1072 Data Analysis courses delivered Online

Anti-Money Laundering (AML): This comprehensive Anti-Money Laundering (AML) course is designed for individuals interested in safeguarding organizations against financial crime. Through up-to-date knowledge and practical guidance, you will be trained in the essential skills required to identify and prevent suspicious activities within any organization. With step-by-step instructions on conducting client risk assessments, this course equips you with a strong foundation in AML procedures.

Discover the fascinating world of decentralized trading with Python and DYDX. Build a sophisticated trading bot, harness statistical arbitrage techniques, and automate your trading strategies on the AWS cloud. Gain the skills to navigate the cryptocurrency market and achieve consistent profitability in this comprehensive and hands-on course.

Course Overview Do you want to earn money passively from home? DO you want to drive more traffic to your website? Google AdWords is a great way for that. Learn how you can use Google ad services to get ahead of your competitors and drive traffic towards your business from this Learn Google AdWords and Earn Passive income with PPC course and boost your sales in no time. This course will teach you to how you can make a profit out of per click of your visitors. In this Learn Google AdWords and Earn Passive income with PPC course, you will learn how to set up an AdWords account, theories, keyword research, conversation tracking, sales and revenue tracking. You'll also understand the importance of quality scores, data analysis and understanding customer psychological level from this course. This course will help you understand the steps of monetizing your website from scratch. Learning Outcomes Be able to drive traffic to your website or landing page Create and optimize your own profitable Google AdWords campaigns Learn how to advertise your products and services online Increase sales to your website using AdSense Use conversion tracking to determine the value of your ad campaign Monetize more than 6 billion daily searches on Google Be able to remarket to your website visitors Who is this course for? This course is for those who want to learn the functions of Adword and earn money from Google ad services. This course will help you to learn how you can earn money passively using AdWord step by step. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £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/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path Learn Google AdWords and Earn Passive income with PPC is a useful qualification to possess and would be beneficial for any related profession or industry such as: Digital Marketers Influencers Content Creators YouTubers Module 01: Introduction to Google Ads Welcome to Google Ads Masterclass! 00:13:00 Link to Isaac Rudansky's Digital Advertising Superstars Facebook Group 00:05:00 How to Make the Most of This Course, Plus a Sneak Peek of What's to Come! 00:20:00 Google Ads Formula Calculator 00:14:00 AdWords Formula Calculator I Built For You 00:05:00 What is Google Ads? 00:12:00 Where do Google Ads Show Up? 00:13:00 Complimentary Adventure Media Account Audit (exclusions apply) 00:06:00 Module 02: Creating and Setting Up Our First Google Ads Account Download Course Slides! 00:05:00 Creating Your First Google Ads Account 00:09:00 Understanding the Google Ads Account Hierarchy 00:08:00 Using Your Website Navigational Structure to Structure Your Google Ads Campaigns 00:20:00 Understanding Network Settings 00:14:00 Understanding Location Targeting 00:12:00 Configuring Location Targeting in Google Ads 00:10:00 Viewing Location Reports in Google Ads 00:15:00 Understanding Advanced Location Options 00:16:00 Setting and Configuring Languages 00:04:00 Setting Your Daily Budget and Understanding How Daily Budgets Work in Google Ads 00:13:00 Finding Your Hourly Reports in the Google Ads Interface 00:06:00 Using Google's Default Bid Strategy (Clicks) And Optional Max CPC Bid Limit 00:06:00 Bidding Strategies: Target Search Page Location 00:06:00 Bidding Strategies: Target ROAS 00:10:00 Bidding Strategies: Target CPA 00:05:00 Bidding Strategies: Target Outranking Share 00:08:00 Bidding Strategies: Maximize Clicks 00:05:00 Bidding Strategies: Enhanced CPC Bidding 00:05:00 Bidding Strategies: Manual CPC Bidding 00:05:00 Campaign Start and End Dates 00:02:00 Introduction to Dynamic Search Ads! 00:08:00 Understanding Sitelink Extensions 00:14:00 Callout Extensions 00:05:00 Call Extensions 00:08:00 Structured Snippet Extensions 00:06:00 App Extensions 00:02:00 Message Extensions 00:09:00 Location Extensions 00:10:00 Location Setting Exercise 00:05:00 Promotion Extensions 00:10:00 Price Extensions 00:12:00 Understanding Ad Rotation Settings 00:05:00 The Basics of Ad Scheduling 00:11:00 Understanding the Basics of Device Targeting 00:15:00 Understanding Campaign URL Options 00:07:00 Module 03: Structuring Your Ad Groups Like A Professional Ad Group Structure Basics and Organization 00:14:00 Ad Group Structure Ideas 00:07:00 Creating Our First Ad Group in Google Ads 00:09:00 Module 04: How To Write Killer Ads in Google Ads! The Anatomy of Google Text Ads 00:07:00 Compliance in Google Text Ads 00:06:00 Requesting a Manual Review of Your Ads and Expediting the Process 00:03:00 Best Practices for Successful Text Ads 00:14:00 Real-Life Case Ad Copy Case Study: Medical Equipment Company 00:15:00 The BJ Fogg Behavioral Model 00:39:00 Creating Our First Ad in Google Ads 00:13:00 Module 05: Setting Up Your AdWords Billing Configuring Your Billing Details in Google Ads 00:05:00 Module 06: Keywords in Depth - The Heartbeat of Your Account Keyword Basics: Keywords vs Queries 00:09:00 The Basics of Keyword Research 00:11:00 The Basics of Keyword Planning 00:13:00 The Basics of Keyword Organization 00:07:00 Understanding Keyword Match Types 00:12:00 Keyword Match Types: Broad Match 00:09:00 Keyword Match Types: Broad Match Modified 00:06:00 Keyword Match Types: Phrase Match 00:07:00 Keyword Match Types: Exact Match 00:12:00 Keyword Match Types: Negative Match 00:12:00 Using the Search Term Report to Find Negative Keywords Part 1 00:15:00 Using the Search Term Report to Find Negative Keywords Part 2 00:17:00 Understanding Negative Keyword Lists 00:12:00 Traffic Sculpting: Negative Keywords at the Ad Group Level 00:18:00 Adding Negative Keywords at The Ad Group Level 00:09:00 Traffic Sculpting Using OPTMYZR 00:07:00 Keyword Research: Google Suggestions, Google Related Searches and Autocomplete 00:14:00 Using Additional Research Tools to Get Negative Keyword Ideas 00:12:00 Keyword Research: Using the Google Keyword Planner 1 00:20:00 Keyword Research: Using the Google Keyword Planner 2 00:16:00 Keyword Research: Downloading Keyword Ideas from the Google Keyword Planner 00:16:00 Keyword Planning: The 6 Main Ways People Communicate With Search Engines 00:17:00 Keyword Planning: Understanding the Buyer Funnel 00:12:00 Keyword Planning: What Keywords Can Teach Us About Buying Intent 00:12:00 Keyword Planning: Using SEM Rush to Get Volume and Cost Estimates 00:18:00 Keyword Planning: Using SEM Rush to Get Keyword Ideas from Your Competitors 00:19:00 Keyword Planning: Using Google Keyword Planner to Get Volume & Cost Estimates 00:17:00 Keyword Organization: Getting Keywords Into Excel & Understanding Keyword Themes 00:17:00 Keyword Organization: Formatting Keywords in Excel 00:12:00 Keyword Organization: Using Pivot Tables to Visualize Your Campaign Structure 00:12:00 Keyword Organization: Using Mergewords to Generate Keyword Lists 00:14:00 Keyword Bidding Basics: Setting Your Initial Max CPC Bids 00:20:00 Module 07: Account Structure - How To Structure Ad Groups Like A pro Account Structure: How To Create A New Ad Group Within Your Campaign 00:07:00 Importing Your Keyword Lists From Excel Into Your New Ad Group 00:11:00 Creating Multiple, Relevant Ads For Your New Ad Groups 00:13:00 How To Navigate Between Ad Groups, Keywords and Ads Within A Campaign 00:08:00 Module 08: The Incredible Dynamics Of The AdWords Auction Introduction To The AdWords Auction 00:20:00 Understanding Quality Score: Click Through Rate And Ad Relevancy 00:15:00 Understanding Quality Score: Landing Page Quality 00:07:00 Understanding Ad Rank and How It Is Calculated 00:12:00 When You Could Ignore Low-Quality Scores (and when you can't!) 00:09:00 Advanced Techniques: Diagnosing Low-Quality Score With Excel Pivot Tables (1/3) 00:08:00 Advanced Techniques: Diagnosing Low-Quality Score With Excel Pivot Tables (2/3) 00:11:00 Advanced Techniques: Diagnosing Low-Quality Score With Excel Pivot Tables (3/3) 00:07:00 Module 09: Expanding And Refining Your Campaigns Navigating The AdWords Dashboard 00:16:00 How To Edit, Pause And Enable Keywords, Ad Groups and Campaigns 00:15:00 Editing The Essential Campaign Settings 00:06:00 How To Create New Campaigns That Will Improve Your Results 00:15:00 How To Use Your Website To Make The Best Campaigns Possible 00:16:00 How To Set Up Powerful Custom Schedules For Your Campaigns 00:12:00 Understanding Bid Adjustments And Using Them To Enhance Your Custom Schedules 00:12:00 Module 10: Negative Keywords - Your Greatest Ally Understanding Negative Keywords In-Depth 00:14:00 Using Broad, Phrase and Exact Match With Your Negative Keywords 00:07:00 Adding and Removing Negative Keywords and Negative Keyword Lists 00:20:00 Module 11: Making Your Ads Unstoppable With Multiple Ad Extnesions Introduction To Ad Extensions 00:06:00 The Benefits Of Using Ad Extensions 00:08:00 Different Types Of Ad Extensions and Best Practices 00:06:00 Adding Sitelink Extensions 00:08:00 Configuring Your Sitelink Extensions For The Best Results 00:11:00 Adding Callout Extensions And Phone Extensions 00:08:00 Module 12: Remarketing - Your Secret Weapon To Converting Like A Boss The 5 Primary Forms Of Remarketing 00:16:00 Realizing The Benefits And Importance Of Remarketing 00:13:00 How To Create And Add Your Remarketing Tag 00:09:00 Creating Your First Remarketing Audience 00:13:00 Configuring Your Remarketing Campaign Settings 00:14:00 Module 13: Keeping Track Of Profits With Conversion Tracking Understanding The Basics Of Conversion Tracking 00:14:00 Exploring The Different Conversion Actions Visitors Take On Your Site 00:14:00 Setting Up Conversion Tracking For Form Submissions 00:18:00 Generating And Installing Your Conversion Tracking Tag 00:09:00 Understanding The Basics Of Phone Call Tracking 00:09:00 Setting Up Phone Call Tracking And Understanding How To Analyze Conversion Data 00:10:00 Module 14: Profitable Bidding Strategies Return On Investment (ROI) vs Return On Ad Spend (ROAS)_ Important Distinction 00:15:00 How To Mathematically Calculate ROI and ROAS 00:09:00 Calculating Max CPC Bids From Your Conversion Rate And Conversion Value 00:12:00 Calculating Profitable Keyword Bids Based On Revenue Per Click 00:09:00 Module 15: Using AdWords Scripts To Enhance Performance and Increase Optimization Speed Introduction To AdWords Scripts - What Are Scripts 00:05:00 Bidding To Average Position AdWords Script (Part 1) 00:12:00 Bidding To Average Position AdWords Script (Part 2) 00:14:00 Module 16: Conclusion ... Goodbye For Now! Conclusion 00:03:00 Module 17: Bonus Material! Part 1 Understanding Search Queries and What We Learn From Searcher Languagage 00:18:00 Part 2 Accessing The Search Query Report and Understanding Long Tail Keywords 00:18:00 Part 3 Qualifying Your Ad Text And How To A_B Split Test Your Ads 00:23:00 Calculating Profitable Keyword Bids Based On Revenue Per Click 00:09:00

This video course will help you learn all the basic and advanced concepts of Microsoft Excel 2019. You'll start with Excel basics and slowly move to the advanced concepts in Excel. Each section is accompanied by an exercise at the end to practice what you have learned.

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Utilise digital marketing tools and techniques, including social media marketing, email marketing, and SEO, to enhance brand visibility and reach. Create and execute compelling content marketing campaigns that engage target audiences and boost conversions. Analyze sales data, marketing performance, and market trends to optimize marketing efforts and improve decision-making processes. Manage customer relationships and improve communication through relationship marketing to increase sales and customer retention. 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You will learn how to create impactful marketing campaigns, optimize brand visibility, and analyze market data to make informed decisions. Whether you're looking to advance in your current role or pursue a new career in marketing management, this course will give you the tools to succeed in today’s competitive landscape. Enrol in this Sales and Marketing Training course today and start your journey to becoming a successful marketing professional or sales expert! ★★★ Course Curriculum of Sales and Marketing Training Bundle ★★★ Course 01: Sales & Selling Management Course Module 01: Understanding the Talk Module 02: Getting Prepared to Make the Call Module 03: Creative Openings Module 04: Making Your Pitch Module 05: Handling Objections Module 06: Sealing the Deal Module 07: Following Up Module 08: Setting Goals Module 09: Managing Your Data Module 10: Using a Prospect Board Course 02: Sales Negotiation Training Course 03: Telesales Executive Training Course 04: Marketing Fundamentals Course 05: Strategic Planning and Analysis for Marketing Course 06: Digital Marketing Course 07: SEO - Search Engine Optimisation Level 5 Course 08: Retail Management - Level 5 Course 09: Customer Relationship Management Course 10: Sales: Psychology of Customers Course 11: Basic Product Management Course 12: Product Photography Course 13: Commercial Law 2021 Course 14: Public Speaking and Presentation Skill Course How will I get my Certificate? After successfully completing the course, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free Hard Copy Certificate: Free CPD 140 CPD hours / points Accredited by CPD Quality Standards Requirements There is no time limit for completing thiscourse; it can be studied in your own time at your own pace. Career path Elevate your professional journey with Sales and Marketing Training. This comprehensive course opens doors to a wide range of career opportunities in the dynamic world of marketing. 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Discover Microsoft Fabric's architecture, master Data Engineering with OneLake and Spark, and elevate your skills in data warehousing and real-time processing. Compare SQL and KQL for better insights, and improve storytelling using Power BI. Finally, you will end with practical data science techniques and data management methods.

Criminal Intelligence: Criminal Intelligence Analyst Course Online Enhance Your Career as a Criminal Intelligence: Criminal Intelligence Analyst Course with Our Comprehensive Course! Are you passionate about fighting crime and uncovering hidden patterns? Do you have a keen eye for detail and a strong analytical mindset? If so, our Criminal Intelligence: Criminal Intelligence Analyst Course is the perfect opportunity for you to unlock a rewarding and exciting career in law enforcement! As crime becomes more sophisticated and complex, the demand for highly skilled Criminal Intelligence: Criminal Intelligence Analyst Course is at an all-time high. This comprehensive Criminal Intelligence: Criminal Intelligence Analyst Course is designed to equip you with the knowledge and skills necessary to excel in this dynamic field. Whether you're a recent graduate or a seasoned professional looking to transition into a new role, our Criminal Intelligence: Criminal Intelligence Analyst Course offers the perfect blend of theoretical knowledge and practical training to help you succeed. Our Criminal Intelligence: Criminal Intelligence Analyst Course curriculum has been meticulously crafted by industry experts with extensive experience in criminal : criminal intelligence analysis. Through this Criminal Intelligence: Criminal Intelligence Analyst Course you will gain a deep understanding of the principles and techniques used in gathering, analyzing, and interpreting data to support investigations and solve complex criminal cases. From mastering the fundamentals of criminal law to learning advanced data analysis methodologies, our Criminal Intelligence: Criminal Intelligence Analyst Course covers it all. Main Course: Criminal Intelligence Analyst Course Free Course: Course 01: Forensic Science [ Note: Free PDF certificate as soon as completing the Criminal Intelligence: Criminal Intelligence Analyst Course] Criminal Intelligence: Criminal Intelligence Analyst Course Online This Criminal Intelligence: Criminal Intelligence Analyst Course consists of 09 modules. Assessment Method of Criminal Intelligence: Criminal Intelligence Analyst Course After completing Criminal Intelligence: Criminal Intelligence Analyst 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 Criminal Intelligence: Criminal Intelligence Analyst Course After completing the Criminal Intelligence: Criminal Intelligence Analyst 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? Criminal Intelligence: Criminal Intelligence Analyst Course Online This Criminal Intelligence: Criminal Intelligence Analyst Course is open to everyone. Requirements Criminal Intelligence: Criminal Intelligence Analyst Course Online To enrol in this Criminal Intelligence: Criminal Intelligence Analyst Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Criminal Intelligence: Criminal Intelligence Course. Be energetic and self-motivated to complete our Criminal Intelligence: Criminal Intelligence Course. Basic computer Skill is required to complete our Criminal Intelligence: Criminal Intelligence Course. If you want to enrol in our Criminal Intelligence: Criminal Intelligence Analyst Course, you must be at least 15 years old. Career path Criminal Intelligence: Criminal Intelligence Analyst Course Online

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

This course covers the important topics needed to pass the AWS Certified Data Analytics-Specialty exam (AWS DAS-C01). You will learn about Kinesis, EMR, DynamoDB, and Redshift, and get ready for the exam by working through quizzes, exercises, and practice exams, along with exploring essential tips and techniques.

Data dashboards provide key information to stakeholders so that they can make informed decisions. While there are plenty of software solutions for building these essential data products, there is much less guidance on how to design dashboards to meet the diverse needs of users.  This course is for anyone who is building or implementing dashboards, and wants to know more about design principles and best practice. You could be using business intelligence software (such as Power BI or Tableau), or implementing bespoke solutions.  The course will give your team the ability to evaluate user needs and levels of understanding, make informed decisions about chart selections, and make effective use of interactivity dynamic data.  We’ll work with you before the course to ensure that we understand your organisation and what you’re hoping to achieve.  Sample learning content  Session 1: Data with a purpose Understanding the different types of dashboard. Information overload and other common dashboard pitfalls. Assessing user needs and levels of data fluency. Session 2: Planning a dashboard Assessing diverse user needs and levels of data fluency. Taking a User Experience (UX) approach to design and navigation. Applying an interative and collaborative approach to onboarding. Session 3: Graphs, charts and dials  Understanding how graphical perception informs chart choices. Making intelligent design choices to help users explore. Design principles for layout and navigation. Session 4: Using interactivity  Making effective use of filters to slice and dice data sets. Using layers of information to enable drilldown data exploration. Complenting dashboards with automated alerts and queries. Delivery We deliver our courses over Zoom, to maximise flexibility. The training can be delivered in a single day, or across multiple sessions. All of our courses are live and interactive – every session includes a mix of formal tuition and hands-on exercises. To ensure this is possible, the number of attendees is capped at 16 people.  Tutor Alan Rutter is the founder of Fire Plus Algebra. He is a specialist in communicating complex subjects through data visualisation, writing and design. He teaches for General Assembly and runs in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, and numerous local government and emergency services teams. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualisation courses. He oversaw the iPad edition launches of Wired, GQ, Vanity Fair and Vogue in the UK, and has worked with Condé Nast International as product owner on a bespoke digital asset management system for their 11 global markets. Testimonial “Alan was great to work with, he took us through the concepts behind data visualisation which means our team is now equipped for the future. He has a wide range of experience across the topic that is delivered in a clear, concise and friendly manner. We look forward to working with Alan again in the future.” John Masterson | Chief Product Officer | ImproveWell