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Advanced audio-visual learning modules of these Business Analysis 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 Business Analysis, 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. This Business Analysis Bundle Consists of the following Premium courses: Course 01: Business Analysis Level 3 Course 02: Strategic Business Management Course 03: Financial Analysis Course 04: Capital Budgeting & Investment Decision Rules Course 05: Basic Business Finance Course 06: SAP Controlling (CO) - Product Costing S4HANA Course 07: Research Methods in Business Course 08: Introduction to Data Analysis Course 09: Business Intelligence and Data Mining Masterclass Course 10: Basic Google Data Studio Course 11: Statistical Analysis Course 12: Payroll Management Course Course 13: Level 3 Tax Accounting Course 14: Certificate in Anti Money Laundering (AML) Enrol now in Business Analysis to advance your career, and use the premium study materials from Apex Learning. 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 (For The Title Course) Hard Copy Certificate: Free (For The Title Course) Course Curriculum Course 01: Business Analysis Level 3 Module 01: Introduction to Business Analysis Module 02: Business Processes Module 03: Business Analysis Planning and Monitoring Module 04: Strategic Analysis and Product Scope Module 05: Solution Evaluation Module 06: Investigation Techniques Module 07: Ratio Analysis Module 08: Stakeholder Analysis and Management Module 09: Process Improvement with Gap Analysis Module 10: Documenting and Managing Requirements Module 11: Career Prospect as a Business Analyst in the UK Course 02: Strategic Business Management Module 01: Introduction to Strategic Management Business Module 02: Corporate Governance Module 03: Industry Analysis Module 04: Strategy Formulation Module 05: Strategy Implementation Module 06: Evaluation and Control Module 07: Building a Brand Module 08: Generating Success from the Customer Relationship Module 09: Social Responsibility and Ethics in Strategic Management Module 10: Getting Ready for Business Improvement Course 03: Financial Analysis Section-1. Introduction Section-2. Profitability Section-3. Return Ratio Section-4. Liqudity Ratio Section-5.Operational Analysis Section-6. Detecting Manipulation Course 04: Capital Budgeting & Investment Decision Rules Section 01: Introduction Section 02: NPV Method Section 03: Payback Period Method Section 04: Internal Rate of Return (IRR) Section 05: Evaluating Projects in Different Lives Section 06: Conclusion Course 05: Basic Business Finance Module 01: What is Business Finance? Module 02: Why Businesses Fail Module 03: The Principles of Business Finance Part 1 Module 04: The Principles of Business Finance Part 2 Module 05: The Balance Sheet Module 06: The Income Statement Module 07: The Cashflow Statement Module 08: A Business Finance Exercise Module 09: Financial Performance Indicators Module 10: Investment Analysis Module 11: Investment Analysis Exercise Module 12: Key Learning Points in Business Finance Course 06: SAP Controlling (CO) - Product Costing S4HANA Section 1: Introduction Section 2: Material Master Data and Pricing Controls Section 3: BoM, Activities and Routing Section 4: Overheads in Costing Section 5: Costing Sheet Section 6: Costing Variant Section 7: Routing and Work Centres Section 8: Cost Component Structure Section 9: Execution of Standard Cost Estimation Course 07: 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 08: 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 And much more... Course 09: 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 10: 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 11: 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 And much more... Course 12: Payroll Management Course Module 01: Payroll System in the UK Module 02: Payroll Basics Module 03: Company Settings Module 04: Legislation Settings Module 05: Pension Scheme Basics Module 06: Pay Elements Module 07: The Processing Date Module 08: Adding Existing Employees Module 09: Adding New Employees Module 10: Payroll Processing Basics And much more... Course 13: Level 3 Tax Accounting Module 01: Tax System and Administration in the UK Module 02: Tax on Individuals Module 03: National Insurance Module 04: How to Submit a Self-Assessment Tax Return Module 05: Fundamentals of Income Tax Module 06: Advanced Income Tax Module 07: Payee, Payroll and Wages Module 08: Capital Gain Tax And much more... Course 14: Certificate in Anti Money Laundering (AML) Module 01: Introduction to Money Laundering Module 02: Proceeds of Crime Act 2002 Module 03: Development of Anti-Money Laundering Regulation Module 04: Responsibility of the Money Laundering Reporting Office Module 05: Risk-based Approach Module 06: Customer Due Diligence And much more... CPD 140 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Business Analysis bundle. Requirements Our Business Analysis course is fully compatible with PCs, Macs, laptops, tablets and Smartphone devices. Career path Having this Business Analysis expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included P.S. The delivery charge inside the UK is £3.99, and the international students have to pay £9.99.
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Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) 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 Building Recommendation Systems with Python (TTAI2360) 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 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.This skills-focused ccombines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Applied AI: Building Recommendation Systems with Python (TTAI2360) 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.
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