4230 Analyst courses in Lutterworth delivered Online

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

Duration 3 Days 18 CPD hours This course is intended for This course is designed for project managers, Scrum masters, business analysts, and team leaders looking to effectively manage their development projects using Team Foundation Server 2017. Overview The course also demonstrates how TFS facilitates the use of storyboards to prototype experiences, request stakeholder feedback, foster team collaboration, and generate reports. The final two modules of the course provide an overview of how testers and developers can work effectively using appropriate tools in the Visual Studio family. In this course, attendees will plan a new software development project and go through the steps to initiate the project using Visual Studio 2017. This includes recording requirements, creating a product backlog, and estimating effort for backlog items. Introducing the Microsoft Visual Studio 2017 Family What?s new in Visual Studio 2017 Overview of the Visual Studio 2017 family Overview of product features Project workflow across the Visual Studio 2017 suite of products Initiating a New Project Organizing projects in TFS Understanding process templates Creating a new team project Setting team project properties Switching between team projects Work Item Primer Overview of work items Traceability between work items Searching and creating custom queries Work item charting and pinning charts Work item tagging Configuring project notifications Creating our Product Backlog Examining requirement types Creating backlog items Creating requirement hierarchies using features The importance of acceptance criteria Agile Estimation Introduction to estimation Using story points Planning Poker and other popular estimation techniques Adding your estimates to TFS work items Working from the Product Backlog Introducing the Kanban board Entering and editing details on the Kanban board Customizing columns, including using split columns and limiting WIP Recording our Definition of Done (DoD) Understanding the Cumulative Flow Diagram Working in Sprints Specifying your sprint schedule and your team capacity Selecting items for the sprint backlog using forecasting Decomposing requirements into tasks Using burndown charts to track progress Monitoring work using the task board Working with unparented work items Retrospectives The importance of retrospectives Conducting an efficient sprint retrospective What you should avoid in your retrospective Working with TFS Teams Configuring teams in our team project Managing work from a master backlog Allocating work to our teams Configuring iterations for TFS teams Enhancing Requirements Using Storyboards Overview of storyboarding capabilities Creating a storyboard to illustrate a requirement Linking a storyboard to a work item Getting Stakeholder Feedback Introducing the Microsoft Feedback Client Using the Microsoft Feedback Client to provide rich feedback to the team Adding continuous feedback into your workflow Fostering Team Collaboration An overview of the various clients The use of email in sharing information Choosing the appropriate client tool Creating and Customizing Reports Overview of reporting architecture Reviewing the out of the box reports Adding new reports Creating ad hoc reports using Excel Overview of Agile Testing The role of the tester in a sprint planning meeting A lap around web-based test management Creating a test plan Creating manual test cases from requirements Overview of Agile Development Using My Work to select tasks from the sprint backlog Understanding the value of linking changesets to work items The importance of unit testing Creating a continuous integration build Additional course details: Nexus Humans Managing Agile Projects Using TFS 2017 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 Managing Agile Projects Using TFS 2017 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 1 Days 6 CPD hours This course is intended for This course is intended for solution architects, developers, business analysts, system administrators, or anyone who works as a solution builder within their company. Overview Build and deploy a solution Create properties and document classes Create roles and in-baskets Create a case type and tasks Create a workflow Use preconditions and sets Automate case packaging Add case stages Apply solution design principles In this course you will create basic case management solutions with IBM Case Manager Builder and Process Designer. Using an iterative solution development process, you will create, deploy, test, and revise your solutions, adding complexity and functionality to your solutions as you gain skills. You will create properties and document classes, configure roles and in-baskets, and define case stages. You will work with case types, tasks, and workflows. This course includes some guidelines on solution design principles. After completing this course, you can build on these skills by taking more advanced or specialized courses in security, user-interface customization, and solution deployment. Build and Deploy a Solution Build a solution Deploy a solution Test a solution Manage roles Redeploy a solution Create Properties and Document Classes Create case properties Create task properties Create a business object Create document classes Create Roles and In-Baskets Create roles Create in-baskets Create Tasks Create a to-do task Create a container task Add the to-do list widget to the Case Details pag Create a Step Map Open a task in Step Designer Create a step map Add a workgroup to a step map Add an attachment to a step map Use Preconditions and Sets Organize tasks with preconditions Organize tasks with inclusive sets Organize tasks with exclusive sets Automate Case Packaging Open a task in Process Designer Add a component step to a task Use a component step to package a case Add Case Stages Add case stages to a solution Use a system step to perform a case stage operation Use a case stage as a task precondition Solution Design Principles Describe solution design principles

Duration 2 Days 12 CPD hours This course is intended for This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it's often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. Additional course details: Nexus Humans Python for Data Science Primer: Hands-on Technical Overview (TTPS4872) 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 Python for Data Science Primer: Hands-on Technical Overview (TTPS4872) 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 This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. An Overview of Python Why Python? Python in the Shell Python in Web Notebooks (iPython, Jupyter, Zeppelin) Demo: Python, Notebooks, and Data Science Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences, Arrays, Dictionaries and Sets About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with Dictionaries Working with Sets Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Functions Defining functions Parameters Global and local scope Nested functions Returning values Essential Demos Sorting Exceptions Importing Modules Classes Regular Expressions The standard library Math functions The string module Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Python and Data Science Data Science Essentials Pandas Overview NumPy Overview SciKit Overview MatPlotLib Overview Working with Python in Data Science Additional course details: Nexus Humans Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Application Developers Business Analysts Developer End Users Functional Implementer Java Developer System Analysts Technical Administrator Overview Create administrator-level personalizations Personalize configurable pages Utilize advanced personalization features Implement flexfields on OA Framework-based pages Create custom look and feel definitions Create user-level personalizations This course will be applicable for customers who have implemented Oracle E-Business Suite Release 12 or Oracle E-Business Suite 12.1. This course will be applicable for customers who have implemented Oracle E-Business Suite Release 12 or Oracle E-Business Suite 12.1.

Duration 2 Days 12 CPD hours This course is intended for Project Managers, Business Analysts, Business and IT stakeholders working with analysts Overview Provide a solid foundation for applying business process modeling principles and best practices with BPMN Demonstrate how to solve practical business problems using BPMN Business Process Diagrams (BPDs) Students will learn to map business processes easily and efficiently using the industry standard - BPMN which stands for Business Process Modeling Notation from the Object Management Group (OMG). Students will learn the best practices in process mapping using the latest industry standards (BPMN) so that both the business and IT stakeholders will be able to understand the models and map processes consistently through-out their organization. Introduction What is Business Process Modeling? What is Business Process Modeling Notation (BPMN)? Benefits of BPMN An Overview of Governance An overview of governance Key governance questions to ask What happens if you don?t have effective governance? Mapping the Business Problem Define a strategic outcomes map Define a Business model and relevant processes Modeling Simple BPMN Structures When do you use BPMN? What are simple BPMN structures? AS-IS vs. TO-BE modeling Modeling Complex BPMN Structures What are complex BPMN structures When to use complex BPMN structures Analyzing Process Models Identifying poor process models Creating process models that everyone can understand Identify criteria for a well-defined process Process Mapping vs. Process Modeling Determine when to create a process map Determine when to create a process model Asking the four ?Ares? Additional Resources Learning about BPMN 2.0 More useful BPMN links BPMN 2.0 free editors

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.