Courses

This is a self-paced lab that takes place in the Google Cloud console. Learn how to run distributed services on multiple Google Kubernetes Engine (GKE) clusters in Google Cloud using Multi Cluster Ingress and GKE Service Mesh

Service etiquette demonstrates effective interpersonal skills, which can help service professionals make a positive impression and deliver a high standard of service. For financial services, carefully executed etiquette strategies can help financial service professionals to connect with their customers, develop positive relationships, and make a good first impression. More importantly, when dealing with consumer finances, it creates customer trust and confidence. The course endeavours to understand the dimensions of service etiquette and leverage it to increase conversions, improve customer loyalty, trust, and respect.

Manage, track, and automate customer interactions with Financial Services CloudLearn how the insurance platform can help deliver connected customer experiences.Deliver connected customer experiences with the insurance platform.Optimize your Insurance for Financial Services Cloud setup with advanced configurations.Use the insurance data model to plan, manage, and track your insurance business.

Share data securely, create meeting notes, and track deals better.Share confidential client data in a secure and compliant manner.Use Interaction Summaries to capture and share structured meeting notes.Manage the entire lifecycle of a financial deal with compliant role-based sharing.

AWS Managed Services (AMS) Self-Service Reporting collects data from various AWS services and provides you with reports on AMS patch, backup, billing, and incident management services. AMS Senior Cloud Service Delivery Manager Jeremy Tennant addresses the challenges that AMS Self-Service Reporting solves, how you can integrate your business intelligence tools with Self-Service Reporting, and provides a demonstration of the service in the AMS Console. Course level: Fundamental Duration: 10 minutes Activities This course includes presentations. Course objectives In this course, you will: Understand how AMS Self-Service Reporting helps create a complete picture of your data. Understand how AMS Self-Service Reporting fills in gaps in your data sets in real time, allowing you access to reporting outside of your AMS Monthly Business Review. Understand how to integrate the data provided by AMS Self-Service Reporting with your organizations business intelligence tools. Understand how to integrate the data provided by AMS Self-Service Reporting with your organizations business intelligence tools. Intended audience This course is intended for: AMS Customers Prerequisites We recommend that attendees of this course have: A fundamental understanding of AWS services. Course outline Module 1: How to Use This Course Module 2: AMS Self-Service Reporting Module 3: Feedback

In this course, you’ll explore how financial statement data and non-financial metrics can be linked to financial performance. Professors Rick Lambert and Chris Ittner of the Wharton School have designed this course to help you gain a practical understanding of how data is used to assess what drives financial performance and forecast future financial scenarios. You’ll learn more about the frameworks of financial reporting, income statements, and cash reporting, and apply different approaches to analyzing financial performance using real-life examples to see the concepts in action. By the end of this course, you’ll have honed your skills in understanding how financial data and non-financial data interact to forecast events and be able to determine the best financial strategy for your organization.

Explore the transformative impact of AI and machine learning on the financial services industry in this 57-minute panel discussion from the Milken Institute. Gain insights into AI-driven decision-making, open banking, and fintech innovations reshaping the sector. Discover how firms are adapting to meet evolving customer demands and learn about critical investment strategies for staying competitive in the global talent market. Delve into the potential of digital ledgers and tokens to expand access to capital and enhance financial service efficiency. Join industry experts as they discuss data ecosystems, institutional adoption, equity capital markets, technology investments, open banking lessons from the UK, talent acquisition, and the future of payments in this comprehensive examination of the reimagined financial services landscape.

Learn about the fundamental concepts and operations of financial markets, institutions, and services in this comprehensive lecture series. Explore key topics including financial intermediaries, money markets, capital markets, and various financial instruments. Gain insights into the roles and functions of commercial banks, investment banks, mutual funds, and other financial institutions. Understand how different financial services work, from traditional banking to modern fintech solutions, while examining regulatory frameworks and risk management practices that govern the financial sector. Master the interconnections between various components of the financial system and their impact on economic growth and stability.

COURSE OUTLINE: Financial Management is an interesting area of learning for management graduates, working professionals, chartered accountants and similar other professionals working in the related areas. Investment and financing decisions in the business are quite complex and risky and require detailed analysis and investigations before finalizing any investment proposal by any existing or a new business organization/firm. Further, it involves complex capital structure related decisions, working out cost of capital and ways and means about maximizing the value of the firm. In this course, I will discuss about the investment, financing and dividend decisions processes in business firms and the process of value maximization of any business firm.

Learn how to manage your manager. In this course, adapted from the podcast How to Be Awesome at Your Job, Mary Abbajay explains how to build a good relationship with your boss.

Learn how to create and manage apps with SCCM and prepare for Microsoft certification exam 70-703. See how to deploy apps using PowerShell scripts, and deploy App-V virtual apps.

AWS Industry Quest: Financial Services is an interactive game-based learning experience to help individuals and organizations develop skills to build solutions for the Financial Services industry. Earn a verifiable AWS digital badge You can earn a digital badge for completing all the assignments available in the game. The AWS Industry Quest: Financial Services badge let's you to demonstrate your industry solution building knowledge to your peers, recruiters, and potential employers. How does it work? Players take over a virtual firm and transform it into an industry leader by completing solution building exercises to increase key performance indicators (KPIs). Players choose from a list of solutions common to the Financial Services industry, such as payment fraud detection, credit risk predictions, and serverless deposit accounts, and learn the solution, build it with guidance, then apply the knowledge in a do-it-yourself console setting in the game. As the company’s KPIs grow, the building grows from a one-story office to a multi-level building and players unlock new furniture and decor to customize their virtual office. Subscribe to AWS Skill Builder with an Individual or Team subscription and start learning to take your virtual company to the top! Assignments available in the game PCI/DSS Compliant Log ProcessingAWS Glue, AWS Secrets Manager, Amazon Relational Database Service (RDS), Amazon S3 Searchable Bank StatementsAWS Glue, Amazon OpenSearch Service, Amazon S3 Buy Now Pay Later as a ServiceAWS Lambda, Amazon API Gateway, Amazon Cognito, Amazon DynamoDB Loan Forms ProcessingAWS Lambda, Amazon DynamoDB, Amazon S3, Amazon SQS, Amazon Textract Record Retention ModernizationAWS Glue, Amazon Athena, Amazon S3 Real-time Fraud DetectionAWS Lambda, Amazon DynamoDB, Amazon Kinesis, Amazon S3, Amazon SageMaker Cyber Security ThreatsAWS WAF, Amazon CloudFront, Amazon EC2, Amazon Inspector Securing Payment APIsAWS Glue, AWS Key Management Service (KMS), AWS Lambda, Amazon API Gateway, Amazon Athena, Amazon Kinesis Isolation with ContainersAWS Transit Gateway, AWS WAF, Amazon Elastic Container Service, Elastic Load Balancing (ELB) Privacy and Compliance RiskAWS, AWS Glue, AWS Key Management Service (KMS), Amazon Athena Creating a Cyber Vault EnvironmentAWS Step Functions, Amazon EventBridge, Amazon S3 Open Finance Data AggregatorAWS Identity and Access Management (IAM), AWS Lambda, AWS WAF, Amazon API Gateway Credit Scoring AutomationAmazon API Gateway, Amazon CloudFront, Amazon S3, Amazon SageMaker Data Lakes for Financial ServicesAWS Database Migration Service, AWS Glue, Amazon Athena, Amazon Aurora, Amazon S3 Ingesting Exchange Data in Near Real-timeAWS Glue, Amazon Kinesis, Amazon Redshift, Amazon S3 ChatBot for Credit Card ServicesAWS Lambda, Amazon Lex, Amazon OpenSearch Service Resilience ComplianceAWS Backup, Amazon DynamoDB, Amazon EC2, Amazon EC2 Auto Scaling, Amazon Relational Database Service (RDS) Serverless Deposit AccountsAWS Cloud9, Amazon DynamoDB, Amazon Elastic Container Registry, Amazon Elastic Container Service, Elastic Load Balancing (ELB) Sentiment Analysis from Customer CallsAWS, AWS Glue, AWS Lambda, Amazon Athena, Amazon Comprehend, Amazon Transcribe Lending Analytics Solution in MinutesAWS Cloud9, AWS Secrets Manager, Amazon Aurora, Amazon Redshift

Get an overview of how to utilize the no-code/low-code Alteryx data analysis software in financial services.

Understanding key elements and basic workings of the Financial Services Industry (useful for exams as well) What you'll learn: Banking - History of bankingBanking - Distinctions between Retail/Investment etcThe role of banksCentral banksSaving and BorrowingEvaluating different sources of borrowing (mortgage, overdraft, credit card, payday loans etc)Calculating effective annual IRsEthics and Integrity in Financial ServicesHow the financial services sector links savers and borrowers, both on a household and corporate scaleInsuranceIPOsSources of return for shareholdersCalculating dividend yieldsBenefits and risks of shareholdingBondsAdvantages and disadvantages of bondholdingCredit rating agencies (S+P, Fitch, Moody’s)Derivatives – call/put options, futuresMarkets – stock exchanges and regions/sectors that they representFund management (vs direct investment)ForexPensionsFintechs, Crowdfunding, Distributed ledger tech Thank you for stopping on our course. The Financial Services industry is one of the most widely publicised, we all interact with it in different ways and yet sometimes we don't know what goes on within. Fundamentals of Financial Services has been developed as an introductory repository of information for the way the industry works. It is developed with the following potential learners in mind:- Anyone new to the industry- Anyone seeking knowledge about the basics relating to FS institutions, products and services- Anyone sitting the any financial services exams - foundation or basic levels, including:New employees at various financial institutionsAnyone interested in Economics and the EconomyCISI Level 2 “Fundamentals of Financial Services” candidatesACCA studentsAAT studentsFinance diploma, degree studentsAccounting diploma, degree studentsTax studentsFinancial Services entry levelBanking entry levelApprentices in the Financial Services industryAnyone interested in Economics and the EconomyWe developed it to help people:- Prepare for exams- Learn more about the Financial Services industry- Get a good foundation of the basics within the industry We have provided information to suite the above mentioned groups of people and also anyone curious about the topic. We wish you success your endeavour's within the industry and look forward to interacting with you on LinkedIn. This extensive, well-rounded course is designed to be a reference and resource for you to come back to at various times, addressing questions you might have relating to the very many areas covered. We welcome your feedback, questions and comments.

AWS: Managed AI Services is the fifth course in the Exam Prep (MLA-C01): AWS Certified Machine Learning Engineer – Associate Specialization. This course is designed to help learners leverage powerful pre-trained AI services offered by AWS to accelerate the development of intelligent applications — without the need to build or train ML models from scratch. Through a practical, service-based approach, learners will explore AWS offerings for natural language understanding, speech processing, computer vision, personalized recommendations, intelligent search, and human-in-the-loop workflows. These services allow developers, data engineers, and ML practitioners to embed intelligence into applications at scale with minimal ML expertise. With real-world examples, this course demonstrates how to use services like Amazon Comprehend, Rekognition, Polly, Textract, Transcribe, Personalize, Kendra, and A2I (Augmented AI) to deliver business value through managed AI capabilities. This course is structured into two major modules, each containing focused lessons and guided walkthroughs. Learners will gain approximately 2.5 to 3 hours of hands-on video content, supported by Graded and Ungraded Quizzes to assess conceptual understanding and real-world application. Module 1: Natural Language, Speech & Vision AI Services on AWS Module 2: Intelligent Search, Personalization & Human-in-the-Loop AI By the end of this course, learners will be able to: Understand how AWS Managed AI Services solve common AI use cases without custom model development Integrate services for NLP, speech, and computer vision into applications Build personalized experiences and intelligent search solutions using Amazon Personalize and Kendra Incorporate human review using Amazon A2I for critical workflows requiring oversight This course is ideal for cloud developers, solution architects, data engineers, and ML beginners who want to integrate powerful AI capabilities without training models. It’s also tailored for learners preparing for the MLA-C01 certification, especially those aiming to master the application of AWS’s fully managed AI services in real-world use cases.

Finance is for “Non-financial Managers” who want to understand key financial principles and apply them in a real-world context. Over the course of the program window, you will work your way through a series of nine modules that move from understanding basic financial principles to applying financial analysis and ratios to drive decisions. In addition, each module is capped with an ending self-evaluation to ensure that you have absorbed the following key learning objectives: + Understand the language associated with finance + Know how and when to use financial terms and analysis techniques + Read and assess company performance using financial statements + Recognize the link between organizational strategy and financial objectives + Use "the numbers" to your best advantage to make more informed decisions

Get a basic understanding of financial management, sufficient to interpret reports, draft budgets, cost products, and make informed financial decisions.

Learn the basic financial management and accounting skills you need to interpret financial reports, draft a budget, understand the cost of a product or service, and more.

This Specialization is intended for learners that have or wants to have a career in the digital financial industries. The Specialization explores the evolving world of finance, focusing on the changing dynamics caused by the conversion of products and services into digital goods, new customer demands and changing regulation to govern the competetive landscape - the digital transformation of finance. You’ll learn about concepts such as digital platforms and business ecosystems, be exposed to the emerging Fintech landscape and master a new toolbox for successfully competing on innovation in the digital era of finance. In the final Capstone Project, you’ll create and defend a holistic digital transformation strategy for a real world company. Throughout the course, the instructors will use state of art examples and share their own research from the European and North American finance industries, as well as expose practices from leading digital financial services and companies, such as MobilePay, Saxo Bank and PayPal. The main focus in the course is on the financial sector (in particular in North America and Europe), but the course also include material of relevance for the financial trading and insurance sectors and inspiration from Africa.

This course will explore the conceptual aspects of applying machine learning to problems in the financial services industry and discuss case studies of machine learning used in financial services. Analytical and statistical models are already an integral part of the finance industry and the use of machine learning builds on a strong foundation in this industry. The financial services industry is uniquely positioned to leverage machine learning because of the vast quantities of high-quality data already available. In this course, Machine Learning for Financial Services, you will explore machine learning techniques currently applied in the financial services industry. First, you will look at some examples and cases of where ML is already being used in financial services - for investment predictions, loan automation, process automation, and fraud detection. Then, you will develop an intuitive understanding of how recurrent neural networks Next, you will explore two ML case studies from research papers - the first focusing on assessing and quantifying the return on investment and the second exploring how classification and clustering models can help detect money laundering. Finally, you will get hands-on coding and see how you can use a classification model for fraud detection on a synthetically generated dataset. When you are finished with this course, you will have the awareness of how machine learning can be applied in the financial services industry and hands-on experience working with financial data.