4714 Graduate courses

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

DontGoToDramaSchool - Teaching you the screen-acting techniques of the Hollywood stars. "Making quality, industry relevant drama training accessible to all." Don't waste your time and money going to traditional drama school. We teach you screen-acting not stage, at a time when streaming content is booming while theatres are being demolished. And costing a fraction of the price of traditional drama schools, start your training today. Don't wait for term time to begin.

The demand for coding essential skills is skyrocketing. The average salary for a web developer in the United Kingdom is £65,824 per year. And that number is only going to go up as more and more businesses move their operations online. If you want to get ahead in the tech industry, you need to learn how to code. This Coding Essentials - Javascript, ASP. Net, C# - Bonus HTML course will teach you the crucial skills you need to become a web developer. You'll learn HTML, JavaScript, C#, and ASP.NET. You'll also learn how to build interactive web applications and use JavaScript to add dynamic functionality to your pages. In this Coding Essentials course, we start with an introduction to HTML, where you'll learn the basics, intermediate to advanced level topics, and explore advanced HTML techniques. Next, we dive into JavaScript, a powerful scripting language used for web development. From the fundamentals to conditional statements, control flow, functions, and error handling, you'll gain a solid understanding of JavaScript and its role in creating dynamic web pages. But that's not all! We also dive into the world of C#, a versatile and widely-used programming language. Starting with the basics, you'll progress through operators, statements, control flow, and debugging techniques. You'll also master object-oriented programming (OOPs) concepts, such as class encapsulation, inheritance, polymorphism, abstract classes, and interfaces. Our comprehensive curriculum concludes with exploring error-handling techniques in C#, ensuring you can create robust and reliable applications. Join us on this exciting coding adventure, where our experienced and expert instructors will guide you every step of the way. Don't miss this opportunity to unlock a world of possibilities and take your coding skills to new heights. Enrol in our Coding Essentials course today and unleash your coding potential! Learning Outcomes: Upon completion of the Coding Essentials course, you should be able to: Master the fundamentals of HTML for creating web pages. Gain intermediate and advanced HTML skills for enhanced web development. Understand the core concepts and syntax of JavaScript. Learn to use JavaScript to create dynamic and interactive web content. Develop proficiency in JavaScript operators and conditional statements. Explore control flow statements and error handling in JavaScript. Acquire a solid foundation in C# programming language. Learn C# operators, statements, and control flow techniques. Understand object-oriented programming (OOPs) concepts in C#. Apply C# error handling techniques for creating robust applications. Who is this course for? This Coding Essentials course is perfect for: Beginners who want to learn coding essentials from scratch. Individuals interested in web development and programming languages. Professionals seeking to enhance their coding skills and expand career opportunities. Students or graduates looking to add valuable coding skills to their resumes. Anyone with a passion for coding and a desire to create innovative applications. Career Path  Our Coding Essentials course will help you to pursue a range of career paths, such as: Web Developer: £25,000 - £50,000 per year. Software Engineer: £30,000 - £60,000 per year. Full Stack Developer: £35,000 - £70,000 per year. Front-end Developer: £25,000 - £55,000 per year. Back-end Developer: £30,000 - £60,000 per year. C# Developer: £35,000 - £70,000 per year. JavaScript Developer: £30,000 - £60,000 per year. Certification After studying the course materials of the Coding Essentials - Javascript, ASP. Net, C# - Bonus HTML 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. Prerequisites This Coding Essentials - Javascript, ASP. Net, C# - Bonus HTML does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Coding Essentials - Javascript, ASP. Net, C# - Bonus HTML 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. Course Curriculum Introduction Introduction 00:03:00 How to Get Course requirements 00:02:00 Getting Started on Windows, Linux or Mac 00:02:00 How to ask Great Questions 00:01:00 FAQ's 00:01:00 HTML Introduction HTML 00:05:00 Choosing Code Editor 00:06:00 Installing Code Editor (Sublime Text) 00:04:00 Overview of a Webpage 00:05:00 Structure of a Full HTML Webpage 00:07:00 First Hello World! Webpage 00:09:00 HTML Basic Heading tag 00:09:00 Paragraph 00:08:00 Formatting Text 00:12:00 List Items Unordered 00:05:00 List Items Ordered 00:04:00 Classes 00:09:00 IDs 00:06:00 Comments 00:04:00 HTML Intermediate Images 00:12:00 Forms 00:05:00 Marquee 00:06:00 Text area 00:06:00 Tables 00:06:00 Links 00:07:00 Navbar - Menu 00:04:00 HTML Entities 00:05:00 Div tag 00:06:00 Google Maps 00:07:00 HTML Advanced HTML Audio 00:07:00 HTML Video 00:05:00 Canvas 00:06:00 Iframes 00:05:00 Input Types 00:04:00 Input Attributes 00:06:00 Registration Form 00:04:00 Contact Us Form 00:10:00 Coding Exercise 00:01:00 Solution for Coding Exercise 00:02:00 JavaScript Introduction What is JavaScript 00:09:00 Hello World Program 00:14:00 Getting Output 00:11:00 Internal JavaScript 00:13:00 External JavaScript 00:09:00 Inline JavaScript 00:04:00 Async and defer 00:06:00 JavaScript Basics Variables 00:13:00 Data Types 00:10:00 Numbers 00:06:00 Strings 00:06:00 String Formatting 00:05:00 JavaScript Operators Arithmetic operators 00:07:00 Assignment operators 00:03:00 Comparison operators 00:06:00 Logical operators 00:08:00 JavaScript Conditional Statements If-else statement 00:05:00 If-else-if statement 00:04:00 JavaScript Control Flow Statements While loop 00:09:00 Do-while loop 00:03:00 For loop 00:08:00 Solution for Coding Exercise 00:02:00 JavaScript Functions Creating a Function 00:07:00 Function Call() 00:07:00 Function with parameters 00:05:00 JavaScript Error Handling Try-catch 00:05:00 Try-catch-finally 00:17:00 JavaScript Client-Side Validations On Submit Validation 00:09:00 Input Numeric Validation 00:12:00 C# Introduction Introduction to CSharp 00:07:00 CSharp vs NET 00:04:00 What is CLR 00:05:00 Architecture of NET Application 00:09:00 Getting Visual Studio 00:07:00 First CSharp Hello World Application 00:16:00 First CSharp Core Hello World Program 00:18:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 C# Basic Variables 00:24:00 CSharp Identifiers 00:08:00 Data Types 00:08:00 Type Casting 00:14:00 User Inputs 00:10:00 Comments 00:03:00 C# Operators Arithmetic Operators 00:09:00 Assignment Operators 00:03:00 Comparison Operators 00:03:00 Logical Operators 00:03:00 Strings 00:10:00 String Properties 00:08:00 Booleans 00:06:00 Assessment Test 00:01:00 Solution for Assessment Test 00:01:00 C# Statements If else Conditions and Statements 00:12:00 Switch-Case Statements 00:09:00 C# Control Flow statements While Loop Statement 00:07:00 Do-While Statement 00:03:00 For Loop Statement 00:07:00 Foreach Statement 00:06:00 Break and Continue 00:03:00 C# Built-in coding Arrays 00:13:00 Loop Through Arrays 00:10:00 Lists 00:07:00 SystemIO Namespace 00:03:00 Datetime 00:10:00 TimeSpan 00:06:00 C# Debugging techniques Debugging Tools in Visual Studio 00:13:00 Call Stack Window 00:04:00 Locals and Autos 00:04:00 C# Object-oriented programming [OOPs] Introduction to Class 00:03:00 Create a Class 00:15:00 Object Initializers 00:16:00 Parameters 00:12:00 Access Modifiers(theory) 00:13:00 C# Methods Introduction to methods 00:06:00 Create a method 00:16:00 Method with parameters 00:09:00 Method default and multiple parameters 00:09:00 Method return keyword 00:07:00 Method Over loading 00:08:00 Assessment Test 00:01:00 Solution for Assessment Test 00:02:00 C# Class Encapsulation Introduction to OOPs 00:04:00 Classes and Objects 00:11:00 Class Members 00:10:00 Class Constructors 00:14:00 Access Modifiers 00:11:00 Properties Get Set 00:06:00 Encapsulation 00:03:00 C# Inheritance and Polymorphism Intro Inheritance and Polymorphism 00:03:00 Inheritance 00:12:00 Polymorphism 00:13:00 Assessment Test 00:02:00 Solution for Assessment Test 00:03:00 C# Abstract and Interfaces Introduction 00:02:00 Abstraction 00:07:00 Interfaces 00:07:00 Enums 00:05:00 C# Error Handling Techniques Try Catch 00:10:00 Custom message on Errors 00:05:00 Finally 00:06:00 Throw keyword 00:09:00 Coding Exercise 00:02:00

This course aims to prepare individuals for the AWS Certified Solutions Architect Associate exam. It covers essential AWS services, cloud architecture design, deployment strategies, and best practices for managing various AWS components. Learning Outcomes: Understand the fundamental concepts of AWS Cloud Services and their application in real-world scenarios. Design and implement AWS Storage and Virtual Private Cloud (VPC) solutions. Learn how to design, implement, and manage Compute Services effectively. Master Identity and Access Management (IAM) and its best practices for secure access control. Explore Auto Scaling Solutions and Virtual Network Services to optimize AWS infrastructure. Gain proficiency in deploying applications and databases on AWS. Discover additional AWS services and their integration for comprehensive cloud solutions. Develop insights into achieving operational excellence with AWS services. Why buy this AWS Certified Solutions Architect Associate Preparation? 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 AWS Certified Solutions Architect Associate Preparation 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 AWS Certified Solutions Architect Associate Preparation 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 AWS Certified Solutions Architect Associate Preparation does not require you to have any prior qualifications or experience. You can just enrol and start learning.This AWS Certified Solutions Architect Associate Preparation 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 AWS Certified Solutions Architect Associate Preparation is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Section 01: Introduction Introduction 00:03:00 Section 02: Exam Tips and Tricks What is AWS? 00:02:00 Why use AWS? 00:03:00 How to Get Started with AWS 00:04:00 AWS Certifications 00:04:00 Preparation Resources 00:02:00 Benefits of Certification 00:02:00 AWS CSA-A Overview 00:04:00 What's New on the 2020 Updated Exam? 00:03:00 AWS CSA-A Exam Objectives 00:06:00 The Four Key Areas (Compute, Networking, Storage, and Databases) 00:04:00 Master the Knowledge Areas 00:02:00 Use the System 00:05:00 Take Notes 00:03:00 Be Mentally and Physically Prepared 00:04:00 Take the Exam 00:04:00 Section 03: AWS Cloud Services Overview Cloud Computing Defined 00:08:00 Benefits of Cloud Computing 00:10:00 Cloud Computing Models 00:07:00 History 00:07:00 Platform 00:06:00 Services, Part 1 00:10:00 Services, Part 2 00:08:00 Security and Compliance 00:07:00 Regions and Availability 00:06:00 Section 04: AWS Storage Design Storage Services 00:07:00 S3 Storage Class 00:07:00 S3 Terminology 00:09:00 S3 Advanced Features 00:08:00 Creating S3 Buckets Lab 00:08:00 S3 Bucket Properties 00:08:00 S3 Managing Objects Lab 00:11:00 Glacier 00:07:00 Setting up a Glacier Vault Lab 00:08:00 S3 and Tape Gateway 00:06:00 S3 Enhanced Features 00:08:00 Elastic Block Store (EBS) 00:08:00 Creating EBS Volumes Lab 00:07:00 Elastic File System (EFS) 00:07:00 Creating an EFS File System Lab 00:07:00 EFS and PrivateLink 00:03:00 Intro to Amazon FSx 00:06:00 Hands-on with FSx 00:06:00 Integrating on-Premises Storage 00:07:00 Storage Access Security Lab 00:10:00 Storage Performance 00:08:00 Section 05: Virtual Private Cloud (VPC) Virtual Private Cloud (VPC) Overview 00:10:00 Creating a VPC Lab 00:11:00 Configuring DHCP Options Lab 00:04:00 Elastic IP Addresses 00:07:00 Elastic Network Interfaces (ENIs) 00:05:00 Endpoints 00:07:00 VPC Peering 00:08:00 Creating a VPC Peering Connection Lab 00:10:00 Security Groups Overview 00:07:00 Network Address Translation (NAT) 00:11:00 Gateways (VPGs and CGWs) 00:08:00 VPN Configuration Option 00:04:00 Section 06: Compute Services Design EC2 Overview 00:11:00 EC2 Instance Types 00:11:00 EC2 Pricing 00:13:00 EBS and EC2 00:05:00 Section 07: Compute Services Implementation Launching an EC2 Linux Instance Lab 00:13:00 Configuring an EC2 Linux Instance Lab 00:08:00 Setting up an EC2 Windows Instance Lab 00:12:00 Shared Tenancy 00:05:00 Dedicated Hosts 00:08:00 Dedicated Instances 00:06:00 AMI Virtualization 00:12:00 Section 08: Compute Services Management Instance Management 00:09:00 Connecting to Instances Lab 00:09:00 Working with Security Groups 00:10:00 Working with Security Groups Lab 00:10:00 Advanced EC2 Management 00:06:00 AWS Batch 00:06:00 Elastic Container Service (ECS) 00:08:00 Elastic Beanstalk Environment 00:11:00 Section 09: Identity and Access Management (IAM) Identity and Access Management (IAM) Overview 00:07:00 Principals 00:10:00 Root User 00:06:00 Authentication 00:06:00 Authorization Policies 00:13:00 Multi-Factor Authentication 00:08:00 Key Rotation 00:10:00 Multiple Permissions 00:06:00 AWS Compliance Program 00:07:00 AWS Security Hub 00:06:00 Shared Responsibility Models 00:06:00 Section 10: IAM Best Practices User Accounts 00:11:00 Password Policies 00:09:00 Credential Rotation 00:06:00 Principle of Least Privilege 00:05:00 IAM Roles 00:08:00 Policy Conditions 00:08:00 CloudTrail 00:12:00 Section 11: Auto Scaling Solutions Auto Scaling Overview 00:06:00 Auto Scaling Groups 00:04:00 Termination Policies 00:07:00 Auto Scaling Configuration Lab 00:13:00 Launch Methods 00:04:00 Load Balancer Concepts 00:08:00 Elastic Load Balancing (ELB) 00:10:00 Section 12: Virtual Network Services DNS 00:14:00 Configuring DNS Lab 00:07:00 Configuring Route 53 Lab 00:13:00 Configuring ACLs and NACLs Lab 00:09:00 Flow Logs 00:07:00 Section 13: AWS Application Deployment Application and Deployment Services 00:04:00 Lambda 00:06:00 API Gateway 00:09:00 Kinesis 00:06:00 Kinesis Data Streams and Firehose 00:06:00 Kinesis Data Analytics 00:04:00 Reference Architectures 00:06:00 CloudFront 00:10:00 Web Application Firewall (WAF) 00:09:00 Simple Queue Service (SQS) 00:10:00 Simple Notification Service (SNS) 00:08:00 Simple Workflow (SWF) 00:07:00 Step Functions 00:05:00 OpsWorks 00:08:00 Cognito 00:04:00 Elastic MapReduce (EMR) 00:05:00 CloudFormation 00:10:00 CloudFormation Properties 00:03:00 CloudWatch 00:06:00 Trusted Advisor 00:07:00 Organizations 00:09:00 Section 14: AWS Database Design Database Types 00:08:00 Relational Databases 00:08:00 Database Hosting Methods 00:05:00 High Availability Solutions 00:06:00 Scalability Solutions 00:06:00 Database Security 00:08:00 Aurora 00:06:00 Redshift 00:11:00 DynamoDB 00:10:00 Section 15: Database Deployment DynamoDB Tables Lab 00:08:00 MySQL Lab 00:13:00 Configuration Lab 00:13:00 Backups Lab 00:04:00 Restore Lab 00:04:00 Snapshot Lab 00:08:00 Monitoring Lab 00:06:00 Section 16: Additional AWS Services Media Content Delivery 00:13:00 Desktop and Appstreaming 00:06:00 ElastiCache 00:05:00 Security Services Lab 00:12:00 Analytics Engines 00:11:00 Development Operations (DevOps) 00:12:00 AWS Solutions 00:05:00 AWS Transit Gateway 00:03:00 AWS Backup 00:04:00 AWS Cost Explorer 00:04:00 Section 17: Operational Excellence with AWS The Operational Excellence Process 00:08:00 Widget Makers Scenario 00:06:00 Resilient Design 00:08:00 Resilient Design Scenario 00:05:00 Performant Design 00:09:00 Performant Design Scenario 00:06:00 Secure Design 00:08:00 Secure Design Scenario 00:05:00 Cost Optimization 00:07:00 Cost Optimization Scenario 00:05:00 General Best Practices 00:07:00

Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents and interests with our special Microsoft Power BI Masterclass 2021 Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today's workplaces. The Microsoft Power BI Masterclass 2021 Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Microsoft Power BI Masterclass 2021 Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Microsoft Power BI Masterclass 2021 Course, like every one of Study Hub's courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At StudyHub, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from StudyHub, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Microsoft Power BI Masterclass 2021? 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 Microsoft Power BI Masterclass 2021 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 Microsoft Power BI Masterclass 2021 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 Microsoft Power BI Masterclass 2021 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Microsoft Power BI Masterclass 2021 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 Microsoft Power BI Masterclass 2021 is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Section 01: Introduction Welcome! 00:01:00 What is Power BI? 00:03:00 Download & Installing Power BI Desktop 00:04:00 Getting to know the interface 00:03:00 Mini Project: Transform Data 00:07:00 Mini Project: Visualize Data 00:05:00 Mini Project: Creating a Data Model 00:07:00 Course Outline: What will you learn in this course? 00:05:00 How to learn best with this course? 00:03:00 Section 02: Preparing our Project Creating our initial project file 00:04:00 Working with the attached project files 00:04:00 Section 03: Data Transformation - The Query Editor Exploring the Query Editor 00:06:00 Connecting to our data source 00:07:00 Editing rows 00:08:00 Changing data types 00:08:00 Replacing values 00:03:00 Close & Apply 00:03:00 Connecting to a csv file 00:03:00 Connecting to a web page 00:05:00 Extracting characters 00:06:00 Splitting & merging columns 00:09:00 Creating conditional columns 00:06:00 Creating columns from examples 00:09:00 Merging Queries 00:17:00 Pivoting & Unpivoting 00:06:00 Appending Queries 00:08:00 Practice & Solution: Population table 00:15:00 The Fact-Dimension-Model 00:09:00 Practice: Load the dimension table 00:04:00 Organizing our queries in groups 00:03:00 Entering data manually 00:05:00 Creating an index column 00:03:00 Workflow & more transformations 00:05:00 Module summary 00:05:00 Exercise 1 - Instruction 00:02:00 Exercise Solution 00:11:00 Section 04: Data Transformation - Advanced Advanced Editor - Best practices 00:09:00 Performance: References vs. Duplicating 00:10:00 Performance: Enable / Disable Load & Report Refresh 00:05:00 Group by 00:05:00 Mathematical Operations 00:05:00 Run R Script 00:15:00 Using Parameters to dynamically transform data 00:06:00 M formula language: Basics 00:07:00 M formula language: Values, Lists & Tables 00:14:00 M formula language: Functions 00:13:00 M formula language: More functions & steps 00:05:00 Exercise 2 - Instructions 00:01:00 Exercise 2 - solution 00:05:00 Section 05: Creating a Data Model Understanding the relationship 00:05:00 Create & edit relationships 00:06:00 One-to-many & one-to-one relationship 00:06:00 Many-to-many (m:n) relationship 00:08:00 Cross filter direction 00:06:00 Activate & deactivate relationships 00:06:00 Model summary 00:03:00 Exercise 3 Create Model 00:02:00 Exercise 3 Solution 00:02:00 Section 06: Data Visualization Our first visual 00:08:00 The format tab 00:12:00 Understanding tables 00:10:00 Conditional formatting 00:09:00 The Pie Chart 00:06:00 All about the filter visual 00:13:00 The filter pane for developers 00:09:00 Cross filtering & edit interactions 00:04:00 Syncing slicers across pages 00:07:00 Creating drill downs 00:08:00 Creating drill throughs 00:07:00 The tree map visual 00:07:00 The decomposition tree 00:05:00 Understanding the matrix visual 00:05:00 Editing pages 00:07:00 Buttons & Actions 00:09:00 Bookmarks to customize your report 00:10:00 Analytics and Forecasts with line charts 00:10:00 Working with custom visuals 00:07:00 Get data using R Script & R Script visual 00:08:00 Asking questions - Q&A visual 00:04:00 Wrap up - data visualization 00:08:00 Section 07: Power BI & Python Python in Power BI - Plan of attack 00:03:00 Setting up Python for Power BI 00:03:00 Transforming data using Python 00:11:00 Creating visualizations using Python 00:08:00 Violin plots, pair plots & ridge plots using Python 00:15:00 Machine learning (BayesTextAnalyzer) using Python 00:00:00 Performance & Troubleshooting 00:03:00 Section 08: Storytelling with Data Introduction 00:01:00 Show Empathy & Identify the Requirement 00:03:00 Finding the Most Suitable KPI's 00:02:00 Choose an Effective Visualization 00:04:00 Make Use of Natural Reading Pattern 00:03:00 Tell a Story Using Visual Cues 00:05:00 Avoid Chaos & Group Information 00:02:00 Warp Up - Storytelling with Data 00:02:00 Section 09: DAX - The Essentials Introduction 00:03:00 The project data 00:04:00 Measures vs. Calculated Columns 00:15:00 Automatically creating a date table in DAX 00:08:00 CALENDAR 00:05:00 Creating a complete date table with features 00:04:00 Creating key measure table 00:03:00 Aggregation functions 00:06:00 The different versions of COUNT 00:14:00 SUMX - Row based calculations 00:09:00 Section 10: DAX - The CALCULATE function CALCULATE - The basics 00:11:00 Changing the context with FILTER 00:07:00 ALL 00:08:00 ALL SELECTED 00:03:00 ALL EXCEPT 00:07:00 Section 11: Power BI Service - Power BI Cloud How to go on now? 00:03:00 Power BI Pro vs Premium & Signing up 00:04:00 Exploring the interface 00:04:00 Discovering your workspace 00:03:00 Connecting Power BI Desktop & Cloud 00:04:00 Understanding datasets & reports 00:03:00 Working on reports 00:04:00 Updating reports from Power BI Desktop 00:04:00 Creating and working with workspaces 00:07:00 Installing & using a data gateway 00:13:00 Get Quick Insights 00:03:00 Creating dashboards 00:04:00 Sharing our results through Apps 00:10:00 Power BI Mobile App 00:05:00 Creating the layout for the Mobile App 00:04:00 Wrap up - Power BI Cloud 00:07:00 Section 12: Row-Level Security Introduction 00:03:00 Creating a Row-Level Security 00:05:00 Row-Level Security in the Cloud 00:04:00 Row-Level Security & Data Model 00:05:00 Dynamic Row-Level Security 00:07:00 Dynamic Many-to-Many RLS 00:04:00 Hierarchical Row-Level Security 00:13:00 Section 13: More data sources JSON & REST API 00:10:00 Setting up a local MySQL database 00:14:00 Connecting to a MySQL database in Power BI 00:05:00 Connecting to a SQL database (PostgreSQL) 00:05:00 Section 14: Next steps to improve & stay up to date Congratulations & next steps 00:06:00 The End 00:01:00 Resources Resources - Microsoft Power BI Masterclass 2021 00:00:00 Assignment Assignment - Microsoft Power BI 00:00:00

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? 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 Complete Python Machine Learning & Data Science Fundamentals 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 Complete Python Machine Learning & Data Science Fundamentals 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 Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals 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 Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step