3400 Intelligence courses

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

Course Objectives By the end of this course, participants will be able to: Differentiate between coaching and mentoring and understand their unique purposes. Apply effective communication and active listening skills in developmental conversations. Use coaching models to guide structured conversations. Build trust and psychological safety in coaching and mentoring relationships. Create actionable development plans and track progress. Understand ethical boundaries and confidentiality. Course Outline Day 1: Foundations of Coaching and Mentoring Session 1: Introduction and Context What is coaching? What is mentoring? Key differences and when to use each Benefits to individuals and organisations Session 2: Core Skills for Effective Coaching and Mentoring Active listening Powerful questioning Giving and receiving feedback Empathy and emotional intelligence Session 3: Building Trust and Creating Psychological Safety Establishing rapport Confidentiality and ethical guidelines Setting boundaries and expectations Session 4: Coaching Models and Frameworks GROW Model (Goal, Reality, Options, Will) OSKAR and CLEAR frameworks Practical application and role play Day 2: Practising and Embedding Coaching and Mentoring Session 5: The Coaching and Mentoring Conversation Structuring conversations Using real-life workplace examples Practice with feedback Session 6: Setting Goals and Development Plans SMART and CLEAR goal setting Creating growth-focused action plans Monitoring progress and accountability Session 7: Mentoring for Career and Leadership Development Mentor roles and responsibilities Supporting long-term growth and resilience Reverse mentoring and cross-generational partnerships Session 8: Embedding a Coaching and Mentoring Culture How to support coaching within your team or organisation Integrating into performance conversations Sustaining development through peer coaching and communities of practice Assessment and Evaluation Participation in discussions and practical activities Feedback on peer coaching/mentoring exercises Optional personal development plan submission Course Materials Provided Participant workbook Coaching and mentoring toolkit (templates, models, guides) Suggested reading and resource list

Overview of Entrepreneurship & Innovation Management Join our Entrepreneurship & Innovation Management course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Entrepreneurship & Innovation Management course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Entrepreneurship & Innovation Management course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Entrepreneurship & Innovation Management Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Entrepreneurship & Innovation Management. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online — Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion – Digital / PDF Certificate After completing the Entrepreneurship & Innovation Management course, you can order your CPD Accredited Digital/ PDF Certificate for £5.99. Certificate of Completion – Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Entrepreneurship & Innovation Management is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand. On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level. This course has been developed with maximum flexibility and accessibility, making it ideal for people who don’t have the time to devote to traditional education. Requirements You don’t need any educational qualification or experience to enrol in the Entrepreneurship & Innovation Management course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Entrepreneurship & Innovation Management Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors.

Ready to break free from emotional baggage and embrace inner peace? Our course is designed for those looking for quick, effective ways to release their anger. Join us on a journey of cathartic release and emotional healing.

Duration 2 Days 12 CPD hours This course is intended for This course is suited to marketeers, business analysts, and researchers who are interested in increasing their statistical knowledge. Overview After attending this course, delegates will understand how statistics can be used to provide valuable insight into their business, and be able to apply statistical methods to solve business problems. On returning to work delegates will immediately be able to make a difference to the way that their organisations make decisions. This course covers the statistical methods that analysts need to move from simple reporting on business problems to extracting insight to solve business problems. Course Outline The course will explore the following topics through a series of lectures and workshops: Summary statistics for both continuous data and categorical data Using and reporting confidence intervals Using hypothesis tests to answer business questions Using correlations to explore data relationships Simple prediction models Analysing categorical data Additional course details: Nexus Humans Data-driven Business Using Statistical Analysis 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 Data-driven Business Using Statistical Analysis course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.This skills-focused ccombines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Applied AI: Building Recommendation Systems with Python (TTAI2360) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 2 Days 12 CPD hours This course is intended for It is appropriate for Managers, Executives, Project Managers, Business Analysts, Business and IT stakeholders working with analysts, Quality and process engineers, technicians, managers; supervisors, team leaders, and process operators. Overview Describe business process improvement (BPI) business drivers.Plan, manage and close requirements for a Business Process Improvement project Understand the essential elements of a successful BPI initiative.Identify candidate business processes for improvement.Understand the essential elements of a successful BPI initiative.Identify candidate business processes for improvement.Apply a methodology to business process improvement projects. This 2-day course aims at introducing its attendees to the core values, principles, and practices of Business Process Improvement. Introduction - A Business Process Improvement (BPI) Overview Why are we here today? What is BPI? Benefits of BPI Specific challenges/obstacles and successes Process improvement examples: Industry specific examples Famous debacles to avoid and successes to emulate Your role in helping to identify problems Overview of the Joiner 7-Step Method What is the Joiner 7-Step Method? Walkthrough of the Joiner 7-Step Method Template: Introduce and review Process Improvement Template Case Study Exercise: Read and discuss introduction to the Case Study Step #1: Initiate the Project Types of business problems typically encountered at insurance companies and banks How to recognize a business-related problem Identifying the gaps (delta between current and future states) Ownership of the project and the business problem Defining measurable success criteria Case Study Exercise: Complete the Problem Statement section (Step #1) of the template Step #2: Define Current Situation What are symptoms of a problem? Looking for symptoms of the problem Performing Stakeholder Analysis Technique: View a RACI Matrix Defining the impacts caused by the problem Technique: Business Process Modeling (As-Is) Understand how to draw an As-Is Business Process Model Case Study Exercise: Complete the Define Current Situation section (Step #2) of the template Step #3: Identify Root Causes What are root causes? Performing Root Cause Analysis Technique: Fishbone Diagram using the cafeteria example Case Study Exercise: Discuss a Fishbone Diagram Technique: Pareto Chart (discuss and show example) Case Study Exercise: Complete the Identify Root Causes section (Step #3) of the template Step #4: Develop Solutions Identifying options for problem resolution Avoid jumping to conclusions Technique: Brainstorming Case Study Exercise: Conduct a Brainstorming Session Recognizing pros and cons for each option Technique: Kempner-Tregoe (?Must-Have? vs. ?Nice-to-Have?) Case Study Exercise: Determine best solution using a ?simple? Kempner-Tregoe model Case Study Exercise: Complete the Develop Solutions section (Step #4) of the template Step #5: Define Measurable Results Prototyping the solution Technique: Business Process Modeling (To-Be) Measuring results against the success criteria (Step #1) Case Study Exercise: Review changes to an As-Is Business Process Model Case Study Exercise: Complete the Define Measurable Results section (Step #5) of the template Step #6: Standardize Process Defining how the process will be documented Plan and understand organizational readiness Discuss how employees are empowered to identify and act upon their ideas Identifying follow-up needs (i.e., training) for the staff that will be impacted Technique: Communication Plan Case Study Exercise: Complete the Standardize Process section (Step #6) of the template Step #7: Determine Future Plans Monitoring the process for Continuous Process Improvement (The ?Plan-Do-Check-Act? Cycle) Understand how to sustain the improvements made by the Joiner 7-Step Method Technique: PDCA form Case Study Exercise: Complete the Determine Future Plans section (Step #7) of the template Going Forward with a Plan of Action Identifying process problems in your organization Individual Exercise: Name three (3) possible areas for improvement Prioritize and define the next steps Individual Exercise: Using a new template complete Step 2 & Step 3 for one possible area for improvement you have identified

Course Duration: Half-day, 1-day, or modular delivery over 2–3 sessions Target Audience: Managers, team leaders, HR professionals, and employees who want to foster trust, openness, and inclusivity within their teams or organisations. Course Objectives By the end of this course, participants will be able to: Understand the concept and importance of psychological safety. Recognise how psychological safety impacts team performance and wellbeing. Identify behaviours and practices that support or undermine psychological safety. Develop strategies to create inclusive, respectful, and open team cultures. Apply tools to encourage constructive feedback, innovation, and open dialogue. Course Outline Module 1: What is Psychological Safety? Definition and origin (Dr Amy Edmondson’s research) Why psychological safety matters: the business and human case Link between psychological safety, innovation, collaboration, and retention Misconceptions: It’s not about comfort or avoiding challenge Module 2: Assessing the Current Environment Signs of a psychologically safe vs unsafe environment Common team behaviours and leadership pitfalls Self-assessment: how psychologically safe is my team? Module 3: Building the Foundations The four stages of psychological safety: Inclusion safety Learner safety Contributor safety Challenger safety Role of trust, empathy, and emotional intelligence The leader’s role in creating safe environments Module 4: Practical Strategies to Foster Safety Encouraging open communication and constructive disagreement Creating space for risk-taking and vulnerability Responding to feedback and mistakes without blame Speaking up behaviours – how to model and support them Module 5: Embedding Psychological Safety into Team Culture Meeting practices that promote psychological safety How to give and receive feedback safely Inclusive decision-making and respectful challenge Recognising and rewarding candour and contribution Module 6: Leading with Psychological Safety Coaching conversations and active listening Managing difficult conversations and underperformance safely Supporting neurodiverse or marginalised voices Sustaining safety under pressure and during change Delivery Style Facilitated discussions and group work Role plays, reflection activities, and real-life scenarios Peer learning and action planning Optional pre-work or post-session surveys Course Materials Provided Participant workbook Psychological safety assessment toolkit Conversation starter guide Leadership checklist for building safety Personal and team action plan Optional Add-ons Team psychological safety assessments (anonymous survey) Post-course coaching or leadership debrief Co-delivery with DEI (Diversity, Equity & Inclusion) workshops Integration with feedback or team development programs

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

Expand your Power BI knowledge and take your reports to the next level. Course overview Duration: 1 day (6.5 hours) This course is aimed at existing users who want to expand their skills to use advanced reporting techniques and use DAX to create calculated columns and measures. Participants should have either attended our Power BI – Introduction course or have equivalent knowledge. You should be able to import and transform data and create simple reports. Objectives  By the end of the course you will be able to: Import and connect data tables Create and use date calendars Create calculated columns Create and use measures Use drill down and drill through Create Tooltip pages Add and customise slicers Add action buttons Streamline your report for use in the Power BI Service Content Review of importing and loading data Importing data Transforming data Adding custom columns Creating data models Building visuals Creating date calendars Building date tables Creating Financial Year information Including Month and Day information Creating calculated columns Power Query custom columns vs DAX columns Creating DAX calculated columns Creating measures Implicit vs Explicit Measures Building measures Using DAX Common DAX functions Drill Down vs Drill Through Review of drill down Creating drill through pages Using drill through Creating ToolTips Pages Adding pages to use for Tooltips Linking ToolTip pages to visuals Using action buttons Adding images Adding buttons Setting actions Working with slicers Adding slicers Changing slicer settings Syncing slicers between pages Showing what has been sliced Setting slicer interactions Techniques in the Power BI Service Hiding the navigation bar Stopping users manually filtering