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Overview This comprehensive course on Complete Microsoft Power BI 2021 will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Complete Microsoft Power BI 2021 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 Complete Microsoft Power BI 2021. It is available to all students, of all academic backgrounds. Requirements Our Complete Microsoft Power BI 2021 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 - Complete Microsoft Power BI 2021: 00:00:00

Overview This comprehensive course on Microsoft PowerBI - 25 Must-Know Tips and Tricks will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Microsoft PowerBI - 25 Must-Know Tips and Tricks 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 Microsoft PowerBI - 25 Must-Know Tips and Tricks. It is available to all students, of all academic backgrounds. Requirements Our Microsoft PowerBI - 25 Must-Know Tips and Tricks 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 • 2 lectures • 01:34:00 total length •Must-Know Tips and Tricks of Microsoft PowerBI: 01:34:00 •Resource - Microsoft PowerBI - 25 Must-Know Tips and Tricks: 00:00:00

Overview This comprehensive course on PowerBI Formulas will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This PowerBI Formulas 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 PowerBI Formulas. It is available to all students, of all academic backgrounds. Requirements Our PowerBI Formulas 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 • 18 lectures • 01:25:00 total length •power pivot power query - 1: 00:01:00 •power pivot power query - 2: 00:02:00 •power pivot power query - 3: 00:06:00 •power pivot power query - 4: 00:07:00 •power pivot power query - 5: 00:02:00 •power pivot power query - 6: 00:05:00 •power pivot power query - 7: 00:05:00 •power pivot power query - 8: 00:04:00 •power pivot power query - 9: 00:03:00 •power pivot power query - 10: 00:02:00 •power pivot power query - 11: 00:04:00 •power pivot power query - 12: 00:08:00 •power pivot power query - 13: 00:04:00 •power pivot power query - 14: 00:03:00 •power pivot power query - 15: 00:13:00 •power pivot power query - 16: 00:03:00 •power pivot power query - 17: 00:13:00 •Assignment - PowerBI Formulas: 00:00:00

Overview Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents, and interests with our special Big Data Analytics with PySpark Power BI and MongoDB Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides the professional training that employers are looking for in today's workplaces. The Big Data Analytics with PySpark Power BI and MongoDB Course is one of the most prestigious training offered at Skillwise and is highly valued by employers for good reason. This Big Data Analytics with PySpark Power BI and MongoDB Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Big Data Analytics with PySpark Power BI and MongoDB Course, like every one of Skillwise's courses, is meticulously developed and well-researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At Skillwise, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from Skillwise, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Big Data Analytics with PySpark Power BI and MongoDB? Unlimited access to the course forever Digital Certificate, Transcript, and student ID are all included in the price Absolutely no hidden fees Directly receive CPD Quality Standard-accredited qualifications after course completion Receive one-to-one assistance 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 Big Data Analytics with PySpark Power BI and MongoDB 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 free. Original Hard Copy certificates need to be ordered at an additional cost of £8. Who is this course for? This Big Data Analytics with PySpark Power BI and MongoDB 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 skills. Prerequisites This Big Data Analytics with PySpark Power BI and MongoDB does not require you to have any prior qualifications or experience. You can just enroll and start learning. This Big Data Analytics with PySpark Power BI and MongoDB was made by professionals and it is compatible with all PCs, Macs, 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 a bonus, you will be able to pursue multiple occupations. This Big Data Analytics with PySpark Power BI and MongoDB is a great way for you to gain multiple skills from the comfort of your home.   Section 01: Introduction Introduction 00:10:00 Section 02: Setup and Installations Python Installation 00:03:00 Installing Apache Spark 00:12:00 Installing Java (Optional) 00:05:00 Testing Apache Spark Installation 00:06:00 Installing MongoDB 00:04:00 Installing NoSQL Booster for MongoDB 00:07:00 Section 03: Data Processing with PySpark and MongoDB Integrating PySpark with Jupyter Notebook 00:05:00 Data Extraction 00:19:00 Data Transformation 00:15:00 Loading Data into MongoDB 00:13:00 Section 04: Machine Learning with PySpark and MLlib Data Pre-processing 00:19:00 Building the Predictive Model 00:12:00 Creating the Prediction Dataset 00:08:00 Section 05: Creating the Data Pipeline Scripts Installing Visual Studio Code 00:03:00 Creating the PySpark ETL Script 00:22:00 Creating the Machine Learning Script 00:24:00 Section 06: Tableau Data Visualization Installing Tableau 00:03:00 Installing MongoDB ODBC Drivers 00:03:00 Creating a System DSN for MongoDB 00:04:00 Loading the Data Sources 00:04:00 Creating a Geo Map 00:11:00 Creating a Bar Chart 00:03:00 Creating a Magnitude Chart 00:07:00 Creating a Table Plot 00:06:00 Creating a Dashboard 00:07:00 Source Code Source Code and Notebook

Personal Development: Personal Development Online Personal development is about looking inside and trying to focus on ways to improve yourself. Personal Development: Personal Development Course increases self-awareness, identity, knowledge, and desires. Mental, Social, Spiritual, Emotional are the areas of personal development. Personal development has numerous advantages. Personal Development: Personal Development Course is not easy, but the advantages will make the effort worthwhile. If you're interested in life coaching or looking for a Personal Development: Personal Development Course to boost your self-esteem or emotional intelligence, this is the course for you. This Personal Development: Personal Development Course provides you with a thorough understanding of personal development, academic and personal development, and enhances your skills for a successful professional career. Enrol our Personal Development: Personal Development Course, which is aligned with job requirements. Our instructors have designed this Personal Development: Personal Development Course with the needs of learners in mind, so you should not be hesitant to invest in it. Main Course: Level 5 Personal Development Course Free Courses: Course 01: Self Esteem & Assertiveness Skill Course 02: Communication Skills [ Note: Free PDF certificate as soon as completing Personal Development: Personal Development Course] Personal Development: Personal Development Course Online This Personal Development: Personal Development Course consists of 12 modules. Assessment Method of Personal Development: Personal Development Course After completing Personal Development: Personal Development Course, you will get quizzes to assess your learning. You will do the later modules upon getting 60% marks on the quiz test. Apart from this, you do not need to sit for any other assessments. Certification of Personal Development: Personal Development Course After completing the Personal Development: Personal Development Course, you can instantly download your certificate for FREE. The hard copy of the certification will also be delivered to your doorstep via post, which will cost £13.99. Who is this course for? Level 5 Personal Development: Personal Development Online This Personal Development: Personal Development Course Online is recommended for people who want to advance in their personal and professional lives. It is also recommended that industry owners enrol their employees in this Personal and Professional Development course. Requirements Personal Development: Personal Development Course Online To enrol in this Personal Development: Personal Development Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Personal Development: Personal Development Course. Be energetic and self-motivated to complete our Personal Development: Personal Development Course. Basic computer Skill is required to complete our Personal Development: Personal Development Course. If you want to enrol in our Personal Development: Personal Development Course, you must be at least 15 years old. Career path Personal Development: Personal Development Course Online After completing this Personal Development: Personal Development Course, you may be able to pursue a variety of promising career opportunities, such as: Coach Mentoring Professional and personal development and many more.

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

Financial Analysis Course Overview The "Financial Analysis" course provides a comprehensive introduction to financial analysis, equipping learners with the knowledge and skills needed to interpret and evaluate financial statements. Covering key areas such as balance sheets, income statements, and cash flow analysis, this course enables learners to assess financial performance and make informed decisions. Whether you are starting your career in finance or aiming to enhance your existing knowledge, this course offers essential tools for financial analysis. Upon completion, learners will be able to analyse financial data effectively, understand the key financial indicators of businesses, and contribute to strategic financial decision-making. Course Description This course covers the fundamentals of financial analysis, providing in-depth insights into financial statements, including balance sheets, income statements, and cash flow statements. Learners will explore various financial reporting techniques, evaluate profitability, and develop the ability to conduct ratio and equity analysis. The course also delves into the applications and limitations of EBITDA and teaches learners to assess credit risks. By the end of the course, participants will have gained valuable skills in financial data interpretation, enabling them to assess financial health and contribute to strategic financial decisions in organisations. The learning experience combines theoretical knowledge with practical analytical skills to prepare learners for roles in finance and accounting. Financial Analysis Curriculum: Module 01: Introduction to Financial Analysis Module 02: The Balance Sheet Module 03: The Income Statement Module 04: The Cash Flow Statement Module 05: Financial Reporting Module 06: Analysing Profitability Module 07: The Applications and Limitations of EBITDA Module 08: Credit Analysis Module 09: Equity Analysis Module 10: Ratio Analysis (See full curriculum) Who is this course for? Individuals seeking to understand financial analysis Professionals aiming to enhance their financial reporting and decision-making skills Beginners with an interest in finance or accounting Business owners looking to improve their financial literacy Career Path Financial Analyst Accountant Credit Analyst Financial Consultant Corporate Finance Manager Business Intelligence Analyst Investment Analyst

Spiritual Life Coaching Course Overview This course on Spiritual Life Coaching is designed to equip learners with the essential knowledge and skills required to guide others through transformative life changes. Covering the basics of spiritual coaching, it explores the role of a coach, the key qualities required, and how to develop a successful practice. Learners will also gain an understanding of ethical considerations, advanced coaching techniques, and strategies to market and grow their business. Upon completion, participants will be able to confidently offer coaching services while aligning with ethical standards and effectively promoting their practice. This course provides a well-rounded foundation for those interested in becoming spiritual life coaches or enhancing their existing skills. Course Description In this comprehensive course, learners will explore the core principles and methodologies of spiritual life coaching. Beginning with an introduction to coaching basics, the course progresses to more advanced topics such as effective communication techniques, the significance of empathy, and the ethical responsibilities of a coach. Learners will develop key qualities such as emotional intelligence, active listening, and mindfulness, which are essential to guide clients through their spiritual and personal journeys. The course also covers strategies for marketing a coaching business, helping participants reach a wider audience and successfully build their practice. By the end of the course, learners will be equipped with the expertise to offer impactful, ethical spiritual coaching services and expand their professional opportunities. Spiritual Life Coaching Curriculum Module 01: Basics of Spiritual Life Coaching Module 02: Understanding Spiritual Life Coaching Module 03: Fundamental Qualities of a Coach Module 04: Advanced Coaching Module 05: Ethical Guidelines Module 06: Marketing Your Business Module 07: Growing Your Business (See full curriculum) Who is this course for? Individuals seeking to become certified spiritual life coaches. Professionals aiming to develop their coaching skills for career advancement. Beginners with an interest in personal development and coaching. Those looking to build a new career in spiritual coaching. Career Path Spiritual Life Coach Personal Development Coach Wellness Coach Life Coach Entrepreneur in Coaching Business Business Consultant in Personal Development

Course Overview This course, Self-Help Psychology: Mental Freedom, is designed to guide individuals through the process of achieving mental liberation from negative thought patterns and emotional baggage. It combines psychological principles with personal development strategies to help learners cultivate resilience, confidence, and emotional balance. By engaging with the course, participants will explore various techniques and theories to reclaim their mental freedom and transform their mindset, empowering them to lead more fulfilling lives. The course equips learners with the tools necessary for emotional empowerment, self-awareness, and psychological well-being. Course Description Self-Help Psychology: Mental Freedom offers a comprehensive exploration of psychological concepts that foster emotional release and mental clarity. The course covers a range of topics, including cognitive behavioural techniques, emotional regulation, mindfulness practices, and resilience-building exercises. Learners will gain a deeper understanding of how thoughts and emotions affect mental freedom and how to break free from limiting beliefs and self-sabotage. By the end of the course, participants will have developed a set of strategies to enhance mental wellness, cope effectively with stress, and achieve a mindset that is positive and empowered. Course Modules Module 01: Mental Freedom: From PAIN To POWER Module 02: Understanding the Psychology of Self-Empowerment Module 03: Cognitive Behavioural Techniques for Emotional Clarity Module 04: The Role of Mindfulness in Mental Liberation Module 05: Building Resilience and Overcoming Setbacks Module 06: Reprogramming Your Mindset for Success Module 07: Creating a Long-Term Plan for Mental Wellness (See full curriculum) Who is this course for? Individuals seeking to improve mental clarity and emotional well-being Professionals aiming to enhance their personal development and emotional intelligence Beginners with an interest in psychology and self-help techniques Anyone looking to break free from mental barriers and develop a positive mindset Career Path Life Coach Mental Health Support Worker Personal Development Specialist Wellness Consultant Counsellor HR Professional focusing on employee well-being

Excel Vlookup, Xlookup, Match and Index Course Overview: This comprehensive course covers essential Excel functions such as VLOOKUP, XLOOKUP, MATCH, and INDEX, which are integral for efficient data management and analysis. Learners will gain a clear understanding of how to use these functions to simplify complex data tasks, enhance productivity, and improve decision-making. Throughout the course, students will master how to search, match, and retrieve data from large datasets, preparing them for real-world scenarios in finance, marketing, HR, and more. The course is designed to equip learners with the necessary skills to perform advanced Excel functions with confidence, contributing to their professional growth and data analysis expertise. Course Description: In this course, learners will explore the powerful functions of Excel, including VLOOKUP, XLOOKUP, MATCH, and INDEX, enabling them to perform efficient data searches, cross-referencing, and information retrieval. The course includes step-by-step lessons on how to apply these functions to real-world datasets, making it highly relevant for anyone working with large volumes of data. Learners will become proficient in building dynamic spreadsheets that streamline decision-making processes and improve data accuracy. Additionally, this course emphasises problem-solving techniques, empowering individuals to handle complex data-related tasks with ease. By the end of the course, learners will have a strong command of these Excel functions, boosting their data management and analytical capabilities. Excel Vlookup, Xlookup, Match and Index Curriculum: Module 01: Excel VLOOKUP Module 02: Excel XLOOKUP Module 03: Excel MATCH Module 04: Excel INDEX Module 05: Advanced VLOOKUP Techniques Module 06: Combining VLOOKUP, MATCH, and INDEX Module 07: Practical Applications of XLOOKUP (See full curriculum) Who is this course for? Individuals seeking to enhance their Excel skills for data analysis. Professionals aiming to improve their data management capabilities. Beginners with an interest in learning advanced Excel functions. Anyone looking to improve their problem-solving abilities in data-heavy tasks. Career Path: Data Analyst Financial Analyst Marketing Analyst HR Specialist Business Intelligence Specialist Excel Expert for Administrative or Management Roles