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This course is a complete guide to Arduino. Designed with multiple practical projects, you can gain hands-on experience during this course. Programming and electronics fundamentals are also covered in the course.

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Advanced audio-visual learning modules of these Data Analysis and Data Science courses are broken down into little chunks so that you can learn at your own pace without being overwhelmed by too much material at once. Furthermore, to help you showcase your expertise in Data Analysis and Data Science, we have prepared a special gift of 1 hardcopy certificate and 1 PDF certificate for the title course completely free of cost. These certificates will enhance your credibility and encourage possible employers to pick you over the rest. 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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 (For The Title Course) Hard Copy Certificate: Free (For The Title Course) The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Data Analysis and Data Science expertise and essential knowledge, which will assist you in reaching your goal. Curriculum of Bundle Course 01: Introduction to Data Analysis Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding Course 02: Python for Data Analysis Welcome, Course Introduction & overview, and Environment set-up Python Essentials Python for Data Analysis using NumPy Python for Data Analysis using Pandas Python for Data Visualization using matplotlib Python for Data Visualization using Seaborn Python for Data Visualization using pandas Python for interactive & geographical plotting using Plotly and Cufflinks Capstone Project - Python for Data Analysis & Visualization Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Python for Machine Learning - scikit-learn - Logistic Regression Model Python for Machine Learning - scikit-learn - K Nearest Neighbors Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Python for Machine Learning - scikit-learn - K Means Clustering Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Recommender Systems with Python - (Additional Topic) Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Course 03: Statistical Analysis Module 01: The Realm of Statistics Module 02: Basic Statistical Terms Module 03: The Center of the Data Module 04: Data Variability Module 05: Binomial and Normal Distributions Module 06: Introduction to Probability Module 07: Estimates and Intervals Module 08: Hypothesis Testing Module 09: Regression Analysis Module 10: Algorithms, Analytics and Predictions Module 11: Learning From Experience: The Bayesian Way Module 12: Doing Statistics: The Wrong Way Module 13: How We Can Do Statistics Better Course 04: SQL NoSQL Big Data and Hadoop Module 01: Introduction Module 02: Relational Database Systems Module 03: Database Classification Module 04: Key-Value Store Module 05: Document-Oriented Databases Module 06: Search Engines Module 07: Wide Column Store Module 08: Time Series Databases Module 09: Graph Databases Module 10: Hadoop Platform Module 11: Big Data SQL Engines Module 12: Distributed Commit Log Module 13: Summary Course 05: Complete Microsoft Power BI 2021 Module 01: Introduction Module 02: Preparing our Project Module 03: Data Transformation - The Query Editor Module 04: Data Transformation - Advanced Module 05: Creating a Data Model Module 06: Data Visualization Module 07: Power BI & Python Module 08: Storytelling with Data Module 09: DAX - The Essentials Module 10: DAX - The CALCULATE function Module 11: Power BI Service - Power BI Cloud Module 12: Row-Level Security Module 13: More data sources Module 14: Next steps to improve & stay up to date Course 06: Data Analysis in Excel Level 3 Course Modifying a Worksheet Working with Lists Analyzing Data Visualizing Data with Charts Using PivotTables and PivotCharts Working with Multiple Worksheets and Workbooks Using Lookup Functions and Formula Auditing Automating Workbook Functionality Creating Sparklines and Mapping Data Forecasting Data Course 07: Data Analytics with Tableau Module 01: Introduction to the Course Module 02: Project 1: Discount Mart (Sales and Profit Analytics) Module 03: Project 2: Green Destinations (HR Analytics) Module 04: Project 3: Superstore (Sales Agent Tracker) Module 05: Northwind Trade (Shipping Analytics) Module 06: Project 5: Tesla (Stock Price Analytics) Module 07: Bonus: Introduction to Database Concepts Module 08: Tableau Stories Course 08: Basic Google Data Studio Module 01: Introduction to GDS Module 02: Data Visualization Module 03: Geo-visualization Module 04: A Socio-Economic Case Study Course 09: Business Analytics Module 01: What is business analysis? Module 02: Strategy analysis Module 03: Collaboration Module 04: Requirements analysis and Design definition Module 05: Requirements lifecycle management Module 06: Solution quality Module 07: Stakeholder management Module 08: BA Governance Module 09: Legal notes and Copyright information Course 10: Complete Introduction to Business Data Analysis Level 3 Module 1: Statistics Fundamentals Module 2: Data Analysis Module 3: Probability Module 4: Random Variables and Discrete Distributions Module 5: Continuous Distributions Module 6: Sampling Distributions Module 7: Confidence Interval Module 8: Hypothesis Testing with One Sample Module 9: Hypothesis Testing with Two Samples Module 10: The Chi-Square Distribution Module 11: F Distribution and One-Way ANOVA Module 12: Correlation analysis Module 13: Simple Linear Regression Analysis Course 11: Business Intelligence and Data Mining Masterclass Module 01: What is Business Intelligence? Module 02: Starting Case in understanding BI needs in diff phase of business Module 03: Decision Making Process and Need of IT systems Module 04: Problem Structure and Decision Support System Module 05: Introduction to BI Applications Module 06: Dashboard presentation systems Module 07: Different Types of Charts used in 131 Dashboards Module 08: Good Dashboard and BSC Module 09: Examples of Bad Dashboards 1 Module 10: Examples of Bad Dashboards 2 And much more... Course 12: Research Methods in Business Section 01: Applied Project & Research Methods in Business Section 02: Writing a Purpose / Quantitative and Qualitative Research Approaches Section 03: Mixed Method Research Approaches, Ethical Considerations & Writing Effectively Written Methodology Part 3 !@@ Section 04: Writing Data Collection Tools, Qualitative & Quantitative Data Analysis Section 05: Comparing Findings to Literature and Writing the Final Paper Course 13: Computer Science: Graph Theory Algorithms Module 00: Promo Module 01: Introduction Module 02: Common Problem Module 03: Depth First Search Module 04: Breadth First Search Module 05: Breadth First Search Shortest Path on a Grid And much more... Course 14: Data Protection and Data Security Level 2 GDPR Basics GDPR Explained Lawful Basis for Preparation Rights and Breaches Responsibilities and Obligations CPD 165 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Data Analysis and Data Science bundle. Requirements Our Data Analysis and Data Science course is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices. Career path Having this Data Analysis and Data Science expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included You will get the PDF Certificate for the title course (Introduction to Data Analysis) absolutely Free! Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Introduction to Data Analysis) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Enroll today and gain the Excel modelling skills needed for corporate finance roles, investment analysis, business planning, and data-driven decision making.  2+ Hours of Video 4+ Hours to Complete10+ Interactive Exercises1 Recognised Certificate Course Overview Our comprehensive Excel Financial Modelling program teaches the essential Excel skills needed to build flexible and dynamic financial models. Financial modelling is a vital skill for business analysts, investment bankers, corporate financiers, and other finance professionals. Through step-by-step video lessons and over 30 hands-on exercises, this course will teach you Excel best practices to analyse financial data, forecast business performance, and evaluate strategic decisions. The self-paced online format is ideal for busy professionals looking to expand their financial analysis skillset. With over 7 hours of content, our program covers everything you need to become an expert in using Excel to build financial models.  “I was previously unsure of all the financial jargon and concepts, now I feel I have taken steps towards getting the big picture of finance. I really liked the Excel web integration!” Rachel Crawford Course Highlights Time Value of Money Principles and Calculations Net Present Value and Internal Rate of Return Metrics Calculating Averages and Statistical Measures Understanding and Measuring Financial Risk 16+ Practice Exercises and Applications Certificate Upon Successful Course Completion

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The Quality Licence Scheme is a distinguished and respected accreditation in the UK, denoting exceptional quality and excellence. It carries significant weight among industry professionals and recruiters. Upon completion, learners will receive a Free Premium QLS Endorsed Hard Copy Certificate titled 'Statistics & Probability for Data Science & Machine Learning at QLS Level 7 Advanced Diploma' & 11 Free CPD Accredited PDF Certificates. These certificates serve to validate the completion of the course, the level achieved, and the QLS endorsement. Please Note: NextGen Learning is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. CPD 180 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Statistics for Data Science & Machine Learning at QLS Level 7 Advanced Diploma bundle is ideal for: Professionals seeking to enhance their skills and knowledge. Individuals aiming for career advancement or transition. 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One of the most important concepts of your product strategy is identifying your minimal viable product or service (MVP or MVS). This walk-through takes you through a process for identifying what key qualities of your product or service comprise your MVP. Once you identify the minimum offering that addresses your customers’ needs, you can position your business for launch.

Learn to program with JavaScript from scratch. This hands-on practice-oriented course starts from the beginner's level and gradually moves to the intermediate level with a detailed understanding of object-oriented programming. We will also cover JSON objects and learn all versions of JavaScript from ES5, ES6, ES7, ES8, and the latest ES9 version.

The course on Blockchain Platforms and Use Cases in Trade and Finance is designed to provide participants with an in-depth understanding of the we.trade platform. Participants will delve into foundational concepts, identify key consortium members and participating banks, analyze platform features and functionalities, explore diverse use cases in trade finance, and recognize the specific benefits that we.trade offers to SMEs, emphasizing its role in facilitating seamless cross-border transactions. After the successful completion of the course, you will be able to learn about the following,⦁ Understand the foundational concepts of the we.trade platform in trade finance.⦁ Identify key consortium members and participating banks in the we.trade ecosystem.⦁ Analyze the features and functionalities of the we.trade platform.⦁ Explore use cases and applications of we.trade in trade finance.⦁ Recognize the benefits of we.trade for SMEs and its role in cross-border transactions.⦁ Analyze real-world examples of successful we.trade implementations. Participants will gain comprehensive insights into the foundational concepts of the we.trade platform, ensuring a solid understanding of its operational framework. Identification of key consortium members and participating banks will provide a holistic view of the platform's ecosystem. The course will delve into the features and functionalities of we.trade, offering a detailed analysis of its use cases in trade finance. Special attention will be given to recognizing how we.trade benefits SMEs and contributes to the efficiency of cross-border transactions. Real-world examples of successful we.trade implementations will be explored to showcase practical applications of the platform in diverse trade scenarios. Immerse yourself in the world of blockchain platforms with a focus on we.trade. Uncover the foundational concepts, features, and functionalities of the platform, while exploring real-world use cases that highlight its transformative impact on trade finance. Gain practical insights into how we.trade benefits SMEs and plays a crucial role in facilitating seamless cross-border transactions. Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Blockchain platforms and use cases in Trade and Finance Self-paced pre-recorded learning content on this topic. Blockchain Platforms And Use Cases In Trade And Finance Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. Blockchain Solutions Architect for Trade Finance Trade Finance Blockchain Developer Blockchain Platform Analyst in Finance Trade Finance Operations Manager - Blockchain Blockchain Integration Specialist for Trade Platforms Trade Finance Blockchain Consultant Blockchain Project Manager in Finance Blockchain Business Analyst for Trade Operations Trade Finance Platform Administrator - Blockchain Blockchain Trade Compliance Specialist Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

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