18367 Step courses in Nottingham delivered Online

Description Beginners Portuguese Course is designed to teach learners the basic grammar rules, typical and common expressions, and pronunciation techniques

Overview This comprehensive course on Develop Your Career in Finance: Blue Ocean Strategy will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Develop Your Career in Finance: Blue Ocean Strategy comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Develop Your Career in Finance: Blue Ocean Strategy. It is available to all students, of all academic backgrounds. Requirements Our Develop Your Career in Finance: Blue Ocean Strategy is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 1 sections • 9 lectures • 01:06:00 total length •Course Introduction: 00:02:00 •What is the Blue Ocean Strategy: 00:07:00 •Methods used in Blue Ocean Strategy - Value Innovation and Actions: 00:05:00 •Applying Blue Ocean Strategy for Career, Future Business Trends: 00:08:00 •How you can apply 4 Point Action for career planning: 00:12:00 •What is Personal Brand and Step1 in creating PB: 00:06:00 •Steps 2 to 8 in Personal Branding: 00:14:00 •Example of a LinkedIn Profile for Personal Branding: 00:08:00 •Summarising the way forward in career development: 00:04:00

Overview This comprehensive course on Professional Email Marketing Diploma will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Professional Email Marketing Diploma comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Professional Email Marketing Diploma. It is available to all students, of all academic backgrounds. Requirements Our Professional Email Marketing Diploma is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 3 sections • 26 lectures • 03:18:00 total length •Introduction and the Biggest Mistakes People Make With Email Marketing 00:06:00 •Introduction to Course Tutor 00:15:00 •What is email marketing all about? 00:04:00 •Promotional Email: 00:08:00 •Value Email: 00:10:00 •Email Checklist: 00:12:00 •Autoresponder - Send a broadcast: 00:14:00 •Example Promotional Email: 00:03:00 •Testing the broadcast: 00:02:00 •Send the broadcast: 00:04:00 •How to add a pop up opt in: 00:07:00 •How to add a pop over opt in: 00:13:00 •Autoresponders: 00:06:00 •Free Trial Aweber: 00:02:00 •Create a New List: 00:05:00 •Turn off double opt in: 00:03:00 •Company Branding: 00:05:00 •Create an opt in box: 00:10:00 •Pop up box opt in: 00:02:00 •Blog 24 Follow up email series: 00:13:00 •Blog 25 Email test: 00:17:00 •The Benefits of the Internet: 00:06:00 •What are we trying to achieve: 00:09:00 •6 steps to a video opt in: 00:11:00 •End result: 00:06:00 •Next steps: 00:05:00

Master quality assurance with this comprehensive training. Learn the difference between quality control and assurance and become a quality manager.

Overview This comprehensive course on Affiliate Marketing will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Affiliate Marketing comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Affiliate Marketing. It is available to all students, of all academic backgrounds. Requirements Our Affiliate Marketing is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 11 sections • 31 lectures • 01:07:00 total length •Unit 1: Welcome to the Course: 00:03:00 •Unit 1: What is Affiliate Marketing: 00:06:00 •Unit 2: Why Affiliate Marketing is Beneficial to Companies: 00:02:00 •Unit 3: Benefits of Doing Affiliate Marketing: 00:03:00 •Unit 4: Why Affiliate Marketing is Awesome: 00:01:00 •Unit 1: 3 Things to Do Before Starting: 00:02:00 •Unit 2: Understand Different Types of Affiliate Sites: 00:02:00 •Unit 3: Always Provide Affiliate Disclosure: 00:02:00 •Unit 1: Steps to Start Affiliate Marketing: 00:02:00 •Unit 2: Choose a Profitable Niche: 00:03:00 •Unit 3: Setup Your Website: 00:03:00 •Unit 1: Different Types of Compensation Model: 00:03:00 •Unit 2: What Are Void Affiliate Transactions: 00:03:00 •Unit 1: How to Find Affiliate Programs: 00:02:00 •Unit 2: Steps to Choose an Affiliate Program: 00:02:00 •Unit 3: Working with Affiliate Networks: 00:02:00 •Unit 4: Download the List of 50 Affiliate Programs & Networks: 00:01:00 •Unit 1: Types of Articles You Can Write: 00:04:00 •Unit 2: What Are Keywords & How to Find Them: 00:05:00 •Unit 3: How to Write SEO Friendly Articles: 00:02:00 •Unit 4: Including Affiliate Links in Articles: 00:01:00 •Unit 1: Why Promoting Content is Important: 00:01:00 •Unit 2: Promoting with Social Media: 00:02:00 •Unit 3: Promoting through Pinterest: 00:02:00 •Unit 4: Using Q & A Forums: 00:01:00 •Unit 5: Running Paid Ads: 00:02:00 •Unit 6: Influencer Outreach Method: 00:02:00 •Unit 7: Using YouTube for Affiliate Marketing: 00:02:00 •Unit 1: Conclusion: 00:01:00 •Resources - Affiliate Marketing: 00:00:00 •Assignment - Affiliate Marketing: 00:00:00

Overview This comprehensive course on SEO - Search Engine Optimisation Level 5 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This SEO - Search Engine Optimisation Level 5 comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? After successfully completing the course you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this SEO - Search Engine Optimisation Level 5. It is available to all students, of all academic backgrounds. Requirements Our SEO - Search Engine Optimisation Level 5 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 7 sections • 38 lectures • 03:13:00 total length •Unit 1: Introduction: 00:04:00 •Unit 2: Course Overview: 00:04:00 •Unit 1: What is SEO (Search Engine Optimisation): 00:04:00 •Unit 2: Types of SEO: Black Hat, Grey Hat & White Hat SEO: 00:05:00 •Unit 3: How Search Engines Give Ranks: Crawling, Indexing & Ranking: 00:06:00 •Unit 4: 2 Ways to Get Ranked on Search Engines: 00:03:00 •Unit 1: On Page SEO Explained: 00:01:00 •Unit 2: On Page SEO Activities: 00:04:00 •Unit 3: 4 Key Ranking Factors of On Page SEO: 00:04:00 •Unit 4: Tools & Tips for Increasing Site Speed: 00:13:00 •Unit 5: Using SEO Friendly Themes: 00:06:00 •Unit 6: Increasing the Dwell Time & Decreasing Bounce Rate: 00:05:00 •Unit 7: How to Make the URL SEO Friendly: 00:03:00 •Unit 8: Long Form SEO Optimised Content: 00:03:00 •Unit 9: Internal Linking: 00:05:00 •Unit 10: Meta Title & Meta Description: 00:03:00 •Unit 11: Optimising Images for SEO: 00:04:00 •Unit 12: Outbound Links: 00:04:00 •Unit 1: What Are Keywords & Why They Are Important: 00:06:00 •Unit 2: Types of Keywords: 00:08:00 •Unit 3: Which Type of Keywords You Should Choose: 00:01:00 •Unit 4: Free Tools for Keyword Research & SEO: 00:06:00 •Unit 5: Paid Tools for Keyword Research & SEO: 00:03:00 •Unit 6: 2 Metrics to Check Before Choosing Content: 00:05:00 •Unit 7: Steps for Keyword Research: 00:11:00 •Unit 8: What is Keyword Stuffing?: 00:05:00 •Unit 1: Write SEO Optimised Title: 00:04:00 •Unit 2: 6 Hacks to Write Attractive Headlines: 00:17:00 •Unit 3: Keyword Placement For SEO: 00:06:00 •Unit 4: Steps to Write Content & Optimise It for Search Engines: 00:09:00 •Unit 1: What Is Off Page Optimisation: 00:01:00 •Unit 2: Link Building - 1st Factor of Off Page SEO: 00:07:00 •Unit 3: 3 Methods to Get Backlinks: 00:02:00 •Unit 4: Method 1: Guest Posting for Link Building: 00:07:00 •Unit 5: Method 2: Building Relations with Experts: 00:04:00 •Unit 6: Method 3: Getting Backlinks from Round Up Post: 00:04:00 •Unit 7: Social Media Marketing - 2nd Factor of Off Page SEO: 00:05:00 •Unit 1: Conclusion: 00:01:00

Dive into the criminal mind! Learn Forensic Psychology, understand criminal behaviour, aid investigations. Ignite your career in criminology, start now!

Overview This comprehensive course on Data Science & Machine Learning with Python will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with Python comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with Python. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with Python is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 90 lectures • 10:24:00 total length •Course Overview & Table of Contents: 00:09:00 •Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types: 00:05:00 •Introduction to Machine Learning - Part 2 - Classifications and Applications: 00:06:00 •System and Environment preparation - Part 1: 00:08:00 •System and Environment preparation - Part 2: 00:06:00 •Learn Basics of python - Assignment 1: 00:10:00 •Learn Basics of python - Assignment 2: 00:09:00 •Learn Basics of python - Functions: 00:04:00 •Learn Basics of python - Data Structures: 00:12:00 •Learn Basics of NumPy - NumPy Array: 00:06:00 •Learn Basics of NumPy - NumPy Data: 00:08:00 •Learn Basics of NumPy - NumPy Arithmetic: 00:04:00 •Learn Basics of Matplotlib: 00:07:00 •Learn Basics of Pandas - Part 1: 00:06:00 •Learn Basics of Pandas - Part 2: 00:07:00 •Understanding the CSV data file: 00:09:00 •Load and Read CSV data file using Python Standard Library: 00:09:00 •Load and Read CSV data file using NumPy: 00:04:00 •Load and Read CSV data file using Pandas: 00:05:00 •Dataset Summary - Peek, Dimensions and Data Types: 00:09:00 •Dataset Summary - Class Distribution and Data Summary: 00:09:00 •Dataset Summary - Explaining Correlation: 00:11:00 •Dataset Summary - Explaining Skewness - Gaussian and Normal Curve: 00:07:00 •Dataset Visualization - Using Histograms: 00:07:00 •Dataset Visualization - Using Density Plots: 00:06:00 •Dataset Visualization - Box and Whisker Plots: 00:05:00 •Multivariate Dataset Visualization - Correlation Plots: 00:08:00 •Multivariate Dataset Visualization - Scatter Plots: 00:05:00 •Data Preparation (Pre-Processing) - Introduction: 00:09:00 •Data Preparation - Re-scaling Data - Part 1: 00:09:00 •Data Preparation - Re-scaling Data - Part 2: 00:09:00 •Data Preparation - Standardizing Data - Part 1: 00:07:00 •Data Preparation - Standardizing Data - Part 2: 00:04:00 •Data Preparation - Normalizing Data: 00:08:00 •Data Preparation - Binarizing Data: 00:06:00 •Feature Selection - Introduction: 00:07:00 •Feature Selection - Uni-variate Part 1 - Chi-Squared Test: 00:09:00 •Feature Selection - Uni-variate Part 2 - Chi-Squared Test: 00:10:00 •Feature Selection - Recursive Feature Elimination: 00:11:00 •Feature Selection - Principal Component Analysis (PCA): 00:09:00 •Feature Selection - Feature Importance: 00:07:00 •Refresher Session - The Mechanism of Re-sampling, Training and Testing: 00:12:00 •Algorithm Evaluation Techniques - Introduction: 00:07:00 •Algorithm Evaluation Techniques - Train and Test Set: 00:11:00 •Algorithm Evaluation Techniques - K-Fold Cross Validation: 00:09:00 •Algorithm Evaluation Techniques - Leave One Out Cross Validation: 00:05:00 •Algorithm Evaluation Techniques - Repeated Random Test-Train Splits: 00:07:00 •Algorithm Evaluation Metrics - Introduction: 00:09:00 •Algorithm Evaluation Metrics - Classification Accuracy: 00:08:00 •Algorithm Evaluation Metrics - Log Loss: 00:03:00 •Algorithm Evaluation Metrics - Area Under ROC Curve: 00:06:00 •Algorithm Evaluation Metrics - Confusion Matrix: 00:10:00 •Algorithm Evaluation Metrics - Classification Report: 00:04:00 •Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction: 00:06:00 •Algorithm Evaluation Metrics - Mean Absolute Error: 00:07:00 •Algorithm Evaluation Metrics - Mean Square Error: 00:03:00 •Algorithm Evaluation Metrics - R Squared: 00:04:00 •Classification Algorithm Spot Check - Logistic Regression: 00:12:00 •Classification Algorithm Spot Check - Linear Discriminant Analysis: 00:04:00 •Classification Algorithm Spot Check - K-Nearest Neighbors: 00:05:00 •Classification Algorithm Spot Check - Naive Bayes: 00:04:00 •Classification Algorithm Spot Check - CART: 00:04:00 •Classification Algorithm Spot Check - Support Vector Machines: 00:05:00 •Regression Algorithm Spot Check - Linear Regression: 00:08:00 •Regression Algorithm Spot Check - Ridge Regression: 00:03:00 •Regression Algorithm Spot Check - Lasso Linear Regression: 00:03:00 •Regression Algorithm Spot Check - Elastic Net Regression: 00:02:00 •Regression Algorithm Spot Check - K-Nearest Neighbors: 00:06:00 •Regression Algorithm Spot Check - CART: 00:04:00 •Regression Algorithm Spot Check - Support Vector Machines (SVM): 00:04:00 •Compare Algorithms - Part 1 : Choosing the best Machine Learning Model: 00:09:00 •Compare Algorithms - Part 2 : Choosing the best Machine Learning Model: 00:05:00 •Pipelines : Data Preparation and Data Modelling: 00:11:00 •Pipelines : Feature Selection and Data Modelling: 00:10:00 •Performance Improvement: Ensembles - Voting: 00:07:00 •Performance Improvement: Ensembles - Bagging: 00:08:00 •Performance Improvement: Ensembles - Boosting: 00:05:00 •Performance Improvement: Parameter Tuning using Grid Search: 00:08:00 •Performance Improvement: Parameter Tuning using Random Search: 00:06:00 •Export, Save and Load Machine Learning Models : Pickle: 00:10:00 •Export, Save and Load Machine Learning Models : Joblib: 00:06:00 •Finalizing a Model - Introduction and Steps: 00:07:00 •Finalizing a Classification Model - The Pima Indian Diabetes Dataset: 00:07:00 •Quick Session: Imbalanced Data Set - Issue Overview and Steps: 00:09:00 •Iris Dataset : Finalizing Multi-Class Dataset: 00:09:00 •Finalizing a Regression Model - The Boston Housing Price Dataset: 00:08:00 •Real-time Predictions: Using the Pima Indian Diabetes Classification Model: 00:07:00 •Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset: 00:03:00 •Real-time Predictions: Using the Boston Housing Regression Model: 00:08:00 •Resources - Data Science & Machine Learning with Python: 00:00:00

Unleash your inner editor with our comprehensive copyediting and proofreading course. Master the skills to polish your writing to perfection and become a sought-after professional.

Overview This comprehensive course on Data Visualization and Reporting with Power BI will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Visualization and Reporting with Power BI comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Visualization and Reporting with Power BI. It is available to all students, of all academic backgrounds. Requirements Our Data Visualization and Reporting with Power BI is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 15 sections • 140 lectures • 14:25:00 total length •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 •Creating our initial project file: 00:04:00 •Working with the attached project files: 00:04:00 •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 1 - Exercise Solution: 00:11:00 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •Congratulations & next steps: 00:06:00 •The End: 00:01:00 •Resources - Data Visualization and Reporting with Power BI: 00:00:00