4021 Courses delivered Online

Duration 3 Days 18 CPD hours This course is intended for This course is designed for Pardot Marketers and Salesforce Administrators responsible for designing, building, and implementing marketing workflows and reports in the Pardot Lightning App. It's also for Business Users looking to learn more about the Pardot Lightning App. This course is a great foundation builder for anyone looking to take the Salesforce Pardot Specialist Certification Exam. Overview When you complete this course, you will be able to: Enable the Pardot Lightning App. Explain the relationship created between Pardot and Salesforce once the Pardot Lightning App has been enabled. Generate leads with Pardot Lightning App's various lead generation tools including forms, landing pages, and custom redirects. Manage leads with Pardot Lightning App's lead management tools including page actions, automation rules, segmentation rules, dynamic lists, and completion actions. Engage leads with Pardot Lightning App's lead engagement tools including email, personalization, dynamic content, and Engagement Studio. Qualify leads with Pardot Lightning App's scoring and grading functionality. Interpret data generated via Pardot Lightning App's reporting capabilities. Design and execute successful end-to-end marketing workflows using the Pardot Lightning App. Discover how to drive more qualified leads, nurture prospects through the sales cycle, and sell more effectively using the Pardot Lightning App. In this 3-day class, Pardot experts will show you how to design and implement marketing workflows in the Pardot Lightning App to make data-driven decisions and drive your company?s business forward. Learn how to create and automate dynamic emails, generate and qualify leads, and leverage reports and data to boost sales. Course Introduction Review Course Objectives Set Learner Expectations Review Housekeeping Items Review Additional Course Resources Explore Course Case Study Salesforce Integration Understand the Pardot-Salesforce Relationship Sync Data Between Salesforce and Pardot Enable the Pardot Lightning App in Salesforce Create Custom Fields Review Salesforce Campaigns Administration Create a Pardot Dashboard Authenticate Your Email Sending Domains Sync with Third-Party Applications Using Connectors Restore Assets from the Recycle Bin Create and Assign Users and User Groups Understand Usage Governance Visitors and Prospects Understand Pardot Visitors Understand Pardot Prospects List Management Create List Types Organize Prospects Using Static Lists Test Emails Using Test Lists Personalization and Email Marketing Personalize Your Emails with HML and Advanced Dynamic Content Automate Email Marketing Create Email Templates See What Works Best for Your Audience Using AB Testing Track Email Performance Using Email Reports Forms and Landing Pages Capture Leads with Forms Convert Visitors to Leads Using Landing Pages Track Leads with Forms and Landing Page Reports Track Clicks Using Custom Redirects Create Custom Redirect Reports Lead Management Trigger Page Actions Automate Actions from a Marketing Element Using Completion Actions Create a List of Prospects and Apply a Segmentation Action Using Segmentation Rules Create Repeatable, Criteria-Based Automation Rules Create Dynamic Lists Choose an Automation Tool Lead Qualification Understand Prospect Scoring Grade Prospects Based on Profiles Lead Nurturing Build an Engagement Program Create Engagement Program Reports Additional course details: Nexus Humans Salesforce Drive Sales with the Pardot Lightning App (PDX101) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Salesforce Drive Sales with the Pardot Lightning App (PDX101) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This class is ideal for Salesforce Certified Administrators and Platform Developers responsible for developing and managing Industries CPQ applications, including catalogs and pricing. It's also designed for solution architects and technical architects looking to understand the full capabilities of Industries CPQ in order to formulate industry-specific solutions. This class is also a great foundation builder for anyone looking to earn the Salesforce Certified Industries CPQ Developer credential. Overview When you complete this course, you will be able to: Create 'perfect' orders using order capture and asset-based ordering functionality. Define products and product bundles in the shared catalog. Use pricing components to support simple and complex pricing strategies. Create promotions and discounts to adjust pricing for a limited time. Use rules to ensure the right products are available to the right customers at the right price. Build ordering and quoting solutions using Industries Digital Commerce & CPQ APIs. xplore how to develop Configure, Price, Quote (CPQ) solutions using Industries CPQ. In this class, our Industries CPQ experts will show you how to configure CPQ solutions that ensure your customers get the right products and the right prices at the right time. You?ll learn how to set up and manage products and prices, leverage promotions and rules to drive action, and build a guided experience declaratively using Industries Digital Commerce and CPQ APIs.Note: This class focuses on Industries CPQ, previously known as Vlocity CPQ, and does not cover Salesforce CPQ. Introduction Explore Communications, Media, and Energy and Utilities Clouds and Industries CPQ Understand the Industries CME Data Model Order Capture Create and Configure Orders Using the Cart Work with MACD and ABO Orders Cancel an Order Create Orders with Non-Assetizable Products Configure Data Movement Across Line Items Using Field Mapper Enterprise Product Catalog Create Attributes and Picklists Create Object Types and Learn Inheritance Architecture Create Products Set Product Attribute Metadata and Override Attribute Defaults Create Product Bundles and Define Product Cardinality Work with Product Lifecycle Dates Manage the Shared Catalog?s Platform Cache Pricing Configure One-Time and Recurring Prices Define Price Lists and Child Price Lists Implement Base and Bundled Prices Configure Time Plans and Policies Configure Advanced Pricing Strategies such as Attribute-Based Pricing and Usage Pricing Promotions and Discounts Determine the Difference Between Products, Product Bundles, and Promotions Compare Pricing Adjustments and Overrides Create Promotions for Existing Products Adjust Prices and Time Plans Create Contextual Discounts for Orders, Accounts, and Contracts Identify the Best Type of Pricing Adjustment Given a Scenario Rules Build Context Rules Components Create and Apply Context Rules to Products, Promotions, Price Lists, and Price List Entries Create Product Relationships to Recommend, Exclude, or Require other Products Create Advanced Rules to Modify Product Attributes During Order Capture Create Advanced Rules to Auto-Add Products to the Cart Identify the Best Type of Rule to Use Given a Scenario Guided Selling Customize a Guided LWC Interaction for Purchasing Products Explore Industries Digital Commerce LWC, SDK, and Cacheable APIs Learn About CpqAppHandler Service, Its Methods, and Cart-Based APIs Additional course details: Nexus Humans Salesforce Build CPQ Solutions for Industries (IPQ435) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Salesforce Build CPQ Solutions for Industries (IPQ435) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

This comprehensive course dives deep into Oracle database RAC administration, spanning 12c and 19c versions. Gain practical skills in architecture, installation, tuning, upgrading, mastering backup, recovery, dynamic services, load balancing, patching, Flex Clusters, and more. Discover advanced techniques through hands-on practice videos.

Register on the SQL NoSQL Big Data and Hadoop today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The SQL NoSQL Big Data and Hadoop is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The SQL NoSQL Big Data and Hadoop Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the SQL NoSQL Big Data and Hadoop, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Section 01: Introduction Introduction 00:07:00 Building a Data-driven Organization - Introduction 00:04:00 Data Engineering 00:06:00 Learning Environment & Course Material 00:04:00 Movielens Dataset 00:03:00 Section 02: Relational Database Systems Introduction to Relational Databases 00:09:00 SQL 00:05:00 Movielens Relational Model 00:15:00 Movielens Relational Model: Normalization vs Denormalization 00:16:00 MySQL 00:05:00 Movielens in MySQL: Database import 00:06:00 OLTP in RDBMS: CRUD Applications 00:17:00 Indexes 00:16:00 Data Warehousing 00:15:00 Analytical Processing 00:17:00 Transaction Logs 00:06:00 Relational Databases - Wrap Up 00:03:00 Section 03: Database Classification Distributed Databases 00:07:00 CAP Theorem 00:10:00 BASE 00:07:00 Other Classifications 00:07:00 Section 04: Key-Value Store Introduction to KV Stores 00:02:00 Redis 00:04:00 Install Redis 00:07:00 Time Complexity of Algorithm 00:05:00 Data Structures in Redis : Key & String 00:20:00 Data Structures in Redis II : Hash & List 00:18:00 Data structures in Redis III : Set & Sorted Set 00:21:00 Data structures in Redis IV : Geo & HyperLogLog 00:11:00 Data structures in Redis V : Pubsub & Transaction 00:08:00 Modelling Movielens in Redis 00:11:00 Redis Example in Application 00:29:00 KV Stores: Wrap Up 00:02:00 Section 05: Document-Oriented Databases Introduction to Document-Oriented Databases 00:05:00 MongoDB 00:04:00 MongoDB Installation 00:02:00 Movielens in MongoDB 00:13:00 Movielens in MongoDB: Normalization vs Denormalization 00:11:00 Movielens in MongoDB: Implementation 00:10:00 CRUD Operations in MongoDB 00:13:00 Indexes 00:16:00 MongoDB Aggregation Query - MapReduce function 00:09:00 MongoDB Aggregation Query - Aggregation Framework 00:16:00 Demo: MySQL vs MongoDB. Modeling with Spark 00:02:00 Document Stores: Wrap Up 00:03:00 Section 06: Search Engines Introduction to Search Engine Stores 00:05:00 Elasticsearch 00:09:00 Basic Terms Concepts and Description 00:13:00 Movielens in Elastisearch 00:12:00 CRUD in Elasticsearch 00:15:00 Search Queries in Elasticsearch 00:23:00 Aggregation Queries in Elasticsearch 00:23:00 The Elastic Stack (ELK) 00:12:00 Use case: UFO Sighting in ElasticSearch 00:29:00 Search Engines: Wrap Up 00:04:00 Section 07: Wide Column Store Introduction to Columnar databases 00:06:00 HBase 00:07:00 HBase Architecture 00:09:00 HBase Installation 00:09:00 Apache Zookeeper 00:06:00 Movielens Data in HBase 00:17:00 Performing CRUD in HBase 00:24:00 SQL on HBase - Apache Phoenix 00:14:00 SQL on HBase - Apache Phoenix - Movielens 00:10:00 Demo : GeoLife GPS Trajectories 00:02:00 Wide Column Store: Wrap Up 00:04:00 Section 08: Time Series Databases Introduction to Time Series 00:09:00 InfluxDB 00:03:00 InfluxDB Installation 00:07:00 InfluxDB Data Model 00:07:00 Data manipulation in InfluxDB 00:17:00 TICK Stack I 00:12:00 TICK Stack II 00:23:00 Time Series Databases: Wrap Up 00:04:00 Section 09: Graph Databases Introduction to Graph Databases 00:05:00 Modelling in Graph 00:14:00 Modelling Movielens as a Graph 00:10:00 Neo4J 00:04:00 Neo4J installation 00:08:00 Cypher 00:12:00 Cypher II 00:19:00 Movielens in Neo4J: Data Import 00:17:00 Movielens in Neo4J: Spring Application 00:12:00 Data Analysis in Graph Databases 00:05:00 Examples of Graph Algorithms in Neo4J 00:18:00 Graph Databases: Wrap Up 00:07:00 Section 10: Hadoop Platform Introduction to Big Data With Apache Hadoop 00:06:00 Big Data Storage in Hadoop (HDFS) 00:16:00 Big Data Processing : YARN 00:11:00 Installation 00:13:00 Data Processing in Hadoop (MapReduce) 00:14:00 Examples in MapReduce 00:25:00 Data Processing in Hadoop (Pig) 00:12:00 Examples in Pig 00:21:00 Data Processing in Hadoop (Spark) 00:23:00 Examples in Spark 00:23:00 Data Analytics with Apache Spark 00:09:00 Data Compression 00:06:00 Data serialization and storage formats 00:20:00 Hadoop: Wrap Up 00:07:00 Section 11: Big Data SQL Engines Introduction Big Data SQL Engines 00:03:00 Apache Hive 00:10:00 Apache Hive : Demonstration 00:20:00 MPP SQL-on-Hadoop: Introduction 00:03:00 Impala 00:06:00 Impala : Demonstration 00:18:00 PrestoDB 00:13:00 PrestoDB : Demonstration 00:14:00 SQL-on-Hadoop: Wrap Up 00:02:00 Section 12: Distributed Commit Log Data Architectures 00:05:00 Introduction to Distributed Commit Logs 00:07:00 Apache Kafka 00:03:00 Confluent Platform Installation 00:10:00 Data Modeling in Kafka I 00:13:00 Data Modeling in Kafka II 00:15:00 Data Generation for Testing 00:09:00 Use case: Toll fee Collection 00:04:00 Stream processing 00:11:00 Stream Processing II with Stream + Connect APIs 00:19:00 Example: Kafka Streams 00:15:00 KSQL : Streaming Processing in SQL 00:04:00 KSQL: Example 00:14:00 Demonstration: NYC Taxi and Fares 00:01:00 Streaming: Wrap Up 00:02:00 Section 13: Summary Database Polyglot 00:04:00 Extending your knowledge 00:08:00 Data Visualization 00:11:00 Building a Data-driven Organization - Conclusion 00:07:00 Conclusion 00:03:00 Resources Resources - SQL NoSQL Big Data And Hadoop 00:00:00

The course starts with requirements gathering and ends with implementation, which are the two main elements of software development. Through this course, you will learn to use UML diagrams to analyze and design classes and to highlight relationships between the classes. You will also learn to implement and program the design in C++, C#, and Java.

Unlock the power of suggestion with our masterclass on the basics of good suggestion therapy. Designed for both beginners and seasoned practitioners, this course delves into the core principles that make suggestion therapy a potent tool for personal growth, healing, and behavioral change.

Parts therapy is a therapeutic approach used to address inner conflicts, reconnect with oneself, and foster personal growth. It is especially effective for resolving behavioral challenges, trauma, and emotional fragmentation. Rooted in Paul Federn's 1952 work on ego states, this technique involves identifying and working with "parts" of an individual's subconscious to achieve harmony and integration.

Embark on a transformative journey with our Diet and Nutrition Coach Certification course, designed to equip you with the expertise needed to excel in the dynamic field of nutrition coaching. Delve into the intricate realm of nutrition theory, energy metabolism, and food digestion as you hone your skills to become a proficient nutrition coach. Whether you're aspiring to launch a rewarding career or enhance your knowledge, our comprehensive curriculum caters to beginners and advanced learners alike, ensuring a seamless learning experience. As you immerse yourself in this course, you'll unravel the complexities of working with clients, mastering the art of assisting them in weight loss and muscle building journeys. From decoding famous diets to crafting optimal nutrition plans for athletes, you'll gain invaluable insights into the diverse facets of nutrition coaching. With the flexibility of online learning, our UK-based programme opens doors to endless opportunities, empowering you to become a sought-after fitness and nutrition coach in your locality or beyond. Elevate your expertise with our online nutrition coach certification, tailored to meet the demands of the ever-evolving wellness industry. Join our community of learners and embark on a transformative journey towards becoming a certified nutrition coach, equipped with the knowledge and skills to make a meaningful impact on individuals' health and well-being. Learning Outcomes: Master the fundamental principles of nutrition theory and energy metabolism. Develop proficiency in crafting personalised nutrition plans for clients to aid in weight loss and muscle building. Acquire in-depth knowledge of various diets and supplements, enhancing your ability to cater to diverse client needs. Hone your communication and coaching skills to effectively support clients in achieving their health goals. Gain practical experience through case studies and client interactions, preparing you for real-world scenarios as a nutrition coach. Why buy this Diet And Nutrition Coach Certification? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Certification After studying the course materials of the Diet And Nutrition Coach Certification: Beginner To Advanced 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 Diet And Nutrition Coach Certification course for? Individuals passionate about health and wellness. Fitness enthusiasts seeking to expand their expertise. Health professionals aiming to integrate nutrition coaching into their practice. Career changers aspiring to enter the nutrition coaching industry. Anyone interested in understanding the science behind nutrition and its practical applications. Prerequisites This Diet And Nutrition Coach Certification: Beginner To Advanced does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Diet And Nutrition Coach Certification: Beginner To Advanced 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 Nutrition Coach: £20,000 - £35,000 per annum Fitness and Nutrition Coach: £25,000 - £40,000 per annum Online Nutrition Coach UK: £20,000 - £45,000 per annum Online Nutrition Coaching Centre Oowner: Earnings vary based on experience and location. Course Curriculum Introduction Introduction & What You Will Learn 00:03:00 How To Get Your Certificate 00:01:00 The Roles & Responsibilitites Of A Diet Coach 00:02:00 Nutrition Theory What Is Nutrition 00:01:00 Meal Planning Explained 00:04:00 Calories Explained 00:04:00 Macronutrients Explained 00:01:00 What Is Protein: Explained 00:02:00 How Much Protein Does Your Body Need 00:04:00 What Is Dietary Fat: Explained 00:03:00 How Much Fat Does Your Body Need 00:04:00 What Are Carbohydrates: Explained 00:03:00 The Different Types Of Carbs 00:05:00 How Much Protein Does Your Body Need 00:04:00 Meal Timing Explained 00:01:00 When & How Often Should You Consume Protein 00:04:00 When & How Often Should You Consume Carbs 00:02:00 When & How Often Should You Consume Fat 00:01:00 Food Sources Explained 00:02:00 Protein Composition 00:02:00 Carbohydrate Composition 00:03:00 Fat Composition 00:01:00 Energy Metabolism Energy Metabolism Explained 00:02:00 Aerobic vs Anaerobic Energy Metabolism 00:02:00 Food Digestion Digestion Introduction 00:03:00 Carbohydrate Digestion 00:02:00 Protein Digestion 00:02:00 Fat Digestion 00:02:00 Working With Clients Client Assessment 00:01:00 Client Interview 00:04:00 How To Set SMART Dieting Goals 00:06:00 How To Design Your First Diet Plan 00:09:00 Body Mass Index Explained 00:03:00 Helping Clients Lose Weight The Science Of Successful Weight Loss 00:05:00 Determining Calorie Needs 00:03:00 How To Take Diet Breaks Correctly 00:05:00 Breaking Through Fat Loss Plateaus 00:04:00 Explaining Unexpected Weight Changes 00:03:00 Is Starvation Mode Real? 00:03:00 Helping Client Build Muscle How To Create A Muscle Building Diet 00:04:00 The Perfect Pre-Workout Meal 00:04:00 The Perfect Post-Workout Meal 00:02:00 The Best Muscle Building Foods 00:02:00 Foods To Boost Testosterone 00:04:00 What Should You Eat Before Going To Bed To Build Muscle 00:03:00 Famous Diet Explained Famous Diets Introduction 00:01:00 Gluten Free Diet Explained 00:03:00 Paleo Diet Explained 00:04:00 Low Carb Diet Explained 00:03:00 Intermittent Fasting Explained 00:03:00 Vegan Diet Explained 00:05:00 Ketogenic Diet Explained 00:06:00 Optimal Diet For Athletes Athlete Diets Introduction 00:01:00 Strength Training 00:02:00 Endurance Training 00:02:00 Ball Sports & Martial Arts 00:02:00 Supplements Supplement Introduction 00:01:00 Whey Protein 00:06:00 BCAAs 00:04:00 Creatine 00:04:00 Fish Oil 00:03:00 Glutamine 00:05:00 caffeine 00:04:00 Vitamins & Minerals Vitamin A 00:03:00 Vitamin B 00:02:00 Vitamin C 00:03:00 Vitamin D 00:02:00 Vitamin E 00:01:00 Vitamin K 00:01:00 9 Calcium supplements copy 00:03:00 Magnesium 00:01:00 Phosphorus 00:01:00 Potassium 00:01:00 Sodium 00:01:00 Copper 00:01:00 Iron 00:01:00 Zinc 00:02:00

The course 'Microsoft Excel' covers the latest features of Microsoft Excel 2019, introducing learners to CONCAT, IFS, MAXIFS, MINIFS, SWITCH, TEXTJOIN, Map Chart, Funnel Chart, and other enhancements. It also covers fundamental Excel skills, data analysis, visualization, pivot tables, workbook management, and automation using VBA. Learning Outcomes: Familiarize with the new features in Microsoft Excel 2019, including CONCAT, IFS, MAXIFS, MINIFS, SWITCH, and more. Gain proficiency in basic Excel tasks like navigating the user interface, entering data, and using Excel commands. Perform calculations, create formulas, and use functions to analyze and manipulate data effectively. Format worksheets, apply conditional formatting, and utilize templates to present data professionally. Understand data visualization using charts, sparklines, and mapping techniques in Excel. Work with PivotTables and PivotCharts for in-depth data analysis and presentation. Learn advanced Excel features such as data validation, scenarios, and Goal Seek. Automate workbook functionality using macros and Visual Basic for Applications (VBA). Collaborate on workbooks, protect data, and apply security measures in Excel. Create and work with Excel templates to streamline repetitive tasks and optimize workflow. Why buy this Microsoft Excel? Unlimited access to the course for forever PDF 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 Microsoft Excel you will be able to take the MCQ test that will assess your knowledge. 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 Microsoft Excel does not require you to have any prior qualifications or experience. You can just enrol and start learning. Prerequisites This Microsoft Excel 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 Microsoft Excel is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Microsoft Excel 2019 New Features Introduction to Microsoft Excel 2019 New Features 00:07:00 CONCAT 00:02:00 IFS 00:01:00 MAXIFS 00:01:00 MINIFS 00:01:00 SWITCH 00:02:00 TEXTJOIN 00:01:00 Map Chart 00:02:00 Funnel Chart 00:01:00 Better Visuals 00:06:00 Pivot Table Enhancements 00:02:00 Power Pivot Updates 00:01:00 Getting Started with Microsoft Office Excel Navigate the Excel User Interface 00:28:00 Use Excel Commands 00:10:00 Create and Save a Basic Workbook 00:19:00 Enter Cell Data 00:12:00 Use Excel Help 00:05:00 Performing Calculations Create Worksheet Formulas 00:15:00 Insert Functions 00:17:00 Reuse Formulas and Functions 00:17:00 Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Formatting a Worksheet Apply Text Formats 00:16:00 Apply Number Format 00:08:00 Align Cell Contents 00:09:00 Apply Styles and Themes 00:12:00 Apply Basic Conditional Formatting 00:11:00 Create and Use Templates 00:08:00 Printing Workbooks Preview and Print a Workbook 00:10:00 Set Up the Page Layout 00:09:00 Configure Headers and Footers 00:07:00 Managing Workbooks Manage Worksheets 00:05:00 Manage Workbook and Worksheet Views 00:07:00 Manage Workbook Properties 00:06:00 Working with Functions Work with Ranges 00:18:00 Use Specialized Functions 00:11:00 Work with Logical Functions 00:23:00 Work with Date & Time Functions 00:08:00 Work with Text Functions 00:11:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:12:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Sharing and Protecting Workbooks Collaborate on a Workbook 00:19:00 Protect Worksheets and Workbooks 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Excel VBA Data Management Create a Macro Using the Macro Recorder 01:00:00 Edit a Macro 01:00:00 Debug a Macro 00:30:00 Customize the Quick Access Toolbar and Hotkeys 00:30:00 Set Macro Security 01:00:00 Insert Text 00:30:00 Format Text 00:30:00 Sort Data 00:30:00 Duplicate Data 01:00:00 Generate a Report 01:00:00 Determine the Dialog Box Type 00:15:00 Capture User Input 01:00:00 Insert, Copy, and Delete Worksheets 00:30:00 Rename Worksheets 00:30:00 Modify the Order of Worksheets 00:15:00 Print Worksheets 00:30:00 Create User-Defined Functions 00:30:00 Automate SUM Functions 00:30:00 Activities and Exercise Files - Microsoft Excel 2016 and VBA 00:00:00 Excel Templates Excel Templates 00:00:00 Mock Exam Mock Exam - Microsoft Excel 00:20:00 Final Exam Final Exam - Microsoft Excel 00:20:00

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