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Learning Objectives Introduction , Customizing Excel , Analyzing Data with Logical Functions , Working with Lookup Functions , Using Text Functions , Working with Date and Time Functions , Formula Auditing , What-If Analysis , Worksheet and Workbook Protection , Automating with Macros , Working with Form Controls , Ensuring Data Integrity , Collaborating in Excel , Importing and Exporting Data to a Text File , Conclusion   Pre-Requisites Excel 365 Introduction and Intermediate courses or equivalent experience.   Description This course will teach students advanced concepts and formulas in Microsoft Excel 365. Students will learn functions such as SUMIF, AVERAGEIF, and COUNTIF, advanced lookup functions, and complex logical and text functions. Additionally, students will experiment with auditing formulas and error checking, use the What-If Analysis tools, learn the options for worksheet and workbook protection, review advanced use of PivotTables and PowerPivot add-in, work with Macros, use form controls, and ensure data integrity in their worksheets and workbooks. Students will also learn about Excel's many collaboration features and import and export data to and from their workbooks. Course Introduction Introduction 00:01:00 Section 01 Lesson 01-Customizing the Ribbon 00:09:00 Lesson 02-Customizing the Quick Access Toolbar 00:06:00 Lesson 03-Customizing the General and Formula Options 00:04:00 Lesson 04-Customizing the AutoCorrect Options 00:03:00 Lesson 05-Customizing the Save Defaults 00:04:00 Lesson 06-Customizing Advanced Excel Options 00:03:00 Section 02 Lesson 01-Working with the Most Common Logical Functions 00:03:00 Lesson 02-Understanding IF Functions 00:06:00 Lesson 03-Evaluating Data with the AND Function 00:05:00 Lesson 04-Evaluating Data with the OR Function 00:03:00 Lesson 05-Creating a Nested IF Function 00:05:00 Lesson 06-Using the IFS Function 00:03:00 Lesson 07-Summarizing Data with SUMIF 00:03:00 Lesson 08-Summarizing Data with AVERAGEIF 00:02:00 Lesson 09-Summarizing Data with COUNTIF 00:02:00 Lesson 10-Summarizing Data with MAXIFS and MINIFS 00:03:00 Lesson 11-Using the IFERROR Function 00:03:00 Section 03 Lesson 01-What are Lookup Functions 00:03:00 Lesson 02-Using VLOOKUP 00:08:00 Lesson 03-Using HLOOKUP 00:03:00 Lesson 04-Using VLOOKUP with TRUE 00:04:00 Lesson 05-Using HLOOKUP with TRUE 00:02:00 Lesson 06-Using the Index Function 00:03:00 Lesson 07-Using the MATCH Function 00:03:00 Lesson 08-Combining INDEX and MATCH 00:04:00 Lesson 09-Comparing Two Lists with VLOOKUP 00:02:00 Lesson 10-Comparing Two Lists with VLOOKUP and ISNA 00:04:00 Lesson 11-Using the New XLookup Function-v2 00:07:00 Lesson 12-Using Dynamic Array functions-v2 00:06:00 Lesson 13-Other New Functions-v2 00:04:00 Section 04 Lesson 01-What are Text Functions 00:01:00 Lesson 02-Using CONCAT, CONCATENATE, AND TEXTJOIN 00:04:00 Lesson 03-Using Text to Columns 00:02:00 Lesson 04-Using LEFT, RIGHT, and MID Functions 00:03:00 Lesson 05-Using UPPER, LOWER, and PROPER Functions 00:02:00 Lesson 06-Using the Len Function 00:03:00 Lesson 07-Using the Trim Function 00:01:00 Lesson 08-Using the SUBSTITUTE Function 00:02:00 Section 05 Lesson 01-What are Date and Time Functions 00:02:00 Lesson 02-Using TODAY, NOW, and DAY Functions 00:03:00 Lesson 03-Using NETWORKDAYS and YEARFRAC Functions 00:03:00 Section 06 Lesson 01-Showing Formulas 00:03:00 Lesson 02-Tracing Precedents and Dependents 00:04:00 Lesson 03-Adding a Watch Window 00:04:00 Lesson 04-Error Checking 00:04:00 Section 07 Lesson 01-Using the Scenario Manager 00:07:00 Lesson 02-Using Goal Seek 00:03:00 Lesson 03-Analyzing with Data Tables 00:04:00 Section 08 Lesson 01-Understanding Protection 00:02:00 Lesson 02-Encrypting Files with Passwords 00:05:00 Lesson 03-Allowing Specific Worksheet Changes 00:02:00 Lesson 04-Adding Protection to Selected Cells 00:03:00 Lesson 05-Additional Protection Features 00:03:00 Section 09 Lesson 01-What are Macros 00:03:00 Lesson 02-Displaying the Developer Tab 00:03:00 Lesson 03-Creating a Basic Formatting Macro 00:05:00 Lesson 04-Assigning a Macro to a Button 00:03:00 Lesson 05-Creating Complex Macros 00:04:00 Lesson 06-Viewing and Editing the VBA Code 00:04:00 Lesson 07-Adding a Macro to the Quick Access Toolbar 00:03:00 Section 10 Lesson 01-What are Form Controls 00:02:00 Lesson 02-Adding a Spin Button and Check Boxes 00:04:00 Lesson 03-Adding a Combo Box 00:07:00 Section 11 Lesson 01-What is Data Validation 00:02:00 Lesson 02-Restricting Data Entry to the Whole Numbers 00:02:00 Lesson 03-Restricting Data Entry to a List 00:04:00 Lesson 04-Restricting Data Entry to a Date 00:02:00 Lesson 05-Restricting Data Entry to Specific Text Lengths 00:01:00 Lesson 06-Composing Input Messages 00:02:00 Lesson 07-Composing Error Alerts 00:03:00 Lesson 08-Finding Invalid Data 00:02:00 Lesson 09-Editing and Deleting Validation Rules 00:01:00 Section 12 Lesson 01-Working with Comments-v2 00:03:00 Lesson 02-Printing Comments and Errors 00:02:00 Lesson 03-Sharing a Workbook 00:04:00 Lesson 04-Co-Authoring in Excel 00:02:00 Lesson 05-Tracking Changes in a Workbook 00:03:00 Lesson 06-Working with Versions 00:03:00 Lesson 07-Sharing files Via Email-v2 00:03:00 Section 13 Lesson 01-Importing a Text File 00:04:00 Lesson 02-Exporting Data to a Text File 00:01:00 Course Recap Recap 00:02:00 Additional Materials Resource - Excel 365 Advanced 00:00:00 Final Exam Final Exam - Excel 365 Advanced 00:20:00

Course Description Get instant knowledge from this bite-sized Criminal Intelligence Analyst Part - 1 course. This course is very short and you can complete it within a very short time. In this Criminal Intelligence Analyst Part - 1 course you will get fundamental ideas of criminal intelligence, the key understanding of criminal intelligence analysis, criminal psychology and so on. Enrol in this course today and start your instant first step towards learning intelligence analysis. Learn faster for instant implementation. Learning Outcome Familiarise with intelligence analysis Understand criminal intelligence analysis Understand criminal psychology Learn about the skills and competencies of a criminal intelligence analyst Know the research methods in crime analysis How Much Do Intelligence Officers Earn? Senior - £131,000 (Apprx.) Average - £91,000 (Apprx.) Starting - £63,000 (Apprx.) Requirement Our Criminal Intelligence Analyst Part - 1 is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Criminal Intelligence Analyst Part - 1 Module 01: Introduction to Intelligence Analysis 00:19:00 Module 02: Criminal Intelligence Analysis 00:21:00 Module 03: Criminal Intelligence Analyst - Skills and Competencies 00:15:00 Module 04: Understanding Criminal Psychology 00:36:00 Module 05: Research Methods in Crime Analysis 00:28:00 Assignment Assignment - Criminal Intelligence Analyst Part - 1 00:00:00

Course Description Get instant knowledge from this bite-sized Criminal Intelligence Analyst Part - 2 course. This course is very short and you can complete it within a very short time. In this Criminal Intelligence Analyst Part - 2 course you will get fundamental ideas of criminal intelligence, the key understanding of decision making in criminal intelligence analysis, counterterrorism and so on. Enrol in this course today and start your instant first step towards learning about decision making in criminal intelligence analysis. Learn faster for instant implementation. Learning Outcome Familiarise with intelligence analysis Understand criminal intelligence analysis Understand criminal psychology Learn about the skills and competencies of a criminal intelligence analyst Know the research methods in crime analysis How Much Do Intelligence Officers Earn? Senior - £131,000 (Apprx.) Average - £91,000 (Apprx.) Starting - £63,000 (Apprx.) Requirement Our Criminal Intelligence Analyst Part - 2 is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Criminal Intelligence Analyst Part - 2 Module 01: Decision Making in Criminal Intelligence Analysis 00:17:00 Module 02: Intelligence-Led Policing 00:21:00 Module 03: Counterterrorism and Criminal Intelligence Analysis 00:21:00 Module 04: Technology in Criminal Intelligence Analysis 00:20:00 Module 05: The Criminal Justice System in England and Wales 00:18:00 Assignment Assignment - Criminal Intelligence Analyst Part - 2 00:00:00

The Microsoft Excel course is designed to teach you everything you need to know about Excel from scratch. This comprehensive, instructor-guided training will help you gain a thorough understanding of Excel’s essential features and functions, enabling you to kickstart your career or enhance your current skills. Whether you are just starting out or looking to build on your knowledge, this course will equip you with the most in-demand skills required in today's competitive job market.

Overview Criminal intelligence involves gathering and analysing information to predict and monitor illegal activity. Gain the relevant skills in criminal intelligence and by taking this Criminal Intelligence Analyst Training.  This Criminal Intelligence Analyst Training course will provide you with a thorough introduction to criminal intelligence analysis. The valuable lectures will guide you through criminal psychology, crime analysis research methods, and criminal intelligence analysis decision-making. The course will also educate you about counterterrorism and technology in criminal intelligence analysis.  Learning Outcomes Discover the skills of a criminal intelligence analyst Gain an excellent understanding of criminal psychology Know about the research methods in crime analysis Learn about counterterrorism and criminal intelligence analysis Understand how technology is used in crime analysis Why You Should Choose Criminal Intelligence Analyst Training Course Lifetime access to the course No hidden fees or exam charges CPD Qualification Standards certification on successful completion Full Tutor support on weekdays (Monday - Friday) Efficient exam system, assessment, and instant results Download Printable PDF certificate immediately after completion Obtain the original print copy of your certificate, dispatch the next working day for as little as £9. Improve your chance of gaining professional skills and better earning potential Who is this Course for? The Criminal Intelligence Analyst Training Course is for anyone interested in gaining the relevant skills in criminal intelligence analysis. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Criminal Intelligence Analyst Training Course is fully compatible with any kind of device. Whether you are using a Windows computer, Mac, smartphone or tablet, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path This course will provide you with the necessary knowledge and skills required to succeed in this sector. You will be ready to enter the relevant job market after completing this course. On top of that, the course will enhance your ability to earn an average salary of £52,500 annually.  Criminal Intelligence Analyst Training Module 01: Introduction to Intelligence Analysis 00:19:00 Module 02: Criminal Intelligence Analysis 00:21:00 Module 03: Criminal Intelligence Analyst - Skills and Competencies 00:15:00 Module 04: Understanding Criminal Psychology 00:36:00 Module 05: Research Methods in Crime Analysis 00:28:00 Module 06: Decision Making in Criminal Intelligence Analysis 00:17:00 Module 07: Intelligence-Led Policing 00:21:00 Module 08: Counterterrorism and Criminal Intelligence Analysis 00:21:00 Module 09: Technology in Criminal Intelligence Analysis 00:20:00 Module 10: The Criminal Justice System in England and Wales 00:18:00 Assignment Assignment - Criminal Intelligence Analyst Training 02:00:00

Master Microsoft Excel with our CPD Accredited Complete Course, covering Beginner, Intermediate & Advanced levels. Boost your skills for data analysis, financial management, and more. Ideal for students, recent graduates, job seekers, and professionals. Get recognized with a worldwide CPD certificate. Learn at your own pace with expert guidance and support. Elevate your career with Excel expertise. Enrol now!

Course overview Take a practical approach to enhance your Excel modelling skills with the Advanced Excel Models using Formulas, VBA & Power Query course. In this course, you will learn how to build robust Excel models using Formulas, VBA and Power Query. This Advanced Excel Models using Formulas, VBA & Power Query course offers a wide range of training modules to enhance your abilities to create better models. You will discover the advanced Excel formulas to prepare reports, forecast and perform mathematical calculations. We will introduce you to the three excel models and show the functions used to prepare these pro models. In addition, you will learn the Excel formulas for prepaid expenses and explore the steps to create dynamic dashboards based on Power Query and Pivot Table without any formula. Learning outcomes Familiarize yourself with the advanced Excel formulas Be able to manage prepaid expenses Deepen your understanding of the prepaid expense models Learn about the pro Excel models and formulas Strengthen your knowledge of Power Query and PowerPivot Learn how to create Power query and pivot table based dashboard without any formula Who Is This Course For? This Advanced Excel Models using Formulas, VBA & Power Query course is recommended to anyone interested in learning how to prepare robust Excel models using advanced formulas, Power Query and VBA. In addition, the skills gained from this training will provide excellent opportunities for career advancement. Entry Requirement This course is available to all learners of all academic backgrounds. Learners should be aged 16 or over. Good understanding of English language, numeracy and ICT skills are required to take this course. Certification After you have successfully completed the course, you will obtain an Accredited Certificate of Achievement. And, you will also receive a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy for £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why Choose Us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos and materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; United Kingdom & internationally recognized accredited qualification; Access to course content on mobile, tablet and desktop from anywhere, anytime; Substantial career advancement opportunities; 24/7 student support via email. Career Path The Advanced Excel Models using Formulas, VBA & Power Query Course provides essential skills that will make you more effective in your role. It would be beneficial for any related profession in the industry, such as: Data Analyst System Support and Reporting Analyst Introduction Course Outline and Introduction 00:04:00 Minimum Requirements for the Course 00:01:00 Prepayments Introduction 00:01:00 Prepaid Expenses Models: Resources Download Month End Date Prepaid Expenses Amortization Calculation 00:00:00 Exact Prepaid Expenses Payment Date Calculation 00:00:00 Accounting for Prepaid Expenses Prepaid Expenses Accounting Definition: Prepayments 00:03:00 Prepaid Expense Example: How Accounting works for Prepayments 00:03:00 Advantages and Disadvantages of Prepaid Expenses 00:03:00 Excel Formulas Detailed: Introduction to three Excel Models Introduction to PRO Excel Models and Formulas 00:06:00 Date Function 00:05:00 EOMONTH Function 00:04:00 DATEVALUE function 00:03:00 IF Function 00:08:00 IFS Function (Office 365 Only) 00:07:00 VLOOKUP Function 00:07:00 MATCH Function 00:05:00 INDIRECT Function 00:02:00 NAMED Ranges: Name Manager 00:03:00 Advanced Version of VLOOKUP Function 00:07:00 Formula Based Prepaid Expenses Model Introduction to Model and Control Panel Tab (Important Sheet Tab) 00:08:00 Formula Based Prepaid Expenses Model - Deep Dive (Part 1) 00:05:00 Formula Based Prepaid Expenses Model - Deep Dive (Part 2) 00:06:00 Formula Based Prepaid Expenses Model - Deep Dive (Part 3) 00:06:00 IFS Function - Month End date Prepayment calculation 00:04:00 Prepaid Expenses - Closing Balance Summary Tab (Formula Based Summary) 00:09:00 Protecting Formulas Cells and Fields in the Model 00:04:00 Calculate Prepaid Expenses Amortisation from Exact Start Date Exact Date Prepaid Amortisation calculation Intro 00:03:00 Formulas update and Model Changes for Exact Prepaid Exps Calculation 00:03:00 Formulas Update for Exact Date Prepaid Exps Amortisation (Part 1) 00:04:00 Formulas Update for Exact Date Prepaid Exps Amortisation (Part 2) 00:03:00 Formulas Update for Exact Date Prepaid Exps Amortisation (Part 3) 00:02:00 Formulas Update for Exact Date Prepaid Exps Amortisation (Part 4) 00:07:00 IFS Function - Exact Date Prepayments Amortisation 00:04:00 Data Validation Controls (Enhancing Data Input Controls with Protection) 00:10:00 Bonus: Prepayment Model with Opening Balance Calculation (Part 1) 00:08:00 Bonus: Prepayment Model with Opening Balance Calculation (Part 2) 00:09:00 Additional Material: Resources 00:00:00 Prepaid Expenses Summary with Power Query and Pivot Table Power Query and Pivot Table Prepayment Summary Table Intro 00:06:00 What is Power Query and Some Awesome Resources for Power Query learning 00:07:00 Power Query and Pivot Table Summary - Deep Dive (Part 1) 00:05:00 Power Query and Pivot Table Summary - Deep Dive (Part 2) 00:04:00 Power Query and Pivot Table Summary - Deep Dive (Part 3) 00:05:00 Power Query and Pivot Table Summary - Deep Dive (Part 4) 00:09:00 Using Array Formulas to Add Formula Protection 00:04:00 Bonus: Allocate Prepaid Expenditure Cost Centre Wise - 1 00:02:00 Bonus: Allocate Prepaid Expenditure Cost Centre Wise - 2 00:08:00 Bonus: Prepayment Model with Opening Balance Calculation (PQ and PT Version) 00:13:00 Advanced VBA Prepaid Expenses Amortisation Model Changing Macros Security in Excel 00:05:00 Complete Walkthrough - Advanced VBA Prepaid Expenses Amortisation Model 00:06:00 Bonus : New Version - Excel VBA Model for Prepayment Expenditure 00:08:00 BONUS: Dynamic Dashboard for Divisional Profit and Loss statements: Easy Way Dynamic Dashboard Overview 00:07:00 Importing Profit and Loss Statements Source Files and creating YTD P&L Sheets 00:08:00 Creating Dynamic Data Validation 00:02:00 Creating Named Ranges for Dynamic Table Arrays 00:03:00 Dynamic Date Column Headings for each Divisional PL Table 00:02:00 Dynamic Month and YTD Dashboard tables headings (PRO TIP) 00:03:00 Dynamic VLOOKUP Formula - Preparing First section of the Dashboard 00:04:00 Creating Rolling Dashboard with Dynamic VLOOKUP Function 00:08:00 IMPORTANT : Error Checking for your reports/Dashboard (PRO TIP) 00:03:00 Data Prep for Visualization: AREA Charts (Awesome trick using #NA Function) 00:05:00 Visualization: AREA Charts for Month - Revenue, Gross Profit and Net Profit 00:05:00 Visualization DONUT Charts Revenue, Gross Profit and Net Profit (Part 1) 00:03:00 Visualization DONUT Charts Revenue, Gross Profit and Net Profit (Part 2) 00:06:00 Power Query & Pivot Tables based Dashboard without any Formulas, Fully Dynamic Introduction - Formula-less Dashboard - Fully Dynamic and easily refreshed 00:05:00 Understanding the data files before building dashboard 00:02:00 Consolidating Reports with Power Query (Get & Transform) , How to install PQ 00:08:00 Dynamic File Path Trick in Power Query with Parameters (Amazing trick) 00:06:00 Conditional Cumulative totals with SUMIFS Function 00:04:00 Bonus: Conditional Cumulative totals with Power Query Custom Formula (M Code) 00:06:00 Dashboard Creation - Pivot Table showing Month and YTD KPIs division wise 00:06:00 Dashboard Creation Donuts Charts linked with Pivot Table (Replicate Charts fast) 00:08:00 Dashboard Creation - Line Charts 00:08:00 Update Dashboard with Additional Divisional Data with Few Click (Magical) 00:03:00 Thankyou Thank you 00:02:00 Ultimate Prepaid Expenditure Model (Super Bonus) 00:02:00 Resources Resources - Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query 00:00:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

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Master VLOOKUP in Excel in just 60 minutes! From menus to list comparisons, learn essential VLOOKUP skills fast.

Overview Mastering data science skills and expertise can open new doors of opportunities for you in a wide range of fields. Learn the fundamentals and develop a solid grasp of Python data science with the comprehensive Data Science with Python course. This course is designed to assist you in securing a valuable skill set and boosting your career. This course will provide you with quality training on the fundamentals of data analysis with Python. From the step-by-step learning process, you will learn the techniques of setting up the system. Then the course will teach you Python data structure and functions. You will receive detailed lessons on NumPy, Matplotlib, and Pandas. Furthermore, you will develop the skills for Algorithm Evaluation Techniques, visualising datasets and much more. After completing the course you will receive a certificate of achievement. This certificate will help you create an impressive resume. So join today! 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? This course Data Science with Python course is ideal for beginners in data science. It will help them develop a solid grasp of Python and help them pursue their dream career in the field of data science. Requirements The students will not require any formal qualifications or previous experience to enrol in this course. Anyone can learn from the course anytime from anywhere through smart devices like laptops, tabs, PC, and smartphones with stable internet connections. They can complete the course according to their preferable pace so, there is no need to rush. Career Path This course will equip you with valuable knowledge and effective skills in this area. After completing the course, you will be able to explore career opportunities in the fields such as Data Analyst Data Scientist Data Manager Business Analyst And much more! Course Curriculum 90 sections • 90 lectures • 10:19:00 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: 00:04:00 •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: 00:06:00 •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