Why Government Leaders Must Embrace Agile Agile is a pathway to innovation in many Government agencies. It is a response to challenges in Information Technology where traditional software development processes often did not yield expected results. This resulted in many projects exceeding budgets and timelines, and ignoring needed requirement changes. At its core, Agile is about priorities, placing individuals and interactions above processes and tools; working products above comprehensive documentation; customer collaboration above contract negotiation; and responding to change above following a plan. Leaders can embrace this approach to improve processing times, and coordination among development teams and users. This presentation provides practical steps on how leaders can better understand and support the innovation practices introduced by Agile. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.
Why Government Leaders Must Embrace Agile Agile is a pathway to innovation in many Government agencies. It is a response to challenges in Information Technology where traditional software development processes often did not yield expected results. This resulted in many projects exceeding budgets and timelines, and ignoring needed requirement changes. At its core, Agile is about priorities, placing individuals and interactions above processes and tools; working products above comprehensive documentation; customer collaboration above contract negotiation; and responding to change above following a plan. Leaders can embrace this approach to improve processing times, and coordination among development teams and users. This presentation provides practical steps on how leaders can better understand and support the innovation practices introduced by Agile. This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.
Employment Law & Agile HR Management Diploma Gain a competitive edge in the HR landscape with our Employment Law & Agile HR Management Diploma. Acquire mastery over Employment Law & Agile HR Management protocols to lead your organisation to success. Transform your career with this must-have diploma in Employment Law & Agile HR Management. Learning Outcomes: Analyse core principles of Employment Law & Agile HR Management. Apply Employment Law in constructing employment contracts. Evaluate rights and responsibilities during employment using Employment Law. Utilise Agile HR Management Methodology as per UK Employment Law in talent development. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Key Modules from Employment Law & Agile HR Management Diploma: Legal Recruitment Process: Implement lawful hiring procedures as per UK Employment Law. Employment Contract: Draft and review employment contracts, strictly adhering to Employment Law guidelines. Rights During Employment: Navigate and uphold employee rights, employing the pillars of Employment Law. Talent Management: Maximise talent potential through Agile HR Management, while remaining compliant with Employment Law. Agile HR Techniques: Implement cutting-edge Agile HR Management strategies.
Level 1 Diploma in Behaviour Management and Business Etiquette Introduce yourself to Business Ethics & Etiquette in the Level 1 Diploma in Business Behaviour Management. Explore the nuances of Global Business Etiquette, vital for effective Business Behaviour Management. Learning Outcomes: Summarise Business Ethics in Business Behaviour Management. Explain Business Etiquette in Business Behaviour Management. Assess Business Behaviour Management environment. Implement Business Behaviour Management in billing. Adapt Business Behaviour Management in global etiquette. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Level 1 Diploma in Behaviour Management and Business Etiquette Course Syllabus Business Behaviour Management Fundamentals: Acquire a foundational understanding of Business Behaviour Management, emphasising the principles of business ethics and workplace conduct. Master Business Behaviour Management Skills: Learn vital Business Behaviour Management techniques, focusing on communication etiquette and professional attire. Navigate Business Behaviour Management Environment: Gain insights into the dynamic Business Behaviour Management milieu, including organisational culture and workplace norms. Business Behaviour Management in Billing: Grasp key financial practices within Business Behaviour Management, from invoicing to ethical billing procedures. Dining Etiquette in Business Behaviour Management: Master dining etiquette through the lens of Business Behaviour Management, covering table manners and professional dining conduct. Global Business Behaviour Management: Expand your Business Behaviour Management expertise to a global scale, exploring cross-cultural communication and international business etiquette.
Embark on a journey to master the multifaceted world of business with our comprehensive Business Studies course. From financial acumen to strategic analysis, and from human resources to contract law, equip yourself with the skills necessary to navigate and lead in the dynamic business landscape.
Duration 2 Days 12 CPD hours This course is intended for Executives, Project Managers, Business Analysts, Business and IT stakeholders engaged in improving the delivery of products and services that meet user needs through the use of Microsoft SharePoint; Anyone who wants to improve their Business Analysis skills; Project stakeholders concerned with SharePoint requirements. Overview Plan, manage and close requirements for a project in reduced time using good business analysis practices Minimize project uncertainty and risk by applying good techniques Ensure your project delivers required functionality and adds value to the business Create an environment of self-management for your team that will be able to continuously align the delivered product or services with desired business needs, easily adapting to changing requirements throughout the process. Requirements can change frequently during a SharePoint project, and therefore projects need a streamlined, flexible approach to requirements change management. SharePoint professionals want to develop systems and services which are both high-quality and high-value, and the easiest way to achieve this is to implement the highest priority requirements first. This enables the projects to maximize value for their stakeholders. Introduction ? Roles involved in a SharePoint project The opportunities and challenges of a SharePoint project The business analysis process BA role vs. project manager role BA / PM competencies Case Study Exercise Understanding SharePoint Requirements Business, User, Functional, Quality-of-service and implementation requirements Requirements vs. specifications Requirements vs. business rules Risk management and risk response strategies Analyzing requirements Characteristics of effective requirements Case Study Exercise SharePoint Requirements Modeling Identify high level scope Identify initial requirements stack Identify an architectural vision Plan your iteration Iteration modeling Model storming Test driven development Case Study Exercise The Change Management Process Managing the Solution Scope and Requirements Capturing the Requirements Traceability Maintaining the Requirements for re-use Managing Requirements Conflicts Preparing the Requirements Package Building the Requirements communications plan Case Study Exercise Assessing & Validating Requirements Validating and verifying SharePoint Requirements Creating a master test plan Create test scenarios and test cases Case Study Exercise Additional Information Useful books and links on managing requirements and projects for SharePoint initiatives
Overview With the ever-increasing demand for Data Analysis Level 3 Diploma in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Data Analysis Level 3 Diploma may be. Learning about Data Analysis Level 3 Diploma or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Data Analysis Level 3 Diploma . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Data Analysis Level 3 Diploma is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Data Analysis Level 3 Diploma course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Data Analysis Level 3 Diploma course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Data Analysis Level 3 Diploma course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Data Analysis Level 3 Diploma , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Data Analysis Level 3 Diploma , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Data Analysis Level 3 Diploma , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Data Analysis Level 3 Diploma course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams. Course Curriculum Module 1 Introduction to Data Analysis. Introduction to Data Analysis. 00:00 Module 2 Mathematics and Statistics. Mathematics and Statistics. 00:00 Module 3 Data Manipulation. Data Manipulation. 00:00 Module 4 Data Visualisation. Data Visualisation. 00:00 Module 5 Data Wrangling. Data Wrangling. 00:00 Module 6 Data Exploration. Data Exploration. 00:00 Module 7 Machine Learning Fundamentals. Machine Learning Fundamentals. 00:00 Module 8 Machine Learning Algorithms. Machine Learning Algorithms. 00:00 Module 9 Data Analysis with Python and Libraries. Data Analysis with Python and Libraries. 00:00 Module 10 Data Analysis with R and Libraries. Data Analysis with R and Libraries. 00:00
Overview With the ever-increasing demand for Data Analysis in Microsoft Excel in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Data Analysis in Microsoft Excel may be. Learning about Data Analysis in Microsoft Excel or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Data Analysis in Microsoft Excel . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Data Analysis in Microsoft Excel is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Data Analysis in Microsoft Excel course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Data Analysis in Microsoft Excel course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Data Analysis in Microsoft Excel course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Data Analysis in Microsoft Excel , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Data Analysis in Microsoft Excel , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Data Analysis in Microsoft Excel , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Data Analysis in Microsoft Excel course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams. Course Curriculum Module 1_ Introduction to Microsoft Excel Introduction to Microsoft Excel 00:00 Module 2_ Data Visualization and Advanced Functions Data Visualization and Advanced Functions 00:00 Module 3_ PivotTables and Regression PivotTables and Regression 00:00 Module 4_ Time Series Analysis in Excel Time Series Analysis in Excel 00:00
Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice