2 QLS Endorsed Course | CPD Certified | Free PDF + Hardcopy Certificates | 150 CPD Points | Lifetime Access
Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts
Embark on a journey to uncover the labyrinthine world of digital financial security with the 'Hacked Credit and Debit Card Recovery Course'. Navigate through the depths of the web, from understanding the diverse range of websites to delving deep into the dark corridors of the internet, equipping yourself with invaluable cyber intelligence. Through this course, you'll decode various threat perceptions, familiarise yourself with card fraud intricacies, and master the art of information recovery - all tailored to ensure your digital financial transactions remain impervious to threats. Learning Outcomes Understand the fundamentals of cyber threats and their impact on digital financial transactions. Differentiate between various website types and their susceptibility to cyber-attacks. Analyse threat actors and their modus operandi in the cyber realm. Gain insights into the deep and dark web and the tools necessary for information recovery. Acquire proficiency in information handling procedures to maintain digital financial security. Why buy this Hacked Credit and Debit Card Recovery Course? 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 Hacked Credit and Debit Card Recovery Course 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 Hacked Credit and Debit Card Recovery Course for? Individuals keen on enhancing their understanding of digital financial security. Banking and finance professionals looking to fortify their defence mechanisms. Cybersecurity enthusiasts aiming to delve into card fraud detection and prevention. Internet users wanting to safeguard their online financial transactions. Tech-savvy individuals eager to explore deep and dark web intelligence. Prerequisites This Hacked Credit and Debit Card Recovery Course does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Hacked Credit and Debit Card Recovery Course was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Cyber Security Analyst: £35,000 - £55,000 Fraud Detection Analyst: £30,000 - £50,000 Dark Web Researcher: £40,000 - £65,000 Information Security Officer: £45,000 - £70,000 Threat Intelligence Specialist: £50,000 - £75,000 Financial Security Consultant: £55,000 - £80,000 Course Curriculum Unit 01: Introduction Introduction & Objective 00:01:00 Unit 02: Types of Website Types of Website 00:01:00 Surface Web 00:01:00 Deep Web 00:01:00 Dark Web 00:03:00 2016 - 2017 Profit Comparison from 5000 00:01:00 Intelligence Agency Web 00:01:00 Quantum Computers 00:01:00 Polymeric Falcighol Derivation 00:01:00 Graphical representation 00:01:00 Unit 03: Threat Perception Threat Perception 00:01:00 Threat Actor 00:01:00 Threat Actor-Compared to a Hacker Or Attacker 00:01:00 Is the Dark Net Market gone? 00:03:00 Unit 04: Card Fraud Card Fraud 00:04:00 Card-Not-Present Fraud (CNP) 00:02:00 Unit 05: Threat Ninja Threat Ninja 00:01:00 Threat Ninja Architecture 00:03:00 Adaptive Assessment 00:01:00 Secure Coat Approach 00:01:00 Secure Coat's Value Proposition 00:02:00 Challenge 00:01:00 Unit 06: Threat Actor Analysis Threat Actor Analysis 00:00:00 Kuchinoni - ATM Theft 00:01:00 Insider Threats 00:01:00 Unit 07: Cyber Security Monitoring Cyber Security Monitoring 00:01:00 Protect Your Company via DDWM 00:01:00 Unit 08: Threat Life Cycle Threat Life Cycle 00:06:00 Unit 09: Information Leakage Points Information Leakage Points 00:04:00 Unit 10: Valuable Information Valuable Information 00:09:00 Unit 11: Area of Search Area of Search 00:01:00 Sell Cards at Social Media, Messenger, etc. Groups 00:01:00 Unit 12: Deep & Dark Web Intelligence and Information Recovery Deep & Dark Web Intelligence and Information Recovery 00:01:00 Unit 13: Banking Fraud Types Banking Fraud Types 00:01:00 Card Fraud- Nilson Report 00:01:00 U.S. Card Fraud Losses 00:01:00 Card Fraud Statistics 00:05:00 Unit 14: Threat Ninja Tool Secure Coat Threat Ninja Portal 00:01:00 Threat Ninja Demo 00:05:00 Unit 15: Information Handing Procedures Information Handling Procedures 00:01:00 Card Discard Life Cycle 00:02:00 Unit 16: Course Wrap up Congratulations and Course Summary 00:03:00 Thank you! 00:01:00 Unit 17: Bonus Rise in the price of the Crypto Coin 00:06:00 Assignment Assignment - Hacked Credit and Debit Card Recovery Course 00:00:00
Level 5 QLS Endorsed Course with FREE Certificate | CPD & CiQ Accredited | 150 CPD Points | Lifetime Access
Level 5 QLS Endorsed Course with FREE Certificate | CPD & CiQ Accredited | 150CPD Points | Lifetime Access
This is a complete crash course about KNIME for beginners. Here, we will learn how to do data cleaning and data preparation without any code, using KNIME. We will also cover data visualization using Tableau and Power BI Desktop. Then we will understand the predictive analytics capabilities of KNIME and finally, cover machine learning in KNIME.
About this Training Course The LNG market is developing from a fully based market on long-term contracts, to a more flexible market based on a portfolio of contracts of different durations. The increase of LNG demand, fuelled by South Korea, Japan and several other emerging economies, are creating a base for a more flexible market, where the LNG spot market will be playing a key role. Changes in the LNG market can be identified in the following areas: development of terminals and plant sizes, increased integration throughout the supply chain, diversification of supply sources, increased contractual flexibility and increased geographical distance. This is creating the foundation for the development of the LNG spot market right here in Asia today. This 3 full-day intensive intermediate level course will give you cutting-edge knowledge needed in today's complex LNG market. Increase your knowledge and understanding of the LNG market and spot trading aspects by attending this course. Training Objectives By the end of this course, participants will be able to: Leverage on the current and global drivers of the world Natural gas and LNG markets Understand regional LNG pricing effects and who the key buyers and new sellers are Appreciate the trading structures of LNG and how to structure its risk management Understand the workings and future outlook of the Asian LNG Spot market Discover and exploit the arbitrage trading opportunities between the different markets Learn what LNG derivatives are and how it will become available for hedging and proprietary trading purposes Target Audience This course will benefit: LNG market development executives are drawn from both technical and non-technical (commercial, finance and legal) backgrounds. Participants in an LNG market development team, perhaps with expertise in one area of gas development, will benefit from the course by obtaining a good grounding of all other areas. The course is pitched at an intermediate level, although those with a basic knowledge will be able to grasp most of the concepts covered. Course Level Intermediate Trainer Your course leader is a skilled and accomplished professional with over 25 years of extensive C-level experience in the energy markets worldwide. He has strong expertise in all the aspects of (energy) commodity markets, international sales, marketing of services, derivatives trading, staff training and risk management within dynamic and high-pressure environments. He received a Master's degree in Law from the University of Utrecht in 1987. He started his career at the NLKKAS, the Clearing House of the Commodity Futures Exchange in Amsterdam. After working for the NLKKAS for five years, he was appointed as Member of the Management Board of the Agricultural Futures Exchange (ATA) in Amsterdam at the age of 31. While working for the Clearing House and exchange, he became an expert in all the aspects of trading and risk management of commodities. In 1997, he founded his own specialist-consulting firm that provides strategic advice about (energy) commodity markets, trading and risk management. He has advised government agencies such as the European Commission, investment banks, major utilities, and commodity trading companies and various energy exchanges and market places in Europe, CEE countries, North America and Asia. Some of the issues he has advised on are the development and implementation of a Risk Management Framework, investment strategies, trading and hedging strategies, initiation of Power Exchanges (APX) and other trading platforms, the set-up of (OTC) Clearing facilities, and feasibility and market studies like for the Oil, LNG and the Carbon Market. The latest additions are (Corporate) PPAs and Artificial Intelligence for energy firms. He has given numerous seminars, workshops and (in-house) training sessions about both the physical and financial trading and risk management of commodity and carbon products. The courses have been given to companies all over the world, in countries like Japan, Singapore, Thailand, United Kingdom, Germany, Poland, Slovenia, Czech Republic, Malaysia, China, India, Belgium and the Netherlands. He has published several articles in specialist magazines such as Commodities Now and Energy Risk and he is the co-author of a book called A Guide to Emissions Trading: Risk Management and Business Implications published by Risk Books in 2004. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable Accreditions And Affliations
Data scraping is used to get the data available on different websites and APIs. This also involves automating the web flows to extract the data from different web pages. Data Scraping and Data Mining with Python is a well-designed course for beginners to develop a solid groundwork for the skills necessary.