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Project Leadership Skills (On-Demand) To be effective within an organization, project managers need to have a wide variety of skills and abilities. Included among these are: creating and executing on a vision; motivating others; influencing without authority; networking; communicating up, down and laterally; negotiating; managing stakeholders; and managing conflict. This highly interactive workshop focuses on building the soft skills that are critical to leading a team and creating sustainable business change. Participants will gain insight into the social science as well as the brain science behind motivating and empowering others. They will learn and experiment with a variety of influencing strategies and tactics. Working in pairs as well as small groups, they will collaborate with others to brainstorm, share experiences, and apply concepts to everyday challenges. Participants will also discover their personal communication preferences, strengths, and blind spots and will gain insight into how best to communicate with others they find 'difficult.' They will gain insight into managing the people side of change, learning strategies for dealing with each step in the process. Hands-on negotiation and conflict management activities enhance the theoretical learning, grounding it in real life and making it actionable. Interweaving role play with experiential learning and group activities, this course will help participants refine a skill set that is invaluable to their organization, and one that transfers easily across their professional and personal lives. What You Will Learn At the end of this course, you will be able to: Explain the importance of vision in driving motivation and engagement Apply science-based research to better motivate those around you Strategically leverage both personal and positional power to achieve positive project results Determine influencing and networking strategies needed for personal growth Identify ways to problem solve communication challenges when others have different personality styles Connect stakeholder expectations to project success criteria Assess key stakeholders across various dimensions of complexity Apply the four rules of principled negotiation to a real-life conflict situation Recognize key aspects of a physiological response to conflict Utilize selected tools and techniques to 'defuse' an emotional situation Leverage various strategies and tactics to successfully deal with ambiguity at work Getting Started / Foundation Concepts Introductions Course structure, goals, and objectives Beginning a personal action plan Managing Vision and Purpose / Motivating Others Communicating and aligning around vision Tying the present to the future The importance of purpose The art and science of motivation Networking and Influencing Positive politics and project success Types of power within organizations Power and influence Networking best practices Communication The medium and the message Personality and communication styles Communication challenges Stakeholder Management and Negotiation Identifying stakeholders Analyzing stakeholders Negotiation basics Principled negotiation Conflict Management Dynamics of conflict The anatomy of conflict Conflict management approaches and tools Dealing with ambiguity Summary and Next Steps Key concepts review Creating your personal action plan

This course aims to teach users how to set a baseline and update an un-resourced project with Oracle Primavera P6 PPM Professional. This course teaches intermediate-level skills in Primavera project manager P6 PPM professional client.

Use Cases for Business Analysis: In-House Training The use case is a method for documenting the interactions between the user of a system and the system itself. Use cases have been in the software development lexicon for over twenty years, ever since it was introduced by Ivar Jacobson in the late 1980s. They were originally intended as aids to software design in object-oriented approaches. However, the method is now used throughout the Solution Development Life Cycle from elicitation through to specifying test cases, and is even applied to software development that is not object oriented. This course identifies how business analysts can apply use cases to the processes of defining the problem domain through elicitation, analyzing the problem, defining the solution, and confirming the validity and usability of the solution. What you will Learn You'll learn how to: Apply the use case method to define the problem domain and discover the conditions that need improvement in a business process Employ use cases in the analysis of requirements and information to create a solution to the business problem Translate use cases into requirements Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Overview of use case modeling What is a use case model? The 'how and why' of use cases When to perform use case modeling Where use cases fit into the solution life cycle Use cases in the problem domain Use cases in the solution domain Use case strengths and weaknesses Use case variations Use case driven development Use case lexicon Use cases Actors and roles Associations Goals Boundaries Use cases though the life cycle Use cases in the life cycle Managing requirements with use cases The life cycle is use case driven Elicitation with Use Cases Overview of the basic mechanics and vocabulary of use cases Apply methods of use case elicitation to define the problem domain, or 'as is' process Use case diagrams Why diagram? Partitioning the domain Use case diagramming guidelines How to employ use case diagrams in elicitation Guidelines for use case elicitation sessions Eliciting the problem domain Use case descriptions Use case generic description template Alternative templates Elements Pre and post conditions Main Success Scenario The conversation Alternate paths Exception paths Writing good use case descriptions Eliciting the detailed workflow with use case descriptions Additional information about use cases Analyzing Requirements with Use Cases Use case analysis on existing requirements Confirming and validating requirements with use cases Confirming and validating information with use cases Defining the actors and use cases in a set of requirements Creating the scenarios Essential (requirements) use case Use case level of detail Use Case Analysis Techniques Generalization and Specialization When to use generalization or specialization Generalization and specialization of actors Generalization and specialization of use cases Examples Associating generalizations Subtleties and guidelines Use Case Extensions The <> association The <> association Applying the extensions Incorporating extension points into use case descriptions Why use these extensions? Extensions or separate use cases Guidelines for extensions Applying use case extensions Patterns and anomalies o Redundant actors Linking hierarchies Granularity issues Non-user interface use cases Quality considerations Use case modeling errors to avoid Evaluating use case descriptions Use case quality checklist Relationship between Use Cases and Business Requirements Creating a Requirements Specification from Use Cases Flowing the conversation into requirements Mapping to functional specifications Adding non-functional requirements Relating use cases to other artifacts Wire diagrams and user interface specifications Tying use cases to test cases and scenarios Project plans and project schedules Relationship between Use Cases and Functional Specifications System use cases Reviewing business use cases Balancing use cases Use case realizations Expanding and explaining complexity Activity diagrams State Machine diagrams Sequence diagrams Activity Diagrams Applying what we know Extension points Use case chaining Identifying decision points Use Case Good Practices The documentation trail for use cases Use case re-use Use case checklist Summary What did we learn, and how can we implement this in our work environment?

Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Duration 1 Days 6 CPD hours This course is intended for New administrators, business analysts or report writers who are new to creating reports or dashboards within Salesforce. Overview A student in this class will learn the basic Salesforce object model, and how to create and secure reports and dashboards. The instructor will lead students through exercises to create tabular, summary, matrix and join reports. Students will learn advanced reporting functionality such as charting, report summary fields, bucket fields, conditional highlighting, advanced report filters and building custom report types. Finally, the student will learn how to create and run dashboards and schedule and email reports and dashboards. This course is specifically designed to teach administrators, business analysts or report writers how to utilize the basic and advanced analytic capabilities of Salesforce. Introductions / Login to Training OrgsOverview of Salesforce Object ModelTabular, Summary, Matrix, Join ReportsCharts, Bucket Fields, Report Summary Fields, Conditional HighlightingCustom Report TypesDashboardsReport & Dashboard Scheduling Additional course details: Nexus Humans Introduction to Salesforce.com Analytics - Building Reports and Dashboards 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 Introduction to Salesforce.com Analytics - Building Reports and Dashboards 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 is about developing core skills that will stay with you for a lifetime. It is designed such that you can watch the material and follow along step-by-step. It focuses on the implementation of YOLOv4 to get you up and running. You'll be an object detecting ninja in no time and be able to graduate to more advanced content.

Description Explore the various ways and methods of learning and choose the appropriate learning styles for you by studying the Learning and Development Course. Each learner is different. Therefore learning style is also different for all. A learning style may works on a particular student while another student many benefited from another learning methods. The course focuses on different types of study skill methods, strategies of reading, taking notes, study from books, prioritizing, and more. In the course, you will understand the various types of learning styles and able to choose the best types for you. Additionally, the course shows you some of the effective ways of reading the book and taking notes. The advantages of auditory methods and techniques and the use of visual methods for information assimilation will be thoroughly discussed in the course. By the end of the course, you will able to master ASPIRE strategy and able to take critical reflective learning exercise. Assessment: This course does not involve any MCQ test. Students need to answer assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Once the answers are submitted, the instructor will check and assess the work. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? Learning and Development Course is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Learning and Development Course is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Essential Study Skills Introductory video FREE 00:04:00 Types of study Why do you study? 00:05:00 How do you learn? How do you learn? 00:04:00 Acrostics, Acronyms, Analogies and Mnemonics Acrostics 00:03:00 Acronyms 00:02:00 Analogies 00:01:00 Mnemonics 00:04:00 Reading Reading video - styles & methods 00:06:00 Condensing and Summarising Keywords 00:03:00 Tree structures/diagrams 00:01:00 Spider diagrams 00:02:00 Mind maps 00:02:00 Concept maps 00:02:00 Cue Methods Flash cards 00:02:00 Note taking Skeleton prose 00:04:00 The Cornell Note Taking System 00:03:00 Studying from books PQRST & SQ3R methods 00:07:00 Prioritisation The traffic light approach 00:03:00 Visual methods Method of Loci 00:06:00 The peg or hook system 00:01:00 Auditory Auditory approaches 00:03:00 Don't miss anything out! BRG 00:02:00 PEE 00:02:00 A general strategy The ASPIRE approach 00:03:00 Summary Summary video 1 00:10:00 Summary video 2 00:08:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Dive into the dynamic realm of clinical data analysis with our comprehensive Clinical Data Analysis with SAS course. This course is your passport to the pharmaceutical industry, guiding you through the essential components, phases of clinical trials, and types of data crucial in this field. You'll gain proficiency in interpreting clinical study documents, from protocols to ethical consent, enabling you to navigate the intricate world of clinical data. Our course equips you with SAS programming skills, empowering you to develop clinical study reports, analyze demographic data, and derive valuable insights. Whether you're a budding data analyst or a professional aiming to enhance your clinical data expertise, this course provides the knowledge and skills needed for a successful career in clinical data analysis. Learning Outcomes Understand the key components and phases of the pharmaceutical industry. Navigate clinical trials with insights into data types and reports. Interpret clinical study documents, including protocols and ethical consent. Develop clinical study reports using SAS programming. Analyze demographic data and derive valuable insights. Why choose this Clinical Data Analysis with SAS course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Clinical Data Analysis with SAS course for? Aspiring clinical data analysts seeking to enter the pharmaceutical industry. Professionals in healthcare, research, or data analysis looking to enhance their clinical data expertise. Students and individuals interested in clinical data and its analysis. Those who want to decode clinical study documents and reports. Anyone aiming to unlock the world of clinical data analysis with SAS. Career path Clinical Data Analyst: £25,000 - £50,000 Biostatistician: £30,000 - £70,000 Pharmaceutical Researcher: £25,000 - £60,000 Data Scientist in Healthcare: £30,000 - £70,000 Clinical SAS Programmer: £28,000 - £60,000 Clinical Research Manager: £35,000 - £80,000 Prerequisites This Clinical Data Analysis with SAS does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Clinical Data Analysis with SAS was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Course Promo Course Promo 00:01:00 Section 01: Introduction 1.1 Components of the Pharma Industry 00:05:00 1.2 Phases of Clinical Trials 00:06:00 1.3 Data and Reports in Clinical Trials 00:04:00 1.4 Types of Data 00:05:00 Section 02: Knowledge on Clinical Study Documents 2.1 Clinical Study Protocol 00:02:00 2.2 Ethical Consent 00:01:00 2.3 Inclusion-Exclusion Criteria 00:01:00 2.4 Statistical Analysis Plan: SAP, Mockshell and CRF 00:04:00 Section 03: Developing the Clinical Study Reports 3.1 General SAS Programming Steps 00:02:00 3.2 One Search Report: Demographics Table 00:04:00 3.3 Understanding the Demographics Table 00:03:00 3.4 Programming the Demographics Table 00:05:00 3.5 Importing Raw Demographic Data into the SAS 00:04:00 3.6 Deciding what Procedure to Use 00:02:00 3.7 Deriving the AGE variable 00:10:00 3.8 Obtaining Summary Statistics for AGE 00:04:00 3.9 Adding the 3rd Treatment Group using Explicit Output 00:05:00 3.10 Deriving the SEX variable 00:03:00 3.11 Obtaining Summary Statistics for SEX 00:03:00 3.12 Concatenating the COUNT and PERCENT Variables 00:03:00 3.13 Deriving the RACE Variable 00:03:00 3.14 Obtaining Summary Statistics for RACE 00:03:00 3.15 Stacking All the 3 Summary Statistics Together 00:06:00 3.16 Fixing the Precision Points 00:04:00 3.17 Transposing Data 00:03:00 3.18 Fixing the Order of Statistical Parameters 00:05:00 3.19 Building the Final Report 00:02:00 3.20 Putting the Final Touches to the Report 00:11:00 Resources Resources - Clinical Data Analysis with SAS 00:00:00 Assignment Assignment - Clinical Data Analysis with SAS 00:00:00

Learn JavaScript from Scratch: JavaScript for Everyone is a hands-on course that teaches the ins and outs of modern JavaScript. It is the perfect course for anyone who wants to learn the programming language from scratch and wants to develop engaging, interactive websites that leverage all the latest features JavaScript comes with.

This course is not suitable for total beginners. To attend this course, you must already have some experience with industrial machines and be able to operate and set up a walking foot independently, or have attended our MODULE 3 – INDUSTRIAL MACHINE TRAINING. Summary of topics covered in the class: – Pattern making, pattern development and pattern vocabulary – Leather preparation, pattern placement, and leather marking – Leather cutting, gluing, and reinforcing – Patterns development, assembling and making for different card holder constructions By the end of the tuition, you will have: – Developed your understanding of pattern drafting and pattern development – Understood the concept of seam, folding, and trimming allowances when drafting patterns – Created some finished patterns, constructed and completed up to 3 finished card holders (depending on your personal abilities the quantity might change) – Learned how to use your patterns to correctly cut your material, minimising waste and using the best parts of a hide/skin – Worked with a variety of tools for pattern making and leatherworking, as well as various types of leather – Developed essential leather craft skills such as preparation, marking, finishing, cutting, and more – Obtained a basic understanding of the differences and best uses of reinforcements, stiffeners and stabilisers Included in the course: You will receive useful paper handouts containing: – A list of tools and materials used during the lesson(s), with descriptions and usage instructions – A list of recommended suppliers for leather and fittings, both in London and online – A glossary containing pattern making terms and general guidelines for pattern drafting All materials are included, there are no additional costs. Find all modules here: https://the-london-leather-workshop.cademy.co.uk/