54 Data Structure courses delivered Live Online

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Software development training course description This three-day MTA Training course helps you prepare for Microsoft Technology Associate Exam 98-361, and build an understanding of these topics: Core programming, Object-Oriented programming, general software development, web applications, desktop applications, and databases. This course leverages the same content as found in the Microsoft Official Academic Course (MOAC) for this exam. What will you learn Describe core programming. Explain Object Oriented programming. Describe general software development. Describe Web applications. Describe desktop applications. Explain how databases work. Software development training course details Who will benefit: Anyone looking to learn the fundamentals of software. Prerequisites: None. Duration 3 days Software development training course contents Core programming Computer storage and data types How a computer stores programs and the instructions in computer memory, memory stacks and heaps, memory size requirements for the various data storage types, numeric data and textual data. Computer decision structures Various decision structures used in all computer programming languages; If decision structures; multiple decision structures, such as If…Else and switch/Select Case; reading flowcharts; decision tables; evaluating expressions. Handling repetition For loops, While loops, Do...While loops and recursion. Understand error handling Structured exception handling. Object-oriented programming Classes Properties, methods, events and constructors; how to create a class; how to use classes in code. Inheritance Inheriting the functionality of a base class into a derived class. Polymorphism Extending the functionality in a class after inheriting from a base class, overriding methods in the derived class. Encapsulation Creating classes that hide their implementation details while still allowing access to the required functionality through the interface, access modifiers. General software development Application life cycle management Phases of application life cycle management, software testing. Interpret application specifications Application specifications, translating them into prototypes, code, select appropriate application type and components. Algorithms and data structures Arrays, stacks, queues, linked lists and sorting algorithms; performance implications of various data structures; choosing the right data structure. Web applications Web page development HTML, CSS, JavaScript. ASP.NET web application development Page life cycle, event model, state management, client-side versus server-side programming. Web hosting Creating virtual directories and websites, deploying web applications, understanding the role of Internet Information Services. Web services Web services that will be consumed by client applications, accessing web services from a client application, SOAP, WSDL. Desktop applications Windows apps UI design guideline categories, characteristics and capabilities of Store Apps, identify gestures. Console-based applications Characteristics and capabilities of console- based applications. Windows Services Characteristics and capabilities of Windows Services. Databases Relational database management systems Characteristics and capabilities of database products, database design, ERDs, normalisation concepts. Database query methods SQL, creating and accessing stored procedures, updating and selecting data. Database connection methods Connecting to various types of data stores, such as flat file; XML file; in-memory object; resource optimisation.

Duration 1 Days 6 CPD hours This course is intended for This basic course is for: Business Analyst Systems Engineer Software Engineer Requirements Engineer Requirements Manager Requirements Team Leader Overview Build projects in DOORS, including defining data structure, linking schema, attributes, and access permissions Use DOORS external linking facilities Share DOORS information with 3rd parties Control the flow of changes through your DOORS database Apply configuration management and backup strategies to your DOORS data This course builds on the content learned in the IBM Engineering Requirements Management DOORS V9.6 Foundation course. It is designed for those who will be in the role of team lead or project manager, or who want to learn more about advanced DOORS end-user functionality. It discusses creating and structuring DOORS projects, defining linking relationships and attributes, setting access permissions, and managing change. It also discusses external linking, working with spreadsheets, and applying configuration management strategies to DOORS data. Course Outline Build projects in DOORS, including defining data structure, linking schema, attributes, and access permissions Use DOORS external linking facilities Share DOORS information with 3rd parties Control the flow of changes through your DOORS database Apply configuration management and backup strategies to your DOORS data

About this Virtual Instructor Led Training (VILT) The energy industry has started its journey to be more data centric by embracing the industry 4.0 concept. As a result, data management - which was considered until recently as a back-office service to support geoscience, reservoir management, engineering, production and maintenance - is now given the spotlight! To become an active stakeholder in this important transition in E&P data management, it is necessary to understand the new technical opportunities offered by the Cloud, Artificial Intelligence and how data governance can pave the way towards more reliable and resilient processes within E&P domain. Several key questions that need to be addressed: Why place more focus on data assets? Is data management just about serving geoscientists or engineers with fresh data? What is the value of data management in the E&P sector for decision making? How to convince the data consumers that the data we provide is reliable? Is the data architecture of my organization appropriate and sustainable? The purpose of this 5 half-day Virtual Instructor Led Training (VILT) course is to present the data challenges facing the energy organizations today and see how they practically solve them. The backbone of this course is based on the DAMA Book of Knowledge for Data Management. The main data management activities are described in sequence with a particular focus on recent technological developments. Training Objectives Upon completion of this VILT course, the participants will be able to: Understand why the data asset is now considered as a main asset by energy organizations Appreciate the importance of data governance and become an active stakeholder of it Understand the architecture and implementation of data structure in their professional environment Get familiarized with the more important data management activities such as data security and data quality Integrate their subsurface and surface engineering skills with the data managements concepts This VILT course is unique on several points: All notions are explained by some short presentations. For each of them, a set of video, exercises, quizzes will be provided to help develop an engaging experience between the trainer and the participants A pre-course questionnaire to help the trainer focus on the participants' needs and learning objectives A detailed reference manual A lexicon of terms for data-management Limited class size to encourage the interactivity Target Audience This VILT course is intended for: Junior/new data managers Geoscientists Reservoir engineers Producers Maintenance specialists Construction specialists Human resources Legal Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-days consisting 4 hours per day, with 2 breaks of 10 minutes per day. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your expert course leader is a geologist by education who has dedicated his career to subsurface data management services. In 2016, he initiated a tech startup dedicated to Data Management using Artificial Intelligence (AI) tools. He is heavily involved in developing business plans, pricing strategies, partnerships, marketing and SEO, and is the co-author of several Machine Learning publications. He also delivers training on Data Management and Data Science to students and professionals. Based in France, he was formerly Vice President, Sales & Marketing at CGG where he was in charge of the Data Management Services strategy, Sales Manager at Spie O&G Services where he initiated the Geoscience technical assistance activities and Product Manager of interactive seismic inversion software design and marketing at Paradigm.       POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

Duration 3 Days 18 CPD hours This course is intended for The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises. This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Prerequisites Understanding core data concepts. Knowledge of working with relational data in the cloud. Knowledge of working with non-relational data in the cloud. Knowledge of data analysis and visualization concepts. DP-900T00 Microsoft Azure Data Fundamentals is recommended 1 - Discover data analysis Overview of data analysis Roles in data Tasks of a data analyst 2 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 3 - Get data in Power BI Get data from files Get data from relational data sources Create dynamic reports with parameters Get data from a NoSQL database Get data from online services Select a storage mode Get data from Azure Analysis Services Fix performance issues Resolve data import errors 4 - Clean, transform, and load data in Power BI Shape the initial data Simplify the data structure Evaluate and change column data types Combine multiple tables into a single table Profile data in Power BI Use Advanced Editor to modify M code 5 - Design a semantic model in Power BI Work with tables Create a date table Work with dimensions Define data granularity Work with relationships and cardinality Resolve modeling challenges 6 - Add measures to Power BI Desktop models Create simple measures Create compound measures Create quick measures Compare calculated columns with measures 7 - Add calculated tables and columns to Power BI Desktop models Create calculated columns Learn about row context Choose a technique to add a column 8 - Use DAX time intelligence functions in Power BI Desktop models Use DAX time intelligence functions Additional time intelligence calculations 9 - Optimize a model for performance in Power BI Review performance of measures, relationships, and visuals Use variables to improve performance and troubleshooting Reduce cardinality Optimize DirectQuery models with table level storage Create and manage aggregations 10 - Design Power BI reports Design the analytical report layout Design visually appealing reports Report objects Select report visuals Select report visuals to suit the report layout Format and configure visualizations Work with key performance indicators 11 - Configure Power BI report filters Apply filters to the report structure Apply filters with slicers Design reports with advanced filtering techniques Consumption-time filtering Select report filter techniques Case study - Configure report filters based on feedback 12 - Enhance Power BI report designs for the user experience Design reports to show details Design reports to highlight values Design reports that behave like apps Work with bookmarks Design reports for navigation Work with visual headers Design reports with built-in assistance Tune report performance Optimize reports for mobile use 13 - Perform analytics in Power BI Explore statistical summary Identify outliers with Power BI visuals Group and bin data for analysis Apply clustering techniques Conduct time series analysis Use the Analyze feature Create what-if parameters Use specialized visuals 14 - Create and manage workspaces in Power BI Distribute a report or dashboard Monitor usage and performance Recommend a development life cycle strategy Troubleshoot data by viewing its lineage Configure data protection 15 - Manage semantic models in Power BI Use a Power BI gateway to connect to on-premises data sources Configure a semantic model scheduled refresh Configure incremental refresh settings Manage and promote semantic models Troubleshoot service connectivity Boost performance with query caching (Premium) 16 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 17 - Implement row-level security Configure row-level security with the static method Configure row-level security with the dynamic method Additional course details: Nexus Humans PL-300T00: Microsoft Power BI Data Analyst 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 PL-300T00: Microsoft Power BI Data Analyst 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 Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context. Overview By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently. In this course you will start with the absolute basics of Python, focusing mainly on data structures. Then you will delve into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python.This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets. Introduction to Data Structure using Python Python for Data Wrangling Lists, Sets, Strings, Tuples, and Dictionaries Advanced Operations on Built-In Data Structure Advanced Data Structures Basic File Operations in Python Introduction to NumPy, Pandas, and Matplotlib NumPy Arrays Pandas DataFrames Statistics and Visualization with NumPy and Pandas Using NumPy and Pandas to Calculate Basic Descriptive Statistics on the DataFrame Deep Dive into Data Wrangling with Python Subsetting, Filtering, and Grouping Detecting Outliers and Handling Missing Values Concatenating, Merging, and Joining Useful Methods of Pandas Get Comfortable with a Different Kind of Data Sources Reading Data from Different Text-Based (and Non-Text-Based) Sources Introduction to BeautifulSoup4 and Web Page Parsing Learning the Hidden Secrets of Data Wrangling Advanced List Comprehension and the zip Function Data Formatting Advanced Web Scraping and Data Gathering Basics of Web Scraping and BeautifulSoup libraries Reading Data from XML RDBMS and SQL Refresher of RDBMS and SQL Using an RDBMS (MySQL/PostgreSQL/SQLite) Application in real life and Conclusion of course Applying Your Knowledge to a Real-life Data Wrangling Task An Extension to Data Wrangling

OVERVIEW Prerequisites—DIAD training or equivalent working experience This one-day course will cover Power BI report layouts and structure the agile process to creating Power BI data visualizations. It will help attendees to understand the art behind visualizations, the implications behind choosing the right charts, the impact of color, shape, and size, and finally the use of Power BI custom visuals. The course includes various design patterns of dashboards and reports, as well as best practices for authoring great reports and dashboards for business users. The course content is managed by the Power BI engineering team at Microsoft. There is no exam associated with the course. COURSE BENEFITS: Understand the need for storytelling with data Understand the agile process to creating Power BI data visualizations Understand the art behind visualizations Gain familiarity with Power BI report layouts and structure Understand implications behind choosing the right charts Gain familiarity with using Power BI custom visuals WHO IS THE COURSE FOR? Power BI report developers who wish to improve the aesthetic quality of their reports Power BI and other BI practitioners who would like to understand more about the theory of data visualization BI practitioners who wish to create reports that communicate the meaning behind the data more clearly Power BI users who would like to explore the types of chart and visual available that answer different types of business question COURSE OUTLINE Module 1 What Is Storytelling With Data? Volume, Velocity and Variety The importance of business questions What is a story in this context? Module 2 The Science Behind Data Visualization Basic problems to avoid Memory and visualization Ways to spark iconic, short-term and long-term memory Module 3 The Process Behind Data Visualization Using an agile approach to report development Data structure and data grain Converting the story to a data model Module 4 Dashboards And Reports Terminology and definitions Dashboard layout and structure Report layout and structure Storyboarding Drill-through, bookmarks, toggles and tooltips Module 5 Chart Selection Charts for comparison Time series Proportions Constructing effective tables, cards and slicers Scatterplots Module 6 Accessibility And Custom Visuals Report accessibility checklists Custom visuals Creating a custom R visual Charticulator Module 7 Publishing And Formatting Colour schemes Making a Power BI theme Use of fonts, icons and symbols Sizing dashboard and report tiles Sparklines, hyperlinks and images Module 8 Report Authoring - Best Practices Design thought process The audience Defining the platform environment The user experience Visualization Implementation and testing Optimization Module 9 Dashboard And Goals Design Tips and tricks Best practices for dashboard design Tracking business metrics with goals

OVERVIEW This official Microsoft Power BI training course will teach you how to connect to data from many sources, clean and transform it using Power Query, create a data model consisting of multiple tables connected with relationships and build visualisations and reports to show the patterns in the data. The course will explore formulas created using the DAX language, including the use of advanced date intelligence calculations. Additional visualisation features including interactivity between the elements of a report page are covered as well as parameters and row-level security, which allows a report to be tailored according to who is viewing it. The course will also show how to publish reports and dashboards to a workspace on the Power BI Service. COURSE BENEFITS: Learn how to clean, transform, and load data from many sources Use database queries in Power Query to combine tables using append and merge Create and manage a data model in Power BI consisting of multiple tables connected with relationships Build Measures and other calculations in the DAX language to plot in reports Manage advanced time calculations using date tables Optimise report calculations using the Performance Analyzer Manage and share report assets to the Power BI Service Prepare for the official Microsoft PL-300 exam using Microsoft Official Courseware WHO IS THE COURSE FOR? Data Analysts with little or no experience of Power BI who wish to upgrade their knowledge to include Business Intelligence Management Consultants who need to conduct rapid analysis of their clients’ data to answer specific business questions Analysts who need to upgrade their organisation from a simple Excel or SQL-based management reporting system to a dynamic BI system Data Analysts who wish to develop organisation-wide reporting in the form of web reports or phone apps Marketers in data-intensive organisations who wish to build visually appealing, dynamic charts for their stakeholders to use COURSE OUTLINE Module 1 Getting Started With Microsoft Data Analytics Data analytics and Microsoft Getting Started with Power BI Module 2 Get Data In Power BI Get data from various data sources Optimize performance Resolve data errors Lab: Prepare Data in Power BI Desktop Module 3 Clean, Transform And Load Data In Power BI Data shaping Data profiling Enhance the data structure Lab: Load Data in Power BI Desktop Module 4 Design A Data Model In Power BI Introduction to data modelling Working with Tables Dimensions and Hierarchies Lab: Model Data in Power BI Desktop Module 5 Create Model Calculations Using DAX In Power BI Introduction to DAX Real-time Dashboards Advanced DAX Lab 1: Create DAX Calculations in Power BI Desktop, Part 1 Lab 2: Create DAX Calculations in Power BI Desktop, Part 2 Module 6 Optimize Model Performance Optimize the data model for performance Optimize DirectQuery models Module 7 Create Reports Design a Report Enhance the Report Lab 1: Design a Report in Power BI Desktop, Part 1 Lab 2: Design a Report in Power BI Desktop, Part 2 Module 8 Create Dashboards Create a Dashboard Real-time Dashboards Enhance a Dashboard Lab: Create a Power BI Dashboard Module 9 Perform Advanced Analytics Advanced analytics Data Insights through AI Visuals Lab: Perform Data Analysis in Power BI Desktop Module 10 Create And Manage Workspaces Creating Workspaces Sharing and managing assets Module 11 Manage Datasets In Power BI Parameters Datasets Module 12 Row-Level Security Security in Power BI Lab: Enforce Row-Level Security

Duration 1 Days 6 CPD hours This course is intended for This class is designed for administrators preparing to take the Salesforce Marketing Cloud Administrator exam who are able to configure Marketing Cloud products using industry and product best practices. You should be generally familiar with data structure in subscriber data management. You should also be able to thoroughly navigate Setup, troubleshoot account configuration, and manage user requests. Overview When you complete this course, you will be able to: Recall exam objectives. Discuss product features and functionality covered on the exam. Assess your exam readiness by answering practice questions. Familiarize yourself with additional resources necessary to prepare for the exam. Take the next step in your career and become a Salesforce Certified Marketing Cloud Administrator. In this 1-day, expert-led certification prep class, boost your exam readiness with a detailed exam overview, exam resources, and practice exam questions to test your knowledge. This course includes a voucher to sit for the Salesforce Marketing Cloud Administrator exam. Course Outline Exam Overview Digital Marketing Proficiency Review Governance and Compliance in Relation to Digital Marketing Review Security Best Practices for Date, Permissions, and PII Review Marketing Cloud Product Inventory and Offerings Subscriber Data Management Review the Contact Model Review Data Quality Evaluation Review Preference and Profile Center Setup Review Business Units, Users, and Security Configuration Review Integrations Configuration Review Features in Setup Home Review Marketing Cloud Extension Products Channel Management Review Mobile Studio Configuration Review Email Studio Configuration Review Social Studio and Advertising Configuration Review Journey Builder Concepts and Use Cases Maintenance Review Data Extraction and Report Generation Solutions Review Monitoring and System Availability Review Additional Marketing Cloud Product Benefits Practice Exam and Wrap-up Complete a Practice Exam Review Next Steps