83 Data Analyst courses in Belfast delivered Live Online

Diploma in Data Analysis Fundamentals Course Overview The Diploma in Data Analysis Fundamentals provides a comprehensive introduction to the core principles and techniques used in data analysis. Throughout this course, learners will explore various data analysis tools and methods, such as Pareto charts, histograms, and control charts, to gain insights into processes and performance. By focusing on key data analysis skills, including identifying variation and interpreting results, this course empowers learners to use data-driven approaches to improve business processes. Upon completion, learners will have the ability to assess and present data effectively, enabling informed decision-making in a wide range of industries. Course Description This course covers essential topics in data analysis, including the principles of process management, tools for data analysis, and methods to interpret and present performance data. Learners will delve into key techniques such as Pareto charts, histograms, run charts, and control charts, focusing on how to use these tools to identify patterns, variations, and areas for improvement. The course also includes a structured approach to performance measurement and provides exercises to reinforce the theoretical knowledge gained. By the end of the course, learners will be equipped with the skills to analyse data, identify trends, and contribute to process improvement initiatives within their organisations. Diploma in Data Analysis Fundamentals Curriculum Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to improve decision-making through data insights. Beginners with an interest in process improvement and business analysis. Data enthusiasts looking to build a solid foundation in analysis techniques. Career Path Data Analyst Business Intelligence Analyst Process Improvement Specialist Operations Analyst Quality Control Analyst

Excel Data Analysis Course Overview The Excel Data Analysis course is designed to equip learners with the essential skills needed to analyse and interpret data using Microsoft Excel. This course covers a range of tools and techniques that are vital for processing, summarising, and visualising data. Learners will explore functions, pivot tables, charts, and data manipulation strategies that will enable them to work efficiently with data sets. By the end of the course, learners will be able to transform raw data into meaningful insights, making it an invaluable skill for professionals across various industries. Whether you're looking to improve your data skills or progress in your career, this course offers the foundational knowledge required for data analysis in Excel. Course Description This course delves into the core aspects of Excel Data Analysis, starting with basic functions and advancing to complex data manipulation techniques. Learners will explore how to create and manage pivot tables, perform data filtering, and apply functions such as VLOOKUP and INDEX MATCH. Visualisation tools like charts and graphs will be covered, enabling learners to present their findings in a clear and impactful way. Additionally, learners will be introduced to data modelling, conditional formatting, and advanced formula techniques that will enhance their data analysis capabilities. The course is structured to provide a comprehensive understanding of Excel’s data analysis features, building competency for a wide range of practical applications in both personal and professional settings. Excel Data Analysis Curriculum Module 01: Introduction to Excel for Data Analysis Module 02: Using Excel Functions for Data Manipulation Module 03: Working with Pivot Tables and Pivot Charts Module 04: Data Visualisation: Creating Charts and Graphs Module 05: Advanced Excel Functions for Complex Data Analysis Module 06: Data Filtering and Sorting Techniques Module 07: Conditional Formatting for Data Insights Module 08: Introduction to Data Modelling and Forecasting Module 09: Data Analysis Best Practices and Case Studies (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to advance in data-centric roles. Beginners with an interest in data analysis and Excel. Anyone looking to improve their Excel knowledge for career development. Career Path Data Analyst Business Analyst Financial Analyst Marketing Analyst Operations Manager Administrative Assistant Project Manager Research and Development Analyst

Microsoft Power BI Masterclass 2021 Course Overview: The "Microsoft Power BI Masterclass 2021" provides learners with the skills to become proficient in data analysis and visualization using Power BI. This comprehensive course covers the core functionalities of Power BI, from data preparation and transformation to creating impactful reports and dashboards. Learners will gain valuable insights into data modelling, visualisation, and the use of DAX for advanced calculations. By the end of the course, participants will be able to apply their knowledge to real-world projects, improving their ability to communicate data-driven insights effectively. This course is ideal for professionals and beginners who want to leverage Power BI to unlock the potential of their data. Course Description: This masterclass delves into the essential features of Microsoft Power BI, guiding learners through every stage of data analysis. Starting with project setup and data transformation in the Query Editor, the course progresses to advanced topics such as DAX functions and data storytelling. Learners will explore how to build data models, create dashboards, and employ Python in Power BI to enhance their reports. The course also covers Power BI Service for cloud-based analytics, row-level security for data protection, and integrating additional data sources. With a focus on empowering users to communicate insights clearly, the course ensures learners gain the expertise to manage data efficiently, make informed decisions, and stay up to date with evolving tools and features. Microsoft Power BI Masterclass 2021 Curriculum: Module 01: Introduction Module 02: Preparing our Project Module 03: Data Transformation - The Query Editor Module 04: Data Transformation - Advanced Module 05: Creating a Data Model Module 06: Data Visualization Module 07: Power BI & Python Module 08: Storytelling with Data Module 09: DAX - The Essentials Module 10: DAX - The CALCULATE function Module 11: Power BI Service - Power BI Cloud Module 12: Row-Level Security Module 13: More data sources Module 14: Next steps to improve & stay up to date (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to advance their data visualization expertise. Beginners with an interest in data science or business analytics. Business analysts or data professionals looking to upskill in Power BI. Career Path: Data Analyst Business Intelligence Analyst Data Scientist Power BI Developer Reporting Analyst Data Visualisation Expert

Course Overview This comprehensive course offers a deep dive into three essential technologies for data science: Python, JavaScript, and Microsoft SQL. Learners will gain foundational knowledge and practical skills in each of these key areas, which are crucial for handling data, creating interactive websites, and working with databases. By the end of the course, students will be proficient in writing Python code for data analysis, creating dynamic web content with JavaScript, and managing data with Microsoft SQL. The course is designed to equip learners with the technical skills needed to succeed in data science, making it a valuable investment for anyone looking to excel in this growing field. Course Description In this course, learners will explore the core principles of Python, JavaScript, and Microsoft SQL, all tailored to the needs of data science professionals. The curriculum covers Python’s data structures, functions, and libraries essential for data analysis, while JavaScript introduces students to web development skills, including client-side validation and data visualisation. The Microsoft SQL section focuses on data management, including filtering, joining, and structuring queries. Learners will develop a solid understanding of these technologies, which will enable them to manipulate data, automate processes, and design interactive applications. The course also includes real-world applications, ensuring learners are well-prepared for future opportunities in data science and web development. Course Modules: Module 01: JavaScript Getting Started Module 02: JavaScript Fundamentals Module 03: JavaScript Strings Module 04: JavaScript Operators Module 05: JavaScript Conditional Statements Module 06: JavaScript Control Flow Statements Module 07: JavaScript Functions Module 08: Data Visualization (Google Charts) Module 09: JavaScript Error Handling Module 10: JavaScript Client-Side Validations Module 11: Python Introduction Module 12: Python Basic Module 13: Python Strings Module 14: Python Operators Module 15: Python Data Structures Module 16: Python Conditional Statements Module 17: Python Control Flow Statements Module 18: Python Core Games Module 19: Python Functions Module 20: Python Args, KW Args for Data Science Module 21: Python Project Module 22: Publish Your Website for Live Module 23: MS SQL Statements Module 24: MS SQL Filtering Data Module 25: MS SQL Functions Module 26: MS SQL Joins Module 27: MS SQL Advanced Commands Module 28: MS SQL Structure and Keys Module 29: MS SQL Queries Module 30: MS SQL Structure Queries Module 31: MS SQL Constraints Module 32: MS SQL Backup and Restore (See full curriculum) Who is this course for? Individuals seeking to enhance their skills in data science. Professionals aiming to expand their knowledge in programming and database management. Beginners with an interest in Python, JavaScript, and SQL. Anyone looking to enter the field of data science or web development. Career Path Data Scientist Web Developer Database Administrator Data Analyst Front-End Developer Full Stack Developer Data Engineer

Diploma in Python Programming Course Overview The Diploma in Python Programming offers an in-depth exploration of Python, one of the most versatile and in-demand programming languages. This course is designed to provide learners with a strong foundation in Python, covering essential concepts such as data structures, functions, libraries, and file handling. Learners will gain the skills necessary to write Python code to solve real-world problems, enabling them to create applications, automate tasks, and perform data analysis. By the end of the course, learners will have the practical knowledge to use Python effectively for various programming tasks in both professional and personal settings. Course Description This comprehensive course begins with the basics of Python programming, guiding learners through essential concepts such as syntax, data types, and conditional statements. Learners will progress to more advanced topics, including file handling, data storage structures, and error handling. Key modules like the creation of user functions, working with external libraries, and implementing Python in database management provide valuable skills that can be directly applied in the workplace. This course also covers essential tools such as command prompt usage, Jupyter notebooks, and package management in Python. By the end of the course, learners will have developed the confidence and competence to apply Python across various domains, including software development, data analysis, and system automation. Diploma in Python Programming Curriculum Module 01: Introduction to Python Programming Module 02: Getting Started with Python Module 03: Conditional Branching with Python Module 04: Importing External/Internal Library in Python Module 05: Project Rock Paper and Scissors Module 06: Strings Operation in Python Module 07: Date and Time in Python Module 08: File Handling, Read and Write Using Python Module 09: Data Storage Structures: Tuple, List, and Dictionary Module 10: Writing User Functions in Python Module 11: Sending Mail Module 12: Import Tricks in Python Module 13: Import Operating System and Platform Module 14: Exceptions Handling in Python Module 15: Installing Packages and Scheduling in Python Module 16: Database in Python Using SQLite Module 17: Running Programs from Command Prompt and Jupyter Notebook Module 18: Conclusion (See full curriculum) Who is this course for? Individuals seeking to develop a foundational understanding of Python programming. Professionals aiming to enhance their programming skills for career advancement. Beginners with an interest in software development, data analysis, or automation. Anyone looking to pursue a career in programming or technology. Career Path Software Developer Data Analyst Automation Engineer Python Programmer Database Administrator IT Specialist

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure 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 DP-203T00 Data Engineering on Microsoft Azure 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.

Data Visualization Courses London. In this Power BI Course, you will learn how to translate data trends, summaries, statistics and insights from your data into powerful and inspirational visualizations This course is ideal for managers and data analysts who need to make business decisions based on data.

Maximize the value of data assets in the oil and gas sector with EnergyEdge's assessment-based training course on Python programming and analytics.

Course Overview This comprehensive course on Coding (HTML, C++, Python, JavaScript & IT) offers a structured introduction to the world of coding and information technology. It covers an expansive array of programming languages and technologies, including HTML, CSS, JavaScript, C++, Python, and PHP, alongside key IT concepts such as cybersecurity, cloud computing, and network security. Learners will develop a deep understanding of programming logic, software development, web development, and essential IT operations. Whether you're aiming to explore programming for the first time or expand your technical skill set, this course equips you with the knowledge required to navigate modern computing systems and coding environments. Upon completion, learners will be better prepared to pursue roles in web development, programming, system administration, and IT support across various industries. Course Description This course delivers an in-depth exploration of both coding and IT fundamentals, offering a diverse curriculum that spans core programming languages such as HTML, C++, Python, JavaScript, and R. It extends into cybersecurity, Linux scripting, ethical hacking, and computer networking—creating a well-rounded foundation for digital fluency. Learners are introduced to the design and development of web applications, front-end and back-end technologies, and essential tools such as GitHub, Heroku, and MySQL. The course further includes IT administration, encryption methods, cloud infrastructure, and system troubleshooting, ensuring coverage of key concepts necessary in today’s tech-driven world. With a focus on conceptual clarity and structured progression, learners will gain valuable knowledge aligned with current industry needs and expectations. Course Modules Module 01: Introduction to Coding With HTML, CSS, & Javascript Module 02: C++ Development: The Complete Coding Guide Module 03: Python Programming: Beginner To Expert Module 04: Learn Ethical Hacking From A-Z: Beginner To Expert Module 05: Bash Scripting, Linux and Shell Programming Module 06: JavaScript Project – Game Development with JS Module 07: R Programming for Data Science Module 08: Secure Programming of Web Applications Module 09: Advanced Diploma in PHP Web Development with MySQL, GitHub & Heroku Module 10: The Complete Front-End Web Development Course! Module 11: The Complete MySQL Server from Scratch: Bootcamp Module 12: Cyber Security Awareness Training Module 13: Cloud Computing / CompTIA Cloud+ (CV0-002) Module 14: CompTIA A+ (220-1001) Module 15: Building Your Own Computer Module 16: Computer Networks Security from Scratch to Advanced Module 17: IT Administration and Networking Module 18: Encryption Module 19: Advance Windows 10 Troubleshooting for IT HelpDesk Module 20: Microsoft Excel Complete Course (See full curriculum) Who is this course for? Individuals seeking to understand programming languages and IT fundamentals. Professionals aiming to transition into coding or expand their IT knowledge. Beginners with an interest in computing, programming, or digital technologies. Students or career changers preparing for roles in the tech sector. Career Path Web Developer Software Programmer IT Support Technician Network Administrator Cybersecurity Analyst Cloud Computing Technician Data Analyst Systems Engineer Helpdesk Specialist IT Consultant

Microsoft Office Basic to Advance Course Overview The "Microsoft Office Basic to Advanced" course provides comprehensive training on the essential applications in the Microsoft Office Suite. From Excel to Word, PowerPoint, and Access, this course equips learners with the skills needed to navigate and master each program's features. Whether you are looking to improve efficiency in everyday tasks or enhance your career prospects, this course covers everything from basic functions to advanced techniques, ensuring a thorough understanding of each program's capabilities. Upon completion, learners will be proficient in using Microsoft Office applications for personal, academic, and professional purposes, enhancing productivity and employability. Course Description This course dives into all key components of the Microsoft Office suite, offering in-depth coverage of Excel, Word, PowerPoint, and Access. Starting with the fundamentals, learners will gain expertise in managing data, creating documents, designing presentations, and managing databases. The course also covers advanced topics such as complex Excel functions, detailed document formatting in Word, effective presentation techniques in PowerPoint, and data management in Access. Through a blend of engaging activities and expert guidance, learners will acquire valuable skills to increase their productivity and confidently use these programs in any professional setting. Microsoft Office Basic to Advance Curriculum Module 01: Microsoft Excel 2019 New Features Module 02: Getting Started with Microsoft Excel Module 03: Performing Calculations Module 04: Modifying a Worksheet Module 05: Formatting a Worksheet Module 06: Printing Workbooks Module 07: Managing Workbooks Module 08: Microsoft Word 2019 Module 09: Microsoft Word 2019 New Features Module 10: Getting Started with Word Module 11: Formatting Text and Paragraphs Module 12: Working More Efficiently Module 13: Managing Lists Module 14: Adding Tables Module 15: Inserting Graphic Objects Module 16: Controlling Page Appearance Module 17: Preparing to Publish a Document Module 18: Workbooks - Microsoft Word 2016 (Beginner) Module 19: Microsoft PowerPoint 2019 Module 20: Microsoft PowerPoint 2019 New Features Module 21: PowerPoint Interface Module 22: Presentation Basics Module 23: Formatting Module 24: Inserting Options Module 25: Working with Objects Module 26: Table Module 27: Charts Module 28: Review and Presentation Module 29: Microsoft Access 2019 Module 30: Microsoft Access 2019 New Features Module 31: Introduction to Access Module 32: Modify Data Module 33: Working with Queries Module 34: Access Forms Module 35: Working with Reports (See full curriculum) Who is this course for? Individuals seeking to improve their Microsoft Office skills. Professionals aiming to enhance their software proficiency for career advancement. Beginners with an interest in office administration or data management. Those wishing to upgrade their knowledge of Microsoft Office for better job opportunities. Career Path Office Administrator Data Analyst Administrative Assistant Project Manager Executive Assistant IT Support Specialist