57505 Courses

Learn how to use this innovative tool to analyse and validate your schedule, to add and model uncertainty and risk and to work with updated plans to compare project progress. Course overview Duration: 1 day (6.5 hours) This course looks at the powerful features of Nodes and Links. It looks at analysing and validating your schedule, adding uncertainty and risk and working with updated plans to compare project progress. Hands on practice will be gained throughout the course to ensure you can confidentially put your new skills into practice back in the workplace. This course is designed for new users of Nodes and links, no previous experience is required. You should however be familiar with risk management processes and terminology. Objectives  By the end of the course you will be able to: Import and validate plans Analyse and review plans Add and model uncertainty Add and model risk Load updated schedules Re run analysis on updated schedules Content Validating your plan Importing a baseline plan Running a health check Analysing the results Reviewing the plan Analysing critical paths Reviewing activities Reviewing resources Adding Uncertainty Setting uncertainty templates Distributions Adding uncertainty Using Inherit Using AI Reviewing activity distributions Modelling Uncertainty Running the Analysis Reviewing the results Reviewing activity results Risk Drivers Filtering for activities Setting up the Risk Register Setting Risk Templates Adding Risks to the Risk Register Independent vs Dependant Events Setting Probability and Impact Modelling Uncertainty and Risk Mapping risks to activities Running the Analysis Reviewing the results Updated Plans Importing a new plan version Comparing plans Tracking progress Trend analysis Analysing Updated Plans Using updated plans Synchronising uncertainly and risk Rerunning analysis

Unlock the Power of Teams: Elevate your leadership with our Building and Leading Effective Teams course. Learn the art of collaboration, communication, and synergy to create high-performing teams that drive success Course overview Duration: 1 day (6 hours) Everyone works in teams today in one way or another. Whatever we do in the workplace we need to interact with another person or a number of people at various times. It is important that we know how to communicate, how to listen, how to work together and how to overcome conflict when it arises in our workplace. Challenges are often created by a lack of trust, poor conflict handling skills, a lack of shared vision and confusion over roles and responsibilities. This course will help delegates understand how to encourage more productive team working in the workplace. By the end of the course delegates will be able to describe what makes a High Performing Team and realistically assess their current strengths and weaknesses. Delegates will also be able to identify and plan behavioural changes that will improve the team’s performance. The course is experiential based with lots of learning by doing activities, reflecting and discussion. This will allow team members to get to know/improve their knowledge of team colleagues and energise or re-energise teams. Objectives  Know more about their colleagues Be able to describe what makes a high performing team Understand the importance of playing to different strengths and skills Recognise the need for clear and effective communication Content The Importance of Team Work The importance of teamwork The ‘third dimension’ – how working together has the potential to achieve more The dangers of an overly competitive workplace culture Psychological Safety Team Development Models Stages of Team Development Behaviours at each stage Dysfunctional Teams – what does good and bad look like Characteristics of high performing and elite teams Teaming and Leadership Skills Teaming competencies Active Listening Proactive Language Values and Beliefs Building Mental Fitness of Teams Becoming an inspirational leader Establishing a climate of psychological safety Team Challenges The importance of Accountability The Team Charter Smart Teams:Building TrustBuilding CollaborationOvercoming ConflictGaining CommitmentDeveloping Shared Goals The importance of shared goals Effective Team communication

Overview of Telehandler Training Course Telehandler Training or Telehandler Courses is an essential program designed to equip operators with the necessary skills and knowledge to safely and efficiently operate telehandlers. These versatile machines, commonly used in agriculture, construction, and warehousing, require precise handling due to their complex controls and varied load capacities. Our Telehandler Courses will help you achieve your goal to be a successful Telehandler Operator. The importance of comprehensive telehandler training cannot be overstated. It ensures that operators are well-versed in both the theoretical and practical aspects of handling these machines, significantly reducing the risk of accidents and injuries on the job. Moreover, proper Telehandler training aids in maximising the operational efficiency of telehandlers, which can contribute to the timely completion of projects and the effective management of resources. In various industries, telehandlers play a critical role in lifting and transporting heavy materials over obstacles and uneven terrain, making the Telehandler course crucial for anyone involved in operations that require heavy lifting and material handling. The Telehandler courses covers a range of topics, including safety regulations, operational techniques, maintenance basics, and troubleshooting common issues, ensuring that all participants are prepared to handle the demands of operating a telehandler in any setting. Booking the Telehandler Training couldn’t be easier. Book Now

Duration 3 Days 18 CPD hours

Look at the in depth features of charts and some specialist tools to make your charts come to life. Course overview Duration: 1 day (6.5 hours) Our Excel Charting Specialist course examines how to unlock the full potential of Charts in Excel. It investigates the useful tools needed for creating bespoke Charts, allowing you to creatively present data more visually. By the end of the course, you will have an awareness of the tools used for creating more advanced Charts and will be able to create your own Dynamic Charts. The course is designed for existing users of Excel who are looking at more advanced ways to visualise data in Excel using Charts. Objectives By the end of the course you will be able to: Create and Amend Charts Format multiple areas of a Chart Use a Combo Chart Apply Conditional Formatting to a Chart Create Dynamic Charts Work with Custom Formatting Create an Advanced Dynamic Chart Content Creating and amending charts Creating Simple Charts Using the Chart Design tab Adding Chart Elements Changing the type of Chart Formatting charts Format Chart Area Format Data Series Format Data Point Format Axis Working with combo charts Adding additional data to a Chart Customising Chart types Creating Clustered Column/line Charts Applying conditional formatting on charts Using IF Statements Highlighting Max/Min Data points in Charts Using Series Overlap Dynamic charts Creating dynamic Target vs Actual Charts Introducing the NA function Hiding data used for Charts Custom formatting charts Formatting Data Labels Customising number formats Using Trend Arrows to show changes Editing Format Code Advanced dynamic charts Pivot Chart rules Creating a Pivot Chart Working with your Pivot Chart Creating calculations Combining all elements to create an Advanced Chart Using Error Bars to create a line Adding a scroll bar and linking with data

Coming soon! Embark on a dynamic journey towards administrative mastery with our Level 3 Business Administrator course. Tailored for individuals stepping into the vibrant world of business administration, be it through recent recruitment or a well-deserved promotion, this program is crafted to instil a distinctive set of skills and insights essential for success in the administrative landscape.

Introduction to Diabetes (2-Day Course) - Norfolk ICB OnlyThis course is for those from the Norfolk ICB only using the unique booking code. Applicants not using this code nor Identifying themselves as Norfolk ICB employees will not be able to attend.Course Description:These two days of comprehensive training are designed for nurses, nurse associates, pharmacists, paramedics, and other Allied Healthcare Professionals (AHPs), and experienced healthcare assistants (HCAs) who are new to or fairly new to the field of diabetes care. If you've recently started seeing patients with diabetes, or are planning to; this course is tailored to provide you with the fundamental knowledge and skills required to confidently care for individuals with diabetes. The primary focus is on adults with Type 2 diabetes, although key recommendations and signposting for patients with Type 1 diabetes will also be covered.Diabetes presents a significant healthcare challenge, costing the NHS £10 billion each year and impacting patients and their families. Primary care professionals play a pivotal role in managing the ever-increasing numbers of people diagnosed with Type 2 diabetes. Good diabetes care is crucial and aligns with national and local policies supported by robust NICE guidance.These interactive days of learning will incorporate various methods, including case studies, to help you progress from basic knowledge to a more confident and positive approach in reviewing and managing patients with diabetes. 2 Day Introduction to diabetes management in primary care (This is intended to provide an overview the programme may change slightly) DAY ONE 09.15 Coffee and registration 09.30 Introduction and course objectives 09.45 Setting the scene - screening, diagnosis, prediabetes, patho-physiology and symptoms, remission in Type 2 diabetes 10.45 Coffee 11.00 Type 1 Vs Type 2 Diabetes 11.20 Metabolic Syndrome and Diagnostic Criteria 11.45 Diabetes Prevention Programme 12.15 Managing Diabetes in Primary Care and Supporting Lifestyle 12.30 Lunch 13.30 Pharmacological Management of Type 2 Diabetes 14.30 Methods for Monitoring Glucose 14.45 Diabetic Emergencies (hypos, HHS and DKA) 15.15 Sick Day Rules 15.30 Action plan, evaluation, and resources 15.45 Close DAY TWO 09.15 Coffee and registration 09.30 Review progress since Day 1 09.45 Macrovascular Complications 10.15 Modifiable Risk Factors leading to CVD 11.00 Coffee 11.20 Cholesterol & Hypertension Management 12.00 Microvascular Complications 12.30 Lunch 13.30 Diabetes and Emotional Wellbeing 14.30 Case Studies 15.30 Q&A, Evaluations 15.45 CloseKey Learning Outcomes for Both Days:Upon completing this course, participants will be able to:1. Explain the physiology of diabetes and differentiate between Type 1 and Type 2 diabetes.2. Discuss methods for diagnosing diabetes and provide information to individuals newly diagnosed with Type 2 diabetes.3. Describe approaches that support achieving remission in Type 2 diabetes.4. Explain basic advice related to a healthy diet, various dietary approaches, and carbohydrate awareness.5. Discuss the modes of action of commonly used non-insulin medications.6. Identify major complications that may arise in individuals with long-standing diabetes and measures to limit or prevent them.7. Describe key advice for patients regarding the recognition and appropriate treatment of hypoglycaemia.8. Discuss DVLA guidance concerning driving and diabetes.9. Explain the risks of acute hyperglycaemia and provide advice to patients on self-managing illness periods.10. Provide examples of referral pathways to other services such as weight management, secondary care, podiatry, structured education, activity, and psychological services.11. Describe the process of routine foot review and factors influencing diabetic foot risk status.12. Discuss local recommendations for the appropriate use of blood glucose and ketone monitoring.13. Explain the key components and processes of an annual diabetes review and a self-management plan.Join us for this comprehensive 2-day course via Zoom and enhance your ability to provide effective diabetes care within primary care settings.

For any business working with high voltage vehicle batteries and systems – bespoke training designed and delivered to meet the exact requirements of the customer, in your location. Enquire using the forms below for a phone consultation.

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Coming soon! Embark on a transformative odyssey into operational leadership with our Level 5 Operations Department Manager course. Meticulously designed for individuals venturing into the role of an Operations Department Manager, whether through recent recruitment or a well-deserved promotion, this program is a gateway to acquiring advanced skills and unique insights crucial for success in the realm of operations.