239 Import/Export courses
The Microsoft Access 2016 Beginner to Advanced course is a comprehensive training program covering all levels of proficiency. From creating simple databases to advanced querying, form creation, report generation, and database management, this course provides a deep understanding of Microsoft Access's features and functions. LEARNING OUTCOMES: 1. Build and modify Access databases, tables, and fields. 2. Create effective queries to sort, filter, and summarize data. 3. Develop professional-looking reports with controls, charts, and calculations. 4. Design forms with controls, tab pages, and conditional formatting. 5. Automate tasks using macros and understand the basics of VBA. 6. Manage database performance, security, and object dependencies. 7. Create a database switchboard and modify startup options. 8. Understand data normalization, table relationships, and import/export processes. WHY BUY THIS MICROSOFT ACCESS 2016 BEGINNER TO ADVANCED? 1. Digital Certificate, Transcript, student ID all included in the price 2. Absolutely no hidden fees 3. Directly receive CPD accredited qualifications after course completion 4. Receive one to one assistance on every weekday from professionals 5. Immediately receive the PDF certificate after passing 6. Receive the original copies of your certificate and transcript on the next working day 7. Easily learn the skills and knowledge from the comfort of your home CERTIFICATION After studying the course materials of the Microsoft Access 2016 Beginner to Advanced you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. WHO IS THIS COURSE FOR? * Beginners with no previous experience in Microsoft Access. * Professionals seeking to enhance their database management and reporting skills. * Individuals aiming to become proficient in creating and maintaining databases. * Students pursuing careers in data analysis, administration, or database management. PREREQUISITES This Microsoft Access 2016 Beginner to Advanced was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. CAREER PATH * Data Analyst: Analyze, interpret, and present data insights using Access. * Database Administrator: Design, implement, and maintain databases for organizations. * Administrative Assistant: Manage data, generate reports, and streamline processes. * Project Manager: Organize project-related data and create performance reports. * Business Owner: Build and manage databases to support business operations. COURSE CURRICULUM Module - 1 Orientation to Microsoft Access 01:00:00 Create a Simple Access Database 01:00:00 Get Help in Microsoft Access 00:30:00 Modify Table Data 00:30:00 Work with Records 01:00:00 Sort and Filter Records 00:30:00 Create Lookups 01:00:00 Join Data from Different Tables in a Query 01:00:00 Sort and Filter Data in a Query 01:00:00 Perform Calculations in a Query 00:30:00 Create Parameter Queries 00:30:00 Create Action Queries 00:30:00 Create Find Duplicate and Find Unmatched Queries 00:30:00 Summarize Data 00:30:00 Create a Report 01:00:00 Add Controls to a Report 00:30:00 Enhance the Appearance of a Report 00:30:00 Prepare a Report for Print 00:30:00 The Access Options Dialog Box 01:00:00 Relational Database Design 00:30:00 Create a Table 01:00:00 Modify a Table and Fields 00:30:00 Create Table Relationships 00:30:00 Create Query Joins 00:30:00 Join Tables That Have No Common Fields 00:30:00 Relate Data within a Table 00:30:00 Work with Subdatasheets 00:30:00 Create Subqueries 00:30:00 Data Normalization 01:00:00 Create a Junction Table 00:30:00 Import Data into Access 00:30:00 Export Data to Text File Formats 00:30:00 Export Access Data to Excel 00:30:00 Create a Mail Merge 00:30:00 Organize Report Information 00:30:00 Format Reports 00:30:00 Include Charts in a Report 00:30:00 Add a Calculated Field to a Report 00:30:00 Add a Subreport to an Existing Report 00:30:00 Create a Mailing Label Report 00:30:00 Publish a Report as PDF 00:30:00 Activities - Microsoft Access 2016 for Beginners 00:00:00 Module - 2 Add Controls to Forms 01:00:00 Set Form Controls 01:00:00 Create Subforms 00:30:00 Organize Information with Tab Pages 00:30:00 Enhance Navigation with Forms 00:30:00 Format a Form 01:00:00 Apply Conditional Formatting 00:30:00 Field Validation 00:30:00 Form and Record Validation 00:30:00 Create a Macro 01:00:00 Restrict Records Using a Condition 00:30:00 Validate Data Using a Macro 00:30:00 Automate Data Entry Using a Macro 00:30:00 Convert a Macro to VBA 00:30:00 Link Tables to External Data Sources 00:30:00 Manage a Database 00:30:00 Determine Object Dependency 00:30:00 Document a Database 00:30:00 Analyze the Performance of a Database 00:30:00 Split a Database for Multiple User Access 00:30:00 Implement Security 00:30:00 Set Passwords 00:30:00 Convert an Access Database to an ACCDE File 00:30:00 Package a Database with a Digital Signature 00:30:00 Create a Database Switchboard 01:00:00 Modify a Database Switchboard 00:30:00 Set Startup Options 00:30:00 Activities - Microsoft Access 2016 Advanced 00:00:00
Google Cloud Engineer Associate Certification Bootcamp
By Nexus Human
Duration 5 Days 30 CPD hours This course is intended for Cloud Solutions Architects DevOps Engineers Individuals using Google Cloud Platform who deploy applications, monitor operations, and manage enterprise solutions Overview At course completion, you will have attained knowledge of: Fundamentals of Google Cloud Platform (GCP) Google Cloud Storage Google Compute Engine Google Cloud SQL Load Balancing (LB) Google Cloud Monitoring Auto-Scaling Virtual Private Cloud (VPC) Network Cloud Identity and Access Management (IAM) Cloud CDN and DNS Cloud VPN Google Cloud Deployment Manager Google Container Engine Cloud Run Cloud Bigtable Cloud Datastore Cloud BigQuery Cloud DataFlow Cloud DataProc Cloud Pub/Sub In this course you will attain a deep knowledge of Google Cloud Platform infrastructure and design patterns on developing applications on GCP. This course will prepare you for the Google Cloud Architect Associate Certification Exam. FUNDAMENTALS OF GOOGLE CLOUD PLATFORM (GCP) * Overview * Regions and Zones * Review of major GCP services * GOOGLE CLOUD STORAGE * Fundamental APIs * Consistency * Cloud Storage Namespace * Buckets and Objects * Bucket and Object Naming Guidelines * Encryption * Object Versioning * Object Lifecycle Management * Access Control * Access Control Lists * Signed URL * Multipart upload * Resumable upload * Understanding Pricing for Cloud Storage * Offline Media Import/Export * Architecture case study of common Use Cases of Google Cloud Storage * Hands-on: Cloud Storage Lab; Creating Buckets, objects, and managing access control * GOOGLE COMPUTE ENGINE * Compute Engine Architecture * VM Instances types * Persistence Disks * Images * Generating Custom Images * IP Addresses * Static IPs * Ephemeral * Access Control Options * IAM * Service Account * Monitoring Instances with Google Cloud Monitoring * Compute Engine Networks and Firewalls * Hands-on: Hosting an Application on Compute Engine * GOOGLE CLOUD SQL * Core advantages of Cloud SQL * Cloud SQL database instance types * Access Control * High availability options * Failover * Read replica * Backup options * On Demand * Automated * Understanding Pricing of Cloud SQL * LOAD BALANCING (LB) * Fundamentals of a Load Balancer * Network Load balancing * HTTPS Load balancing * Cross region Load balancing * Content Load balancing * Target proxies * SSL Load Balancing * Internal Load Balancing * Network Load Balancing * Understanding Pricing for Load Balancer * GOOGLE CLOUD MONITORING * Architecture of Cloud Monitoring * Supported metrics * Stackdriver Monitoring APIs * AUTO-SCALING * Overview of Autoscaling * Auto-scaling Fundamentals * Instance groups * Templates * Policies * Decisions * Hands-on: Deploying a scale application on GCP using Autoscaling, Compute Engine, Cloud SQL, Load Balancers. * VIRTUAL PRIVATE CLOUD (VPC) NETWORK * Salient features of Virtual Private Cloud (VPC) Network Infrastructure * Virtual Private Cloud (VPC) Networking Fundamentals * Subnetworks * Firewall * Internal DNS * Network Routes * Hands-on: Hosting Secure Applications in Google Cloud VPC Networks * CLOUD IDENTITY AND ACCESS MANAGEMENT (IAM) * Introduction * User and Service Accounts * IAM Roles * Policy * Hands-on: Managing Users, Policies and Granting Roles using Service Accounts * CLOUD CDN AND DNS * What is CDN * Google Cloud CDN * Cloud CDN Concepts * Some of the Cloud CDN Edge locations * Cloud DNS * Cloud DNS Terminologies * Supported Record Types * Hands-on: Moving an Existing Domain Name to Cloud DNS * CLOUD VPN * Cloud VPN overview * Types of Cloud VPN * Specifications * Maintenance and Availability * Google Cloud Deployment Manager * Deployment Manager * Deployment Manager Fundamentals * Runtime Configurator * Quotas * Hands-on: Generating and Creating Cloud Deployment Manager Template * GOOGLE CONTAINER ENGINE * Google Container Engine Overview * Docker Overview * Kubernetes Terminologies * Replication Controller * Deployment * Price and Quotas * Hands-on: Deploying WordPress Cluster using Container Engine * CLOUD RUN * Overview of Cloud Run * Deploy a Prebuilt Sample container * CLOUD BIGTABLE * Overview of Cloud Bigtable * Access Control * Performance * Locations * Cloud Datastore * Overview of Cloud Datastore * Limits * Storage Size * Multitenancy * Benefits of Multitenancy * Encryption * Locations * CLOUD BIGQUERY * BigQuery Overview * Interacting with BigQuery * Datasets, Tables, and Views * Partitioned Tables * Query Plan Explanation * Hands-on: Getting Started with BigQuery * CLOUD DATAFLOW * Overview * Programming Model * DataFlow SDK 1.x for java * Cloud Dataflow SDK 2.x * Security and Permissions * Advanced Access Control * CLOUD DATAPROC * Overview * Clusters * Versioning * CLOUD PUB/SUB * Overview of Cloud Pub/Sub * Pub/Sub Concepts and Message Flow * Data Model * Cleanup of All Services * Hands-on: Cloud Pub/Sub Lab with Background Cloud Function * ADDITIONAL COURSE DETAILS: Nexus Humans Google Cloud Engineer Associate Certification Bootcamp 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 Google Cloud Engineer Associate Certification Bootcamp 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.
Introduction to R Programming
By Nexus Human
Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. WHAT IS R * ? What is R? * ? Positioning of R in the Data Science Space * ? The Legal Aspects * ? Microsoft R Open * ? R Integrated Development Environments * ? Running R * ? Running RStudio * ? Getting Help * ? General Notes on R Commands and Statements * ? Assignment Operators * ? R Core Data Structures * ? Assignment Example * ? R Objects and Workspace * ? Printing Objects * ? Arithmetic Operators * ? Logical Operators * ? System Date and Time * ? Operations * ? User-defined Functions * ? Control Statements * ? Conditional Execution * ? Repetitive Execution * ? Repetitive execution * ? Built-in Functions * ? Summary INTRODUCTION TO FUNCTIONAL PROGRAMMING WITH R * ? What is Functional Programming (FP)? * ? Terminology: Higher-Order Functions * ? A Short List of Languages that Support FP * ? Functional Programming in R * ? Vector and Matrix Arithmetic * ? Vector Arithmetic Example * ? More Examples of FP in R * ? Summary MANAGING YOUR ENVIRONMENT * ? Getting and Setting the Working Directory * ? Getting the List of Files in a Directory * ? The R Home Directory * ? Executing External R commands * ? Loading External Scripts in RStudio * ? Listing Objects in Workspace * ? Removing Objects in Workspace * ? Saving Your Workspace in R * ? Saving Your Workspace in RStudio * ? Saving Your Workspace in R GUI * ? Loading Your Workspace * ? Diverting Output to a File * ? Batch (Unattended) Processing * ? Controlling Global Options * ? Summary R TYPE SYSTEM AND STRUCTURES * ? The R Data Types * ? System Date and Time * ? Formatting Date and Time * ? Using the mode() Function * ? R Data Structures * ? What is the Type of My Data Structure? * ? Creating Vectors * ? Logical Vectors * ? Character Vectors * ? Factorization * ? Multi-Mode Vectors * ? The Length of the Vector * ? Getting Vector Elements * ? Lists * ? A List with Element Names * ? Extracting List Elements * ? Adding to a List * ? Matrix Data Structure * ? Creating Matrices * ? Creating Matrices with cbind() and rbind() * ? Working with Data Frames * ? Matrices vs Data Frames * ? A Data Frame Sample * ? Creating a Data Frame * ? Accessing Data Cells * ? Getting Info About a Data Frame * ? Selecting Columns in Data Frames * ? Selecting Rows in Data Frames * ? Getting a Subset of a Data Frame * ? Sorting (ordering) Data in Data Frames by Attribute(s) * ? Editing Data Frames * ? The str() Function * ? Type Conversion (Coercion) * ? The summary() Function * ? Checking an Object's Type * ? Summary EXTENDING R * ? The Base R Packages * ? Loading Packages * ? What is the Difference between Package and Library? * ? Extending R * ? The CRAN Web Site * ? Extending R in R GUI * ? Extending R in RStudio * ? Installing and Removing Packages from Command-Line * ? Summary READ-WRITE AND IMPORT-EXPORT OPERATIONS IN R * ? Reading Data from a File into a Vector * ? Example of Reading Data from a File into A Vector * ? Writing Data to a File * ? Example of Writing Data to a File * ? Reading Data into A Data Frame * ? Writing CSV Files * ? Importing Data into R * ? Exporting Data from R * ? Summary STATISTICAL COMPUTING FEATURES IN R * ? Statistical Computing Features * ? Descriptive Statistics * ? Basic Statistical Functions * ? Examples of Using Basic Statistical Functions * ? Non-uniformity of a Probability Distribution * ? Writing Your Own skew and kurtosis Functions * ? Generating Normally Distributed Random Numbers * ? Generating Uniformly Distributed Random Numbers * ? Using the summary() Function * ? Math Functions Used in Data Analysis * ? Examples of Using Math Functions * ? Correlations * ? Correlation Example * ? Testing Correlation Coefficient for Significance * ? The cor.test() Function * ? The cor.test() Example * ? Regression Analysis * ? Types of Regression * ? Simple Linear Regression Model * ? Least-Squares Method (LSM) * ? LSM Assumptions * ? Fitting Linear Regression Models in R * ? Example of Using lm() * ? Confidence Intervals for Model Parameters * ? Example of Using lm() with a Data Frame * ? Regression Models in Excel * ? Multiple Regression Analysis * ? Summary DATA MANIPULATION AND TRANSFORMATION IN R * ? Applying Functions to Matrices and Data Frames * ? The apply() Function * ? Using apply() * ? Using apply() with a User-Defined Function * ? apply() Variants * ? Using tapply() * ? Adding a Column to a Data Frame * ? Dropping A Column in a Data Frame * ? The attach() and detach() Functions * ? Sampling * ? Using sample() for Generating Labels * ? Set Operations * ? Example of Using Set Operations * ? The dplyr Package * ? Object Masking (Shadowing) Considerations * ? Getting More Information on dplyr in RStudio * ? The search() or searchpaths() Functions * ? Handling Large Data Sets in R with the data.table Package * ? The fread() and fwrite() functions from the data.table Package * ? Using the Data Table Structure * ? Summary DATA VISUALIZATION IN R * ? Data Visualization * ? Data Visualization in R * ? The ggplot2 Data Visualization Package * ? Creating Bar Plots in R * ? Creating Horizontal Bar Plots * ? Using barplot() with Matrices * ? Using barplot() with Matrices Example * ? Customizing Plots * ? Histograms in R * ? Building Histograms with hist() * ? Example of using hist() * ? Pie Charts in R * ? Examples of using pie() * ? Generic X-Y Plotting * ? Examples of the plot() function * ? Dot Plots in R * ? Saving Your Work * ? Supported Export Options * ? Plots in RStudio * ? Saving a Plot as an Image * ? Summary USING R EFFICIENTLY * ? Object Memory Allocation Considerations * ? Garbage Collection * ? Finding Out About Loaded Packages * ? Using the conflicts() Function * ? Getting Information About the Object Source Package with the pryr Package * ? Using the where() Function from the pryr Package * ? Timing Your Code * ? Timing Your Code with system.time() * ? Timing Your Code with System.time() * ? Sleeping a Program * ? Handling Large Data Sets in R with the data.table Package * ? Passing System-Level Parameters to R * ? Summary LAB EXERCISES * Lab 1 - Getting Started with R * Lab 2 - Learning the R Type System and Structures * Lab 3 - Read and Write Operations in R * Lab 4 - Data Import and Export in R * Lab 5 - k-Nearest Neighbors Algorithm * Lab 6 - Creating Your Own Statistical Functions * Lab 7 - Simple Linear Regression * Lab 8 - Monte-Carlo Simulation (Method) * Lab 9 - Data Processing with R * Lab 10 - Using R Graphics Package * Lab 11 - Using R Efficiently
AZ-104: Microsoft Azure Administrator Full Course
By Packt
This course teaches you to prepare for AZ-104 Certification. The course gives you the knowledge to make you Azure ready and become a better Azure administrator. All the changes that were made to AZ-103 by Microsoft to make it AZ-104 are incorporated in this course.
Embark on a comprehensive journey into the world of MySQL with a focus on its applications in Data Science and Analytics. This course is structured to take you from the fundamentals to advanced topics in MySQL Server. Covering SQL basics, data manipulation and definition, control and analytic functions, and database management, you'll acquire the essential skills for harnessing MySQL's power in data-driven decision-making. Learning Outcomes: * Establish a strong foundation in SQL and MySQL. * Set up and configure SQL Server for efficient data handling. * Master SQL's Data Manipulation, Definition, and Control Language. * Create and optimize SQL queries for data analysis. * Perform advanced data analytics using SQL. * Understand the power of GROUP BY and JOIN statements. * Implement data constraints and views for data integrity and security. * Develop proficiency in stored procedures, data import/export, and database backup/restore. Why buy this Learn MySQL from Scratch for Data Science and Analytics? * Unlimited access to the course for forever * Digital Certificate, Transcript, student ID all included in the price * Absolutely no hidden fees * Directly receive CPD accredited qualifications after course completion * Receive one to one assistance on every weekday from professionals * Immediately receive the PDF certificate after passing * Receive the original copies of your certificate and transcript on the next working day * Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Learn MySQL from Scratch for Data Science and Analytics you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Learn MySQL from Scratch for Data Science and Analytics course is ideal for * Aspiring Data Scientists and Analysts. * Database Administrators and Developers. * Students and professionals seeking to enter the field of Data Science. * Anyone looking to enhance their SQL and MySQL skills for data-related roles. Prerequisites This Learn MySQL from Scratch for Data Science and Analytics was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path * Data Analyst: £25,000 - £50,000 per year. * Database Administrator: £30,000 - £60,000 per year. * SQL Developer: £30,000 - £60,000 per year. * Data Scientist: £40,000 - £80,000 per year. * Business Intelligence Analyst: £35,000 - £65,000 per year. COURSE CURRICULUM Learn MySQL from Scratch for Data Science and Analytics Section 01: Getting Started Introduction 00:02:00 How to get course requirements 00:01:00 Getting started on Windows, Linux or Mac 00:01:00 How to ask great questions 00:01:00 FAQ's 00:01:00 What is Source Code? 00:09:00 Section 02: SQL Server setting up Section Introduction 00:01:00 MySQL Server Installation 00:14:00 Connect MySQL Server Instance 00:06:00 MySQL Workbench overview 00:11:00 Download and Restore Sample Database 00:08:00 Section 03: SQL Database basics Section Introduction 00:01:00 Overview of Databases 00:09:00 Creating Database 00:07:00 SQL Data Types 00:04:00 Column Data Types on Workbench 00:07:00 Creating Table 00:04:00 Overview of Primary and Foreign Key 00:03:00 Primary Key 00:06:00 Foreign Key 00:12:00 Creating Temporary tables 00:12:00 EER - Enhanced Entity Relationship Diagrams 00:04:00 Section 04: SQL DML (Data Manipulation Language) Section Introduction 00:01:00 Insert statement 00:07:00 Update statement 00:06:00 Delete statement 00:03:00 Section 05: SQL DDL (Data Definition Language) Section Introduction 00:01:00 CREATE table statement 00:08:00 DROP statement 00:03:00 ALTER statement 00:05:00 TRUNCATE statement 00:03:00 COMMENT in query 00:02:00 RENAME table 00:03:00 Section 06: SQL DCL (Data Control Language) Create Database user 00:03:00 GRANT permissions 00:06:00 REVOKE permissions 00:04:00 Section 07: SQL Statement Basic Section Introduction 00:01:00 SQL Statement basic 00:03:00 SELECT Statement 00:03:00 SELECT DISTINCT 00:02:00 SELECT with column headings 00:01:00 Column AS statement 00:02:00 DASHBOARD Analytics 00:06:00 Section 08: Filtering Data rows SELECT WHERE Clause - theory 00:03:00 SELECT WHERE Clause - practical 00:06:00 Section 09: Aggregate functions for Data Analysis Sum() 00:06:00 Min()-Max() 00:03:00 Section 10: SQL Data Analyticstatements Order By statement 00:05:00 SELECT TOP 3 records 00:02:00 BETWEEN command 00:06:00 IN operator 00:03:00 Search Data usingLIKE cards 00:05:00 Section 11: SQL Group by statement Section Introduction 00:01:00 Group by - theory 00:04:00 Data Analytics with Group By 00:04:00 HAVING statement 00:03:00 Section 12: JOINS Overview of Joins 00:02:00 What are Joins 00:02:00 Inner join 00:07:00 Left outer join 00:02:00 Right outer join 00:02:00 Union 00:03:00 CERTESIAN Product or Cross Join 00:03:00 Query Exercise 00:01:00 Solution for Query Exercise 00:01:00 Section 13: SQL Constraints Section introduction 00:01:00 Check constraint 00:09:00 NOT NULL constraint 00:03:00 UNIQUE constraint 00:06:00 Section 14: Views Creating Views 00:03:00 Data Analytic Views from multiple tables 00:03:00 Section 15: Advanced SQL Functions Section Introduction 00:01:00 Timestamp 00:03:00 Extract from timestamp 00:03:00 Mathematical scalar functions 00:03:00 String functions3 00:07:00 Advanced functions 00:04:00 Sub Queries 00:03:00 SELECT with calculations 00:05:00 Section 16: SQL Stored procedures Create stored procedure 00:06:00 Stored procedure with parameter 00:03:00 Drop Procedure 00:01:00 Section 17: Import & Export data Section Introduction 00:01:00 Import .csv file 00:04:00 Export Data to .csv file 00:02:00 Section 18: Backup and Restore Database Section Introduction 00:01:00 Creating Database backup 00:02:00 Restoring Database backup 00:02:00
This comprehensive course, 'SQL for Data Science, Data Analytics, and Data Visualization,' covers essential SQL concepts and tools for working with data. Participants will learn to manipulate, analyze, and visualize data using SQL Server, Azure Data Studio, and other relevant tools. The course also delves into advanced SQL commands, stored procedures, and data import/export, making it ideal for aspiring data professionals. LEARNING OUTCOMES: * Set up and configure SQL Server and SQL Azure Data Studio for data analysis. * Master SQL statements for data manipulation, data structure, and user management. * Utilize SQL queries, joins, and aggregate functions for efficient data analysis. * Understand SQL constraints, views, and advanced commands for in-depth data exploration. * Create and implement SQL stored procedures to automate tasks. * Leverage Azure Data Studio for data visualization and perform data analysis with SQL. WHY BUY THIS SQL FOR DATA SCIENCE, DATA ANALYTICS AND DATA VISUALIZATION? 1. Unlimited access to the course for forever 2. Digital Certificate, Transcript, student ID all included in the price 3. Absolutely no hidden fees 4. Directly receive CPD accredited qualifications after course completion 5. Receive one to one assistance on every weekday from professionals 6. Immediately receive the PDF certificate after passing 7. Receive the original copies of your certificate and transcript on the next working day 8. Easily learn the skills and knowledge from the comfort of your home CERTIFICATION After studying the course materials of the SQL for Data Science, Data Analytics and Data Visualization there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. WHO IS THIS COURSE FOR? This SQL for Data Science, Data Analytics and Data Visualization course is ideal for * Students * Recent graduates * Job Seekers * Anyone interested in this topic * People already working in the relevant fields and want to polish their knowledge and skill. PREREQUISITES This SQL for Data Science, Data Analytics and Data Visualization does not require you to have any prior qualifications or experience. You can just enrol and start learning.This SQL for Data Science, Data Analytics and Data Visualization was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. CAREER PATH As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This SQL for Data Science, Data Analytics and Data Visualization is a great way for you to gain multiple skills from the comfort of your home. COURSE CURRICULUM Section 01: Getting Started Introduction 00:03:00 How to get course requirements 00:03:00 Getting started on Windows, Linux or Docker 00:01:00 How to ask great questions 00:01:00 FAQ's 00:01:00 Section 02: SQL Server setting up Section Introduction 00:02:00 Microsoft SQL Server Installation 00:19:00 SQL Server Management Studio (SSMS) Installation 00:08:00 How to connect MS SQL (Windows Authentication) 00:04:00 How to connect MS SQL (SQL Server Authentication) 00:03:00 Download and Restore Sample Database 00:07:00 Section 03: SQL Azure Data Studio What is Azure Data Studio 00:06:00 Azure Data Studio Installation steps 00:07:00 Azure Data Studio to Connect SQL Server 00:09:00 Create a Database 00:07:00 Create a Table 00:09:00 Insert Data rows 00:07:00 View the Data returned by Query 00:03:00 Section 04: SQL Database basic SSMS Section Introduction 00:01:00 Overview of Databases8 00:11:00 Creating Database 00:05:00 SQL Data Types 00:03:00 Column Data Types on SSMS 00:04:00 Creating Table 00:09:00 Overview of Primary Key and Foreign Key 00:04:00 Primary Key 00:04:00 Foreign Key 00:07:00 Creating Temporary tables 00:06:00 Section 05: SQL Statements for DATA Section Introduction 00:01:00 Insert statement 00:08:00 Update statement 00:05:00 Delete statement 00:03:00 Section 06: SQL Data Structure statements Section Introduction 00:01:00 CREATE table statement 00:03:00 DROP statement 00:02:00 ALTER statement 00:05:00 TRUNCATE statement 00:04:00 COMMENT in query 00:01:00 RENAME 00:02:00 Section 07: SQL User Management Create Database user 00:04:00 GRANT permissions 00:06:00 REVOKE permissions 00:04:00 Section 08: SQL Statement Basic Section Introduction 00:01:00 SQL Statement basic 00:03:00 SELECT Statement 00:07:00 SELECT DISTINCT 00:03:00 SELECT with column headings 00:03:00 Column AS statement 00:02:00 Section 09: Filtering Data rows SELECT WHERE Clause - theory 00:04:00 SELECT WHERE Clause - practical 00:07:00 Section 10: Aggregate functions Sum() 00:08:00 Min()-Max() 00:06:00 Section 11: SQL Query statements Order By statement 00:05:00 SELECT TOP clause in SQL 00:04:00 BETWEEN command 00:08:00 IN operator 00:04:00 Wildcard Characters and LIKE 00:05:00 Section 12: SQL Group by statement Section Introduction 00:01:00 Group by - theory8 00:03:00 Group by - practical 00:05:00 HAVING statement 00:04:00 Section 13: JOINS for Multiple table Data Analysis Overview of Joins 00:02:00 What are Joins 00:02:00 Inner join 00:08:00 Left outer join 00:03:00 Right outer join 00:02:00 Full outer join 00:01:00 Union 00:03:00 Cartesian Product with the Cross Join 00:03:00 Query Exercise 00:01:00 Solution for Query Exercise 00:01:00 Section 14: SQL Constraints Section introduction 00:01:00 Check constraint 00:07:00 NOT NULL constraint 00:08:00 UNIQUE constraint 00:05:00 Section 15: Views Creating Views 00:04:00 Reporting with multiple tables 00:03:00 Section 16: Advanced SQL commands Section Introduction 00:01:00 Timestamp 00:04:00 Extract from timestamp 00:03:00 Mathematical scalar functions 00:04:00 String functions 00:05:00 Sub Query 00:03:00 SELECT with calculations 00:06:00 Section 17: SQL Stored procedures Create stored procedure 00:05:00 Stored procedure with parameter 00:04:00 Section 18: Azure Data Studio Visualization Installing SandDance Extension 00:03:00 Visualization Charts 00:05:00 Multiple Table Data Charts 00:06:00 Section 19: Azure Studio SQL for Data Analysis Type Decision for Data Analysis 00:13:00 Data Analysis with Case Statement and String Text 00:09:00 Section 20: Import & Export data Section Introduction 00:01:00 Import Flat File 00:05:00 Import .csv or excel file 00:03:00 Export Data to Excel or any format 00:06:00 Section 21: Backup and Restore Database Section Introduction 00:01:00 Creating Database backup 00:04:00 Restoring Database backup 00:04:00
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