264 Matrix courses

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

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

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? 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 Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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 Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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 £85 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 Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

This Laboratory Expert Diploma course is the perfect stepping stone for anyone looking to become a Laboratory Technician

Branding is an important aspect of marketing to promote your product or services. It is best for you to be exposed to strategies, methods, and solutions on the marketing performance your business is currently having. This Professional Diploma in Business Administration and Branding can help you in learning marketing applications how to identify problems and create solutions for your marketing needs. You will learn new strategies and techniques appropriate for your brand to promote your products and services to your target market. Course Highlights The price is for the whole course including final exam - no hidden fees Accredited Certificate upon successful completion at an additional cost Efficient exam system with instant results Track progress within own personal learning portal 24/7 customer support via live chat Professional Diploma in Business Administration and Branding has been given CPD accreditation and is one of the best-selling courses available to students worldwide. This valuable course is suitable for anyone interested in working in this sector or who simply wants to learn more about the topic. If you're an individual looking to excel within this field then Professional Diploma in Business Administration and Branding is for you. We've taken this comprehensive course and broken it down into several manageable modules which we believe will assist you to easily grasp each concept - from the fundamental to the most advanced aspects of the course. It really is a sure pathway to success. All our courses offer 12 months access and are designed to be studied at your own pace so you can take as much or as little time as you need to complete and gain the full CPD accredited qualification. And, there are no hidden fees or exam charges. We pride ourselves on having friendly and experienced instructors who provide full weekday support and are ready to help with any of your queries. So, if you need help, just drop them an email and await a speedy response. Furthermore, you can check the validity of your qualification and verify your certification on our website at anytime. So, why not improve your chances of gaining professional skills and better earning potential. Assessment and Certification At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. After you have successfully passed the final exam, you will be able to order an Accredited Certificate of Achievement at an additional cost of £19 for a PDF copy and £29 for an original print copy sent to you by post or for both £39. Career Path Not only does our CPD and CiQ accredited course look good on your CV, setting you apart from the competition, it can be used as a stepping stone to greater things. Further advance your learning, launch a new career or reinvigorate an existing one. On successful completion of this course, you have the potential to achieve an estimated salary of £17,100. The sky really is the limit. Course Curriculum Business Administration What is Business Administration? 00:30:00 Business and Organisations 00:15:00 Management of Business 00:40:00 Business Organization Perspectives 00:30:00 Decision Making 00:30:00 Approaches to Leadership 00:30:00 Business Communication Communication Basics 00:30:00 Know Thyself and The Message 00:30:00 Learn To Use Terms of Business Communication That Invoke Emotions 00:30:00 Pay Attention To Body Language 00:30:00 Learn To Use Terms That Spark Interest 00:30:00 The Benefits Of Presenting Your Message In 1 Minute 00:30:00 Branding Basics Introduction 00:15:00 The Purple Cow 00:30:00 Try to be an Exceptionist 00:30:00 Make Yourself Well Recognised Before Your Customers 00:15:00 Wow Your Customers 00:30:00 Develop a Personal Style 00:30:00 Use Creative Imageries to Catch the Attention 00:30:00 Be a Traditionalist, Not a Fad Chaser 00:15:00 Bringing Out the Purple Cow in Your Business 00:30:00 Conclusion 00:15:00 Brand Management Defining Branding 00:15:00 What Are You All About? 00:30:00 Creating a Mission 00:15:00 Creating a Vision of the Future 00:15:00 Positioning Your Brand 00:15:00 Developing Your Style 00:15:00 Developing a Brand Name and Slogan 00:15:00 Creating a Visual Identity 00:30:00 Living Your Brand 00:15:00 Connecting with Customers 00:15:00 Launching Your Brand 00:15:00 Taking Your Brand's Pulse 00:15:00 Performing a SWOT Analysis 00:15:00 Measuring Brand Health with a Balanced Scorecard 00:15:00 Middleton's Brand Matrix 00:15:00 Interpreting Evaluation Results 00:15:00 Keeping the Brand Alive 00:15:00 Going Beyond the Brand 00:15:00 Business Branding What Is Branding 00:30:00 Research Your Topic Thoroughly 00:30:00 Let People Know Who You Are: Distinguish Yourself 01:00:00 Represent Yourself 00:30:00 Networking With Social Media 01:00:00 Use Videos 00:30:00 Offer Training Courses 00:30:00 Provide Quality Material And Customer Service 00:30:00 Live And Breathe Your Brand 00:30:00 How Not Branding Can Spell Disaster 00:15:00 Personal Branding Module One - Getting Started 00:30:00 Module Two - Defining Yourself (I) 00:30:00 Module Three - Defining Yourself (II) 00:30:00 Module Four - Controlling and Developing Your Image 00:30:00 Module Five - Personal and Professional Influences 00:30:00 Module Six - Sharpening Your Brand 00:30:00 Module Seven - Appearance Matters 00:30:00 Module Eight - Social Media (I) 00:30:00 Module Nine - Social Media (II) 02:00:00 Module Ten - Brand Management During a Crisis 01:00:00 Module Eleven - Branding Personality Traits 00:30:00 Module Twelve - Wrapping Up 00:30:00 Recommended Reading Recommended Reading : Professional Diploma in Business Administration and Branding 00:00:00 Mock Exam Mock Exam - Professional Diploma in Business Administration and Branding 00:20:00 Final Exam Final Exam - Professional Diploma in Business Administration and Branding 00:20:00

Strengthen your command over C language

The core principles gained from this course will help delegates have a better understanding of how to manage the relationships between sales and marketing stakeholders on the demand side and the manufacturing and other operational stakeholders on the supply side. PARTICIPANTS WILL LEARN HOW TO: • Take a different perspective on traditional data such as sales history and forecasts, as well as time-phased inventory projections and production capacity. • Recognise how their forecasts impact manufacturing schedules and inventory levels. • Assess whether they are producing enough products to meet sales demand. • Recognise how production is tied to finance and see the financial impact of production decisions, so appropriate adjustments may be then undertaken. COURSE TOPICS INCLUDE: What is S&OP? – Introduction – Definition and benefits S&OP processes – What information is required? – The stages of the S&OP process (including inputs & outputs) The integration of S&OP into a business – Critical success factors for an effective implementation – Typical roles and responsibility matrix

Throughout this course, you will learn how to operate and maintain laboratory equipment and perform laboratory technician tasks.

Key Objectives for the Training provision Effective listening to a client's needs and requirements during various stages of the sales process. Engage in meaningful communication with clients, learn to identify challenges and opportunities that relate to the prospects. Overcome the identified challenge. Build long term rapport and establish trust with the prospect throughout the sales process, Ensure continued customer satisfaction that can turn into repeat business. Be able to build rapport with customers or clients. Know the right questions to ask to fully understand the customer or client’s needs without putting on any pressure. Be able to check you have the right information from the customer or client. Be able to match products and services to the customer or client using the information you have gathered. Be able to influence effectively. Know how to stand out from your competitors. Stage 1 – Research the Company’s ‘Value Propositions’ and USP Analysis  Conducting 30 min confidential interviews with a cross-section of the eligible Attendees & the Stakeholders, in order to gain an objective understanding of the various scenarios and clients that the Participants work with. the Company’s ‘Value Propositions’ Unique Selling Points The Customers’ journey(s) The Competition’s offers for analysis and comparisons. From these findings, a carefully calibrated bespoke Programme will be designed and delivered.  Stage 2 - Design the Bespoke 2 x day Course  nd Stage 3 - Delivery of the Course Programme This Programme can be delivered in 2 x consecutive days, or split between 2 – 3 weeks, to make it more ‘work-friendly’ – if required. It is very practical and commercially focussed in approach, with lots of interactive exercises designed to draw out the learning applications via the debriefings. The ‘Real Play’ scenarios on day 2 will be based on specific case studies drawn from the Research findings so that they are authentic to optimise the learning. Individual Action Plans will be captured at the end of each day to be debriefed by the Participants’ respective Line Managers.  Template Programme Day One – Foundation – Strategic Approach Section One – The Principles of Consultative Selling Defining ‘Consultative Selling’ The Company’s ‘Unique Selling Points’ & Value Proposition The Consultative Selling model – the five stages Avoiding appearing ‘pushy’, ‘pressurising’ or ‘talking through the sale’ Section Two –Strategy & Preparation  ‘Buy-Class’ Matrix Strategic plan Template – matching services/products to identified needs & opportunities. Preparing a range of objectives Constants and variables – USP’s Researching key Client/Decision Makers’ priorities, profile & background (LinkedIn etc.) Preparing for potential & likely Objections Section Three – Email etiquette & ‘influencing’ email correspondence.  Email etiquette A.B.S.U.R.D model Clarity and tone – discovery of clients’ needs & motivational factors. Techniques to influence and ‘nudge’. Ensuring the data and content have a ‘gentle’ motivational & appealing message. Top Tips Day Two – Practical Application Section Four – Rapport Building & Effective Communication skills ‘Behaviour Labelling’ techniques – setting a positive tone. Asking Open Questions – gaining a full understanding of the clients’ priorities & expectations. EQ - Inviting opinions; perspectives; experiences – winning confidence. Active Listening – focus and commitment to understand. ‘Reading the room’ – adapting to responses and reactions. Maintaining focus on relevant topics that the Client cares about; carefully consider the opportunities to influence. But NO PRESSURE! Building a ‘bond of trust’ with commitments and authentic, shared values. Section Five – Explaining the Benefits – aligned to the Customers’ Priorities Understanding ‘Why do People Buy?’ Research data analysis. Open questions that lead to understanding the key issues and Clients’ priorities. Avoiding the danger of ‘pressurising’ the Client. Responding to objections effectively, with confidence and sensitivity. Explaining the benefits that are aligned to the Clients’ stated requirements. Making the Data ‘sing’ – memorable takeaways for the Client. Augmented benefits – Brand confidence; Case studies; Warranty; Service; Range; Flexibility etc. in alignment with their stated preferences/requirements Differentials compared to Competitors Section Six – Winning Commitment Inviting commitment – with confidence Consultative Selling Closing techniques (e.g. Alternative Close/Assumptive Close et al) Avoiding ‘talking through the sale’ – knowing when to ‘Shut UP!’ Confirming agreement – ensuring Clients’ motivation for repeat business Section Seven – Practical Application ‘Real Play’ From the Research findings, carefully devised scenarios can be generated to provide the most valuable learning opportunities to underpin all the skills & techniques covered in the Programme.  Potential Real Play scenarios: A well-established customer has indicated that they are soon to be opening up additional new offices – this presents an opportunity to arrange for the Company to support them with their upcoming needs. After some very positive feedback and with the upcoming contract renewal imminent – how can the Company give the Customer more high-quality support in other areas of their business? A Competitor has been to see the client and they have prompted some concerns about ‘value for money’ & ‘quality of service’. How Real Play works… The group is split the group into 2 sub-groups, one with our Professional Actor (option available); the other with the Trainer or a willing Participant. Each group has a brief and has to instruct their Trainer/Actor/Participant on how to approach the scenario supplied. The Actor and Trainer (or willing Participant) perform the role play(s) as instructed by their respective teams; however, during the action they can be paused for further recommendations or direction. The outcome is the responsibility of the team(s) – not the performers. Debrief the full Programme Individual Action Plans - to be followed through. ‘Best Practices’ for application into the business Options for Exercises within the Programme  Sample Exercise – Red & White  There is a specific time managed agenda and itinerary, which puts the group under pressure.  The key challenge is for the sub-groups to maximise the commercial value from the task, however there is always a great danger that the individuals attempt to gain financial progress at the expense of the other group! Debriefing points: Persuasive communication and influence across barriers Gaining buy-in when others are sceptical Strategic planning accounting for others’ behaviours Sample Exercise – Communication Challenge Each Participant has different pieces of information, but are not allowed to share it visually. They are only allowed to communicate to work out the solution hidden among the large amount of data. Debrief: Structured approach Maintaining focus through distractions/interference Active Listening Controlled communication Sample Exercise – Persuasive emails Sample emails are shared to be critiqued and improved upon to be debriefed: Tone & impact Making the Data ‘sing’ Influential & motivational language Customer centric message. Sample Exercise –Juggling   Each Participant has to pass the ‘Customers’ (Juggling balls) carefully through the system with all the other Participants to reach a profitable conclusion  Debrief: EQ to read the room and effectively communicate, when the pressure is on Customer focus and adapting to challenges Devising a plan that wins buy-in Overcoming competing ideas to get to ‘best practice’ Consistent commitment, communication and motivational drivers that influenced performance. Sample Exercise –Critical Path  The group are provided with 30 x discs and some ‘post-it’ notes. (no pens or pencils are allowed) Their brief is to create a grid shape with the 30 x discs, which will act as ‘stepping stones’ for the ‘Critical Path’ But they have to follow the correct order through the grid from the start to finish, which they will have to work out through ‘trial & error’ All of the team must pass through the ‘Critical Path’ worked out on the grid, observing the constraints, within the time limit. No talking is permitted once they start using the materials Debrief: - Clear communication focussing on the ‘client’s journey’ Planning for challenges Identifying risks and mitigating them Role allocations & support Quality control and disciplines  Sample Exercise –Back to Back  Each Participant is positioned back-to-back with a partner. They have to work out precisely what the ‘statement’ given to the other person is without looking around. Each person has a different brief. Debrief: - Asking Open Questions Active Listening Accuracy in identifying the objective.

Our up-to-date course covers the latest PMBOK 6, 7, and Agile updates, providing a simplified guide to project management. Learn the framework, processes, and knowledge areas, and see how they work together to manage projects and stakeholders. It is perfect for those seeking to efficiently manage projects and pass the PMP exam.