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Explore our Car Mechanic & Repair Level 3 Diploma Course! Master essential skills like vehicle maintenance, engine care, and electrical diagnostics. Perfect for aspiring mechanics and automotive enthusiasts. Enrol now for hands-on training and expert guidance!

Are you embarking on the journey of mastering data analytics and visualisation in the UK? The 'Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7' is your beacon. Positioned to illuminate the intricate realm of Power BI, this course offers a comprehensive look into the foundational aspects and the advanced features that make Microsoft's tool a standout. With sections meticulously designed ranging from the fundamentals, like data transformation, to advanced concepts, such as integrating Power BI with Python and storytelling with data, this course ensures learners grasp the complete spectrum. With the rising emphasis on data analytics in today's business world, this course acquaints you with Power BI's prowess. It prepares you for the sought-after Microsoft Power BI certification in the UK. Learning Outcomes Comprehend the fundamental aspects of Power BI, from initiating a project to understanding the user interface. Develop proficiency in advanced data transformation techniques and data model creation. Integrate Python with Power BI and harness the benefits of both for enhanced data analytics. Master the art of 'Storytelling with Data' to deliver impactful presentations and reports. Understand and implement Row-Level Security and harness Power BI Cloud services efficiently. Why choose this Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 for? Individuals keen on obtaining the Microsoft power bi certification UK. Analysts and data professionals aspiring to enhance their data visualisation skills. Business professionals wanting to leverage Power BI for insightful business decision-making. Tech enthusiasts aiming to amalgamate programming (Python) with data analytics. Those seeking to stay updated with the latest trends in Power BI and its evolving capabilities. Career path Data Analyst: Average Salary £30,000 - £40,000 Annually Business Intelligence Developer: Average Salary £35,000 - £45,000 Annually Power BI Developer: Average Salary £40,000 - £50,000 Annually Data Visualisation Specialist: Average Salary £32,000 - £42,000 Annually Business Intelligence Manager: Average Salary £45,000 - £55,000 Annually Data Strategy Consultant: Average Salary £50,000 - £60,000 Annually Prerequisites This Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This course 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. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. 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 00:03:00 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 - Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 00:00:00 Assignment Assignment - Advanced Diploma in Microsoft Power BI 2021 at QLS Level 7 04:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Join our Microsoft Power BI Masterclass course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Microsoft Power BI Masterclass course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Microsoft Power BI Masterclass course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! You will Learn The Following Things: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Microsoft Power BI Masterclass. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-to-one support from a dedicated tutor throughout your course. Study online - whenever and wherever you want. Instant Digital/ PDF certificate 100% money back guarantee 12 months access Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement After completing the Microsoft Power BI Masterclass course, you will receive your CPD-accredited Digital/PDF Certificate for £5.99. To get the hardcopy certificate for £12.99, you must also pay the shipping charge of just £3.99 (UK) and £10.99 (International). Who Is This Course for? This Microsoft Power BI Masterclass is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements There is no prerequisite to enrol in this course. You don't need any educational qualification or experience to enrol in the Microsoft Power BI Masterclass course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Microsoft Power BI Masterclass Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. 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 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

Dive into the dazzling realm of gemstones with our Gemology Online Diploma Course, designed to illuminate the science and art behind precious stones from the comfort of your home. Whether you’re fascinated by the sparkle of diamonds or intrigued by the secrets of sapphires, this course provides a deep understanding of gemstone identification, grading, and valuation. You’ll gain expert knowledge of the geological origins, physical properties, and market trends shaping the gem industry today. Ideal for enthusiasts and aspiring gemologists alike, this course blends detailed theory with expert insights to broaden your appreciation and expertise in gemology. All content is delivered through engaging, carefully crafted modules that fit your schedule, ensuring you stay informed and inspired without the need for any on-site attendance. Prepare to add a brilliant new dimension to your skills—minus any fuss or the need to leave your favourite armchair. Key Features Free PDF Certificate CPD Accredited Lifetime Access Instant Access Gemology Course Curriculum: Module 01: Introduction to Gemology Module 02: Formation of Gems Module 03: Gemology & Colour Module 04: Fashioning Module 05: Gem Testing Module 06: Weight and Measurement Module 07: Precious Gemstones Gemology Course Assessment You will immediately be given access to a specifically crafted MCQ test upon completing the Gemology - CPD Accredited course. For each test, the pass mark will be set to 60%. Certificate After successfully completing this Gemology - CPD Accredited course, you will qualify for the CPD Quality Standards (CPD QS) certified certificate from Training Express. CPD 10 CPD hours / points Accredited by The CPD Quality Standards (CPD QS) Who is this course for? The Gemology - CPD Accredited training is ideal for highly motivated individuals or teams who want to enhance their skills and efficiently skilled employees. Requirements There are no formal entry requirements for the gemology course, with enrollment open to anyone! Career path Learn the essential skills and knowledge you need to excel in your professional life with the help & guidance from our Gemology - CPD Accredited training, including: Gemologist Retail associates Lab gemologists Jewelry designers Certificates Digital certificate Digital certificate - Included Hard copy certificate Hard copy certificate - Included Shipping cost: £3.99

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Duration 5 Days 30 CPD hours This course is intended for This course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of the fundamentals of coding and basics of C++ and object-oriented programming concepts. This course is for Non-Developers, or anyone who wants to have a basic understanding of and learn how to code C++ applications and syntax Overview Companies are constantly challenged to keep their applications, development projects, products, services (and programmers!) up to speed with the latest industry tools, skills, technologies and practices to stay ahead in the ever-shifting markets that make up today's fiercely competitive business landscape. The need for application, web and mobile developers and coders is seemingly endless as technologies regularly change and grow to meet the modern needs of demanding industries and clients. C++ and Programming Basics for Non-Programmers is a five-day, basic-level training course geared for IT candidates who have little or no prior experience in computer programming. Throughout this gentle introduction to programming and C++, students will learn to create applications and libraries using C++ using best practices and sound OO development techniques for writing object-oriented programs in C++. Special emphasis is placed on object-oriented concepts and best practices throughout the training. Fundamentals of the Program Development Cycle Computer Architecture The Notion of Algorithms Source Code vs. Machine Code Compile-Time vs. Run-Time Software Program Architecture Standalone Client/Server Distributed Web-Enabled IDE (Interactive Development Environment) Concepts Looping Constructs Counter-Controlled Repetition Sentinel-Controlled Repetition Nested Control Constructs break and continue Statements Structured Programming Best Practices Writing Methods (Functions) Static vs. Dynamic Allocation Declaring Methods Declaring Methods with Multiple Parameters Method-Call Stack Scope of Declarations Argument Promotion and Casting Designing Methods for Reusability Method Overloading Arrays Purpose of Arrays Declaring and Instantiating Arrays Passing Arrays to Methods Multidimensional Arrays Variable-Length Argument Lists Using Command-Line Arguments Using Environment Variables Deeper Into Classes and Objects Controlling Access to Class Members Referencing the Current Object Using this Overloading Constructors Default and No-Argument Constructors Composition of Classes Garbage Collection and Destructors The finalize Method Static Class Members Defining Classes Using Inheritance Application Development Fundamentals Structure of a C++ Program Memory Concepts Fundamental Data Type Declarations Fundamental I/O Concepts Fundamental Operators Arithmetic Operators Logical Operators Precedence and Associativity Building and Deploying a C++ Program Superclasses and Subclasses Advantages of Using Inheritance protected Class Members Constructors in Subclasses Increasing Convenience by Using Polymorphism Purpose of Polymorphic Behavior The Concept of a Signature Abstract Classes and Methods final Methods and Classes Purpose of Interfaces Using and Creating Interfaces Common Interfaces of the C++ API Files and Streams Concept of a Stream Class File Sequential Access Object Serialization to/from Sequential Access Files Fundamental Searching and Sorting Introduction to Searching Algorithms Linear Search Binary Search Introduction to Sorting Algorithms Selection Sort Insertion Sort Merge Sort Fundamental Data Structures Dynamic Memory Allocation Linked Lists Stacks Queues Trees Exception Handling Types of Exceptions Exception Handling Overview Introduction to Classes and Objects Classes, Objects and Methods Object Instances Declaring and Instantiating a C++ Object Declaring Methods set and get Methods Initiating Objects with Constructors Primitive Types vs. Reference Types Flow Control Conditional Constructs Exception Class Hierarchy Extending Exception Classes When to Throw or Assert Exceptions Formatted Output printf Syntax Conversion Characters Specifying Field Width and Precision Using Flags to Alter Appearance Printing Literals and Escape Sequences Formatting Output with Class Formatter Strings, Characters and Regular Expressions Fundamentals of Characters and Strings String Class String Operations StringBuilder Class Character Class StringTokenizer Class Regular Expressions Regular Expression Syntax Pattern Class Matcher Class Fundamental GUI Programming Concepts Overview of Swing Components Displaying Text and Graphics in a Window Event Handling with Nested Classes GUI Event Types and Listener Interfaces Mouse Event Handling Layout Managers Additional course details: Nexus Humans C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) 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 C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This section specifies the primary and secondary target audiences of this course by job roles and notes the relevance to each job role. Collaboration Engineers and Administration Primary audiences: Collaboration engineers involved in the design, implementation, and troubleshooting of Cisco collaboration core technologies. Secondary audiences: Administration involved in support and troubleshooting of Cisco collaboration technologies. Overview Upon completing this course, you will be able to meet these objectives: Describe the Cisco Expressway - C features and functionality within the collaboration architecture Configure and troubleshoot Cisco Unified Communications Manager and Cisco expressway Series integration Describe the Cisco Expressway - C additional features Configure and troubleshoot Cisco Collaboration solutions for B2B calls Describe how to secure B2B communication with Cisco Expressway Series Describe the MRA feature Describe the Cisco Expressway MRA security and integration options, including integration with Cisco Unity Connection and Cisco IM&P Configure Cisco Webex Hybrid Services This course provides students knowledge about Cisco Expressway Series solutions, such as B2B calls, Cisco Mobile and Remote Access for remote workers, authentication options, and additional Cisco Expressway Series features. Configuring and Troubleshooting the Cisco Expressway Series Cisco Expressway Series Architecture Discovery 1: Deploy virtualized Cisco Expressway Discovery 2: Perform the initial Cisco Expressway series configuration Describe SIP and H.323 in the Cisco Expressway series Describe interworking in the Cisco Expressway series Discovery 3: Register endpoints on Cisco Expressway series Zones Digital string manipulation Search rules Transforms Discovery 4: Call search history and registrations Troubleshoot call processing on Cisco Expressway series Discovery 5: Troubleshooting tools Backup and restore Rerference Configuring Cisco Expressway Additional Freatures Describe bandwidth management Hardening local endpoint registrations Discovery 6: Configure Cisco Expressway series bandwidth management and registration restrictions Discovery 7: Troubleshoot Cisco Expressway series endpoint registration and local dial plan Describe Cisco Expressway security and clustering features Discovery 8: Configure Cisco Expressway series security features Configuring and Troubleshooting Cisco Unified Communications Manager and Cisco Expressway Series Cisco unified communications manager and Cisco Expressway-C integration overview Dian plan overview Call policy Discovery 9: Configure Cisco unified communications manager to connect with Cisco Expressway-C Troubleshooting options for Cisco unified communications manager and Cisco Expressway-C intergration Discovery 10: Troubleshoot Cisco unified communications manager and Cisco Expressway series integration Discovery 11: Configure and troubleshoot Cisco unified communications manager and Cisco Expressway series integration (practice activity) References Configuring and Troubleshooting Cisco Collaboration Solutions for Bussiness-to-Bussiness Describe supported services for B2B collaboration Describe prerequisites for business to business collaboration Call flow including Cisco unified communications manager endpoints Network address translation in a collaboration environment Discovery 12: Implement a B2B Cisco collaboration solution Cisco Expressway series B2B call troubleshooting Discovery 13: Troubleshoot B2B calls on the Cisco Expressway series References Discovery 14: Troubleshoot B2B calls on the Cisco Expressway series (practice activity) Securing Business-Business Communication Firewall Traversal Secure media Secure media between Cisco unified communications manager and Cisco Expressway series Toll fraud prevention Discovery 15: Secure a B2B Cisco collaboration communication Refrences Configuring and Troubleshooting Mobile and Remote Access Describe prerequisites for mobile and remote access Describe service discovery Explore Expressway settings for MRA Certificates HTTP proxy Cisco jabber registration procedure Cisco jabber registration procedure in Hybrid deployment Cisco jabber configuration file Discovery 16: Configure MRA on the Cisco Expressway series MRA troubleshooting Discovery 17: Troubleshoot MRA on the Cisco Expressway series Integrating and Securing Mobile and Remote Access Secure Cisco unified communications integration Cisco unity connection integration Cisco MRA access control options Additional Cisco MRA features Discovery 18: Configure MRA with additional application integrations References Configuring Cisco Webex Hybrid Services Cisco Webex teams Describe Cisco Webex control hub Describe Cisco Webhex hybrid media services Describe Cisco Expressway requirements for using hybrid call service connect Explore Cisco Expressway requirements for using hybrid call service connect Describe Cisco Webex video mesh Discovery 19: Prepare for Cisco Webex teams integration Discovery 20: Configure Cisco Webex hybrid services Additional course details: Nexus Humans Cisco Implementing Cisco Collaboration Cloud and Edge Solutions v1.0 (CLCEI) 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 Cisco Implementing Cisco Collaboration Cloud and Edge Solutions v1.0 (CLCEI) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for The audience for this course includes enterprise-level messaging administrators on Exchange Server. IT generalists and helpdesk professionals who want to learn about Exchange Server may also take this course. Students taking this course are expected to have at least two years of experience working in the IT field-typically in the areas of Windows Server administration, network administration, helpdesk, or system administration. They are also expected to have some experience with Exchange Server concepts but previous experience managing Exchange Server is not a requirement. Overview After completing this course, students will be able to: Deploy Exchange Server. Plan and configure storage for Exchange Server. Create and manage various recipient objects in Exchange Server. Perform recipient management and Exchange server management tasks by using Exchange Server cmdlets. Deploy Client Access services in Exchange Server. Manage high availability in Exchange Server. Implement disaster recovery for Exchange Server. Configure and manage message transport in Exchange Server. Configure message security in Exchange Server. Monitor and troubleshoot Exchange Server. Configure Exchange Server role-based access control permissions and configure audit logging for both administrators and users. Implement and manage integration with Exchange Online. This course teaches IT professionals how to administer and support Exchange Server. The course covers how install and configure Exchange Server. It also covers how to manage mail recipients and public folders, including how to perform bulk operations by using Exchange Management Shell. In addition, the course covers how to manage client connectivity, message transport and hygiene, and highly available Exchange Server deployments. It also covers how to implement disaster recovery solutions. Finally, the course covers how to maintain and monitor an Exchange Server deployment and how to administer Exchange Online in a Office 365 deployment. Deploying Microsoft Exchange Server 2016 Overview of Exchange Server Exchange Server architecture Requirements for Exchange Server Deploying Exchange Server Exchange Server Exchange Server Management Tools Lab : Deploying Exchange Server Managing Exchange Server 2016 storage Exchange Server mailbox databases Exchange Server storage Configuring Exchange Server mailbox databases and storage Lab : Configuring Exchange Server storage Managing recipient objects Managing user mailboxes Managing other types of mailboxes Managing other recipients objects Configuring policies and address lists Lab : Managing recipient objects Lab : Configuring address lists and policies Managing recipients and Exchange servers by using Exchange Server cmdlets Overview of the Exchange Management Shell Managing Exchange Servers by using Exchange Management Shell cmdlets Managing Exchange servers by using scripts Lab : Managing Exchange Server and recipient objects by using Exchange Management Shell Implementing client connectivity Configuring client access services Managing client access services Client connectivity in Exchange Server Configuring Outlook on the web Configuring mobile messaging Lab : Configuring client access services Lab : Deploying and configuring client access services on Exchange Server Managing high availability in Exchange Server High availability on Exchange Server Configuring highly available mailbox databases Configuring high availability of Client Access services Lab : Implementing DAGs Lab : Implementing and testing high availability Implementing disaster recovery for Exchange Server Implementing Exchange Server backup Implementing Exchange Server recovery Lab : Backing up Exchange Server data Lab : Restoring Exchange Server data Configuring and managing message transport Overview of message transport Configuring message transport Managing transport rules Lab : Configuring and managing message transport Configuring message security Deploying and managing an Edge Transport server for message security Implementing an antivirus solution for Exchange Server Implementing an antispam solution for Exchange Server Lab : Configuring message security in Exchange Server Monitoring and troubleshooting Exchange Server Monitoring Exchange Server Troubleshooting Exchange Server Lab : Monitoring and troubleshooting Exchange Server Securing and maintaining Exchange Server Securing Exchange Server by using RBAC Configuring audit logging in Exchange Server Maintaining Exchange Server Lab : Securing and maintaining Exchange Server Implementing and managing Exchange Online deployments Overview of Exchange Online and Office 365 Managing Exchange Online Implementing the migration to Exchange Online Managing a hybrid environment Lab : Managing Exchange Online Additional course details: Nexus Humans 20345-1 Administering Microsoft Exchange Server 2016/2019 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 20345-1 Administering Microsoft Exchange Server 2016/2019 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for Application developers who want to increase their understanding of Spring and Spring Boot with hands-on experience and a focus on fundamentals Overview By the end of the course, you should be able to meet the following objectives: Spring configuration using Java Configuration and Annotations Aspect oriented programming with Spring Testing Spring applications using JUnit 5 Spring Data Access - JDBC, JPA and Spring Data Spring Transaction Management Simplifying application development with Spring Boot Spring Boot auto-configuration, starters and properties Build a simple REST application using Spring Boot, embedded Web Server and fat JARs or classic WARs Implementing REST client applications using RestTemplate and WebClient Spring Security Enable and extend metrics and monitoring capabilities using Spring Boot actuator Utilize Spring Boot enhancements to testing This course offers hands-on experience with the major features of Spring and Spring Boot, which includes configuration, data access, REST, AOP, auto-configuration, actuator, security, and Spring testing framework to build enterprise and microservices applications. On completion, participants will have a foundation for creating enterprise and cloud-ready applications. Introduction to Spring Java configuration and the Spring application context @Configuration and @Bean annotations @Import: working with multiple configuration files Defining bean scopes Launching a Spring Application and obtaining Beans Spring JAVA Configuration: A Deeper Look External properties & Property sources Environment abstraction Using bean profiles Spring Expression Language (SpEL) Annotation-based Dependency Injection Component scanning Autowiring using @Autowired Java configuration versus annotations, mixing. Lifecycle annotations: @PostConstruct and @PreDestroy Stereotypes and meta-annotations Factory Pattern in Spring Using Spring FactoryBeans Advanced Spring: How Does Spring Work Internally? The Spring Bean Lifecycle The BeanFactoryPostProcessor interception point The BeanPostProcessor interception point Spring Bean Proxies @Bean method return types Aspect-oriented programming What problems does AOP solve? Defining pointcut expressions Implementing various types of advice Testing a Spring-based Application Spring and Test-Driven Development Spring 5 integration testing with JUnit 5 Application context caching and the @Dirties Context annotation Profile selection with @Active Profiles Easy test data setup with @Sql Data Accss and JDBC with Spring How Spring integrates with existing data access technologies Data Access Exception hierarchy Spring?s Jdbc Template Database Transactions with Spring Transactions overview Transaction management with Spring Transaction propagation and rollback rules Transactions and integration testing Spring Boot Introduction Introduction to Spring Boot Features Value Proposition of Spring Boot Creating a simple Boot application using Spring Initializer website Spring Boot Dependencies, Auto-configuration, and Runtime Dependency management using Spring Boot starters How auto-configuration works Configuration properties Overriding auto-configuration Using Command Line Runner JPA with Spring and Spring Data Quick introduction to ORM with JPA Benefits of using Spring with JPA JPA configuration in Spring Configuring Spring JPA using Spring Boot Spring Data JPA dynamic repositories Spring MVC Architecture and Overview Introduction to Spring MVC and request processing Controller method signatures Using @Controller, @RestController and @GetMapping annotations Configuring Spring MVC with Spring Boot Spring Boot packaging options, JAR or WAR Rest with Spring MVC An introduction to the REST architectural style Controlling HTTP response codes with @ResponseStatus Implementing REST with Spring MVC, @RequestMapping, @RequestBody and @ResponseBody Spring MVC?s HttpMessageConverters and automatic content negotiation Spring Security What problems does Spring Security solve? Configuring authentication Implementing authorization by intercepting URLs Authorization at the Java method level Understanding the Spring Security filter chain Spring security testing Actuators, Metrics and Health Indicators Exposing Spring Boot Actuator endpoints Custom Metrics Health Indicators Creating custom Health Indicators External monitoring systems Spring Boot Testing Enhancements Spring Boot testing overview Integration testing using @SpringBootTest Web slice testing with MockMvc framework Slices to test different layers of the application Spring Security Oauth (Optional Topic) OAuth 2 Overview Implementing OAuth 2 using Spring Security OAuth Reactive Applications with Spring (Optional Topic) Overview of Reactive Programming concepts Reactive Programming support in Spring Using Spring?s reactive WebClient Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Spring: Core Training 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 VMware Spring: Core Training 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.