impacted by stress Articulate ways to develop and maintain strong working relationships Describe how emotional intelligence translates into high performance Make use of the EI model and associated competencies Employ strategies for enhancing leadership through Emotional Intelligence Getting Started Foundation Concepts The biology of emotion Why Emotional Intelligence matters The impact of EI on performance The EQ-I 2.0 Model Overview of the EQ-i 2.0 framework Exploring your report Balancing your EI domains Self: Awareness and Sensitivity Self-awareness and empathy Perception vs. reality Acting by choice, not impulse Other: Communication and Relationship-Building Elements of effective communication Communication styles Communication techniques Neuroscience and Behavioral Change Insights from social neuroscience Making a change Summary and Next Steps
About this Virtual Instructor Led Training (VILT) The energy industry has started its journey to be more data centric by embracing the industry 4.0 concept. As a result, data management - which was considered until recently as a back-office service to support geoscience, reservoir management, engineering, production and maintenance - is now given the spotlight! To become an active stakeholder in this important transition in E&P data management, it is necessary to understand the new technical opportunities offered by the Cloud, Artificial Intelligence and how data governance can pave the way towards more reliable and resilient processes within E&P domain. Several key questions that need to be addressed: Why place more focus on data assets? Is data management just about serving geoscientists or engineers with fresh data? What is the value of data management in the E&P sector for decision making? How to convince the data consumers that the data we provide is reliable? Is the data architecture of my organization appropriate and sustainable? The purpose of this 5 half-day Virtual Instructor Led Training (VILT) course is to present the data challenges facing the energy organizations today and see how they practically solve them. The backbone of this course is based on the DAMA Book of Knowledge for Data Management. The main data management activities are described in sequence with a particular focus on recent technological developments. Training Objectives Upon completion of this VILT course, the participants will be able to: Understand why the data asset is now considered as a main asset by energy organizations Appreciate the importance of data governance and become an active stakeholder of it Understand the architecture and implementation of data structure in their professional environment Get familiarized with the more important data management activities such as data security and data quality Integrate their subsurface and surface engineering skills with the data managements concepts This VILT course is unique on several points: All notions are explained by some short presentations. For each of them, a set of video, exercises, quizzes will be provided to help develop an engaging experience between the trainer and the participants A pre-course questionnaire to help the trainer focus on the participants' needs and learning objectives A detailed reference manual A lexicon of terms for data-management Limited class size to encourage the interactivity Target Audience This VILT course is intended for: Junior/new data managers Geoscientists Reservoir engineers Producers Maintenance specialists Construction specialists Human resources Legal Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-days consisting 4 hours per day, with 2 breaks of 10 minutes per day. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your expert course leader is a geologist by education who has dedicated his career to subsurface data management services. In 2016, he initiated a tech startup dedicated to Data Management using Artificial Intelligence (AI) tools. He is heavily involved in developing business plans, pricing strategies, partnerships, marketing and SEO, and is the co-author of several Machine Learning publications. He also delivers training on Data Management and Data Science to students and professionals. Based in France, he was formerly Vice President, Sales & Marketing at CGG where he was in charge of the Data Management Services strategy, Sales Manager at Spie O&G Services where he initiated the Geoscience technical assistance activities and Product Manager of interactive seismic inversion software design and marketing at Paradigm. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations
Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence
Business Intelligence Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence
Low laser Lipo therapy(LLLT) What is LLLT? Low-level laser therapy is a form of medicine that applies low-level lasers or light-emitting diodes to the surface of the body. Whereas high-power lasers are used in laser medicine to cut or destroy tissue, it is claimed that the application of low-power lasers relieves pain or stimulates and enhances cell function Course content * Health and safety * Sterilisation and disinfection * Appearance of the therapist * Ergonomics * Laser lipolysis * History of light and energy devices * Properties of laser light * Selective photo thermolysis * Laser classifications * Why do we put on weight * Subcutaneous fat * White and brown adipocytes * Cellulite * Client consultation * Consultation form * Contraindications * Treatment protocol * Aftercare How does the course work? The course is divided into 2 parts, the first part is theoretical which you have to complete before you come for your practical training, and the second one is a practical assignment. The practical assignment is done on the day which will be agreed upon course purchase. You will spend around 2-3 hours practising on a model in our venue in London E106RA. We will call you to arrange date once you sign up for the course. Will I require a model? Yes, usually 1 model is required Do I Need Experience Before Booking a Course? We’re pleased to offer courses to people with lots of different experiences. However, previous experience nor qualifications are not necessary if you would like to enrol on our Course. Certificate You will receive an end of course certificate which is accredited by the cpd group and allows you to work on public Payment By paying for the course you agree to our Terms and Conditions
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