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Are you interested in learning and deploying applications at scale using Google Cloud platform? Do you lack hands-on exposure when it comes to deploying applications and seeing them in action? Then this course is for you. You will also learn microservices and event-driven architectures with real-world use case implementations.

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[vc_row][vc_column][vc_column_text] Description: This Python Basic to Advanced for Data Science Online Course is a great way to get started in programming. It covers the study of the Python language used to build most of the world's object-oriented systems. The course is for interested students with a good level of computer literacy who wish to acquire programming skills. It is also ideal for those who wish to move to a developer role or areas such as software engineering. This is a great course to develop your coding skills. This Python Basic to Advanced for Data Science Online Course is an ideal preliminary to the Object-Oriented Programming using Python. Join the course now! Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification: After completing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market.[/vc_column_text][/vc_column][/vc_row] Python 3 Beginners Module 01 Introduction FREE 00:29:00 Starter Examples 00:33:00 Learning C Concepts 00:13:00 Module 02 Data Types and Inference 00:20:00 Sizeof and IEEE 754 00:33:00 Constants L and R Values 00:11:00 Operators and Precedence 00:25:00 Literals 00:26:00 Module 03 Classes and Structs FREE 00:22:00 Enums 00:14:00 Unions 00:16:00 Introduction to Pointers 00:11:00 Pointers and Array Indexing 00:12:00 Using Const with Pointers 00:09:00 Pointers to String Literals 00:12:00 References 00:14:00 Smart Pointers 00:22:00 Arrays 00:15:00 Standard Library Strings 00:13:00 More Standard Library Strings 00:18:00 Functions 00:06:00 More Functions 00:16:00 Function Pointers 00:15:00 Control Statements 00:18:00 Python 3 Intermediate Module 04 Installing Python FREE 00:17:00 Documentation 00:30:00 Command Line 00:17:00 Variables 00:29:00 Simple Python Syntax 00:15:00 Keywords 00:18:00 Import Module 00:17:00 Additional Topics 00:23:00 Module 05 If Elif Else 00:31:00 Iterable 00:10:00 For 00:11:00 Loops 00:20:00 Execute 00:05:00 Exceptions 00:18:00 Data Types 00:24:00 Module 06 Number Types 00:28:00 More Number Types 00:13:00 Strings 00:20:00 More Strings 00:11:00 Files 00:08:00 Lists 00:15:00 Dictionaries 00:04:00 Tuples 00:07:00 Sets 00:09:00 Module 07 Comprehensions 00:10:00 Definitions 00:02:00 Functions 00:06:00 Default Arguments 00:06:00 Doc Strings 00:06:00 Variadic Functions 00:07:00 Factorial 00:07:00 Function Objects 00:07:00 Module 08 Lambda 00:11:00 Generators 00:06:00 Closures 00:10:00 Classes 00:09:00 Object Initialization 00:05:00 Class Static Members 00:07:00 Classic Inheritance 00:10:00 Data Hiding 00:07:00 Python 3 Advanced Iterators and Generators FREE 00:16:00 Regular Expressions 00:19:00 Introspection and Lambda Functions 00:27:00 Metaclasses and Decorators 00:24:00 Modules and Packages 00:25:00 Working with APIs 00:15:00 Metaprogramming Primer 00:19:00 Decorators and Monkey Patching 00:21:00 XML and JSON Structure 00:10:00 Generating XML and JSON 00:17:00 Parsing XML and JSON 00:19:00 Implementing Algorithms 00:19:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

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Course Curriculum Unit 01: Excel from A-Z Course Introduction Excel from A-Z Course Intro 00:03:00 Excel Job Opportunities 00:03:00 Excel Job Types 00:04:00 Microsoft Excel Marketplace 00:04:00 What is Microsoft Excel? 00:04:00 Who is This Course For? 00:03:00 Unit 02: Getting Started With Excel Finding & Opening Excel 00:01:00 Excel's Start Screen 00:03:00 Explaining the Excel Interface 00:03:00 Excel Interface Continued 00:01:00 Excel Workbook vs. Excel Worksheet 00:02:00 Saving an Excel Document 00:04:00 Customizing the Quick Access Toolbar 00:02:00 Customizing the Excel Ribbon 00:03:00 Excel Shortcut Keys 00:02:00 Unit 03: Values, Referencing and Formulas Creating Excel Labels 00:03:00 Entering Numeric Values in Excel 00:03:00 Formatting Date Values in Excel 00:05:00 Building Basic Formulas in Excel 00:05:00 Order of Operations 00:06:00 Relative vs. Absolute Cell References 00:07:00 Unit 04: Intro to Excel Functions Excel Functions Explained 00:03:00 The SUM() Function 00:08:00 The MIN() & MAX() Function 00:04:00 The AVERAGE() Function 00:02:00 COUNT() Functions 00:05:00 Unit 05: Adjusting Excel Worksheets Moving & Copying Data 00:07:00 Insert & Delete Rows and Columns 00:05:00 Adjusting the Width and Height of Cells 00:05:00 Hiding and Unhiding Excel Rows and Columns 00:04:00 Renaming, Moving & Deleting Excel Worksheets 00:05:00 Adding Protection to Specific Cells 00:04:00 Protecting the Structure of a Workbook 00:02:00 Adding a Workbook Password to Open File 00:02:00 Unit 06: Visually Pleasing Cell Formatting Formatting Fonts and Cell Background Color 00:05:00 Adding Cell Borders 00:05:00 Formatting Data Appropriately 00:05:00 The Magic behind Excel's Format Painter 00:03:00 Creating Styles for Formatting Efficiency 00:06:00 Merging Cells for a Cleaner Look 00:03:00 The Power of Conditional Formatting 00:06:00 Unit 07: How to Insert Images and Shapes! Grab User's Attention using Illustrations 00:09:00 Customizing Icons 00:05:00 Create Compelling Graphics with SmartArt 00:06:00 Unit 08: Visualize Data with Charts The Commonly Used Column Chart 00:03:00 Changing the Chart Design.mp4 00:02:00 Formatting Elements of a Chart 00:06:00 Modifying the Data, Type & Location of a Chart 00:06:00 Unit 09: Excel's Printing Options Print Preview Options 00:04:00 Excel's Page Layout View 00:07:00 Printing a Specific Range of Cells 00:03:00 Converting Spreadsheets to PDF Files 00:02:00 Unit 10: Benefits of Using Excel Templates Why Create an Excel Template 00:01:00 How to Create an Excel Template 00:05:00 Unit 11: Working with Excel Datasets How to Prepare Data for Analysis 00:04:00 How to Sort Data in Excel 00:03:00 Multi-Level Sorting 00:03:00 Custom Sorting Datasets in Excel 00:02:00 Applying Filters to Datasets 00:05:00 Creating Subtotals within a Dataset 00:06:00 Converting Datasets into Tables 00:06:00 Little Slice of Pie Charts 00:05:00 Finding & Removing Duplicate Values 00:07:00 Unit 12: Excel Database Functions The SUMIF() Function 00:09:00 The DSUM() Function 00:08:00 The DSUM() Function Cont. 00:07:00 The SUBTOTAL() Function 00:06:00 Unit 13: Excel Data Validation What is Excel Data Validation? 00:02:00 Creating a Drop Down List with Data Validation 00:07:00 Different Types of Excel Data Validation 00:06:00 Adding Custom Alerts to Data Validation 00:07:00 Creating a Dynamic Drop Down List 00:03:00 Complex Validation: Dependent Drop Down List! 00:09:00 Unit 14: Excel PivotTables Creating an Excel Pivot Table 00:06:00 Modifying Excel PivotTables 00:06:00 Grouping & Filtering PivotTable Data 00:06:00 Drilling Down into PivotTable Data 00:02:00 Creating Pivot Charts & Utilizing Slicers 00:08:00 Unit 15: Excel's PowerPivot Add-In What is PowerPivot? 00:04:00 Activating the Excel PowerPivot Add-In 00:02:00 Creating Relationships between Data Tables.mp4 00:06:00 Using Data Models to Create PivotTables 00:05:00 How to Create PowerPivot KPI's 00:08:00 Unit 16: Excel's Conditional Functions Excels IF Function 00:05:00 IF() Function with AND() Criteria 00:05:00 IF() Function with OR() Criteria 00:05:00 Nesting Multiple IF() Functions 00:07:00 The COUNTIF() Function 00:04:00 Key Benefits of Named Ranges 00:04:00 Unit 17: Excel's Lookup Function VLOOKUP() Function 00:09:00 The Beauty of Excel's IFERROR() Function 00:04:00 HLOOKUP() Function 00:06:00 The INDEX Function 00:05:00 MATCH() Function 00:05:00 INDEX() and MATCH() Combined 00:05:00 Two-Way Lookup with INDEX() and MATCH() 00:04:00 Unit 18: Text Based Functions in Excel LEFT(), RIGHT() and MID() Function 00:07:00 Extracting Specific Text using LEN() & SEARCH() 00:13:00 Combining Text with CONCATENATE() 00:06:00 Quick Tips & Other Text Based Functions 00:06:00 Unit 19: Auditing Formulas and Views in Excel Tracing Precedents & Dependents in Formulas 00:04:00 Showing Formulas 00:02:00 Grouping Data 00:03:00 3D Referencing in Formulas 00:05:00 Utilizing the Watch Window in Excel 00:03:00 How to Freeze Panes in Excel 00:03:00 Unit 20: Excel's 'what If?' Tools Excel's Scenario Manager Tool 00:06:00 Goal Seek in Excel 00:06:00 Compare Results with Excel Data Tables 00:04:00 Solver Tool 00:11:00 Unit 21: Welcome to Excel VBA The Power Behind Excel VBA 00:03:00 A Look Inside the Visual Basic Editor (VBE) 00:04:00 Recording a Macro 00:09:00 Saving & Opening a Macro-Enabled Workbook 00:02:00 Unit 22: The VBA Language Modules and Procedures 00:07:00 Objects, Methods and Properties 00:06:00 Excel VBA Variables 00:05:00 Unit 23: Writing VBA Code Referencing a Range 00:13:00 InputBox & MsgBox 00:06:00 Using Variables in VBA Code 00:05:00 If Then Else Statement 00:10:00 Worksheet Functions inside VBA 00:08:00 Creating User Defined Functions 00:09:00 User Defined Functions within VBA Scripts 00:06:00 Unit 24: Important VBA Tools and Logic Find Last Row of Data 00:06:00 Find Last Column of Data 00:03:00 With Statement 00:05:00 Debugging & Error Handling 00:07:00 Debugging & Error Handling Cont. 00:07:00 Unit 25: Excel VBA Loop For Next Loop 00:09:00 Do Until Loop 00:06:00 For Each Loop 00:04:00 Unit 26: Triggering Macros Assigning Macros to Shapes 00:04:00 Form Controls vs ActiveX Controls 00:08:00 Worksheet Events 00:04:00 Workbook Events 00:03:00 Fun with VBA Events! 00:07:00 Unit 27: Excel User Forms Creating an Excel UserForm 00:03:00 Adding Controls to UserForms 00:10:00 How to Show an UserForm 00:03:00 Passing TextBox Values to Desired Cells 00:07:00 Passing Option Buttons to Desired Cells 00:07:00 UserForm ComboBoxes 00:08:00 Clearing Values from UserForm Controls 00:03:00 How to Close an UserForm 00:02:00 UserForms and Protected Sheets 00:05:00 Unit 28: Starting a Career in Excel Creating an Excel Resume 00:05:00 Getting Started with Freelancing 00:06:00 How to Become an Excel Freelancer 00:05:00 Top Freelance Websites 00:05:00 How to Get Your First Client 00:08:00 Personal Branding 00:07:00 Networking Do's and Don'ts 00:04:00 Importance of Having a Website 00:04:00 Resources Resources - Microsoft Excel 00:00:00

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.

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