An ambitious vision for the future of your organisation isn’t enough – how do you communicate this vision to get your colleagues on board? The ability to effectively communicate and persuade others is a key leadership skill. Traditional and common-sense models of communication and persuasion often fail to capture the complex nature of ‘influencing’. Via structured learning activities (video lectures, quizzes, discussion prompts and written assessments) this course will develop your capacity to communicate appropriately in different situational and cultural contexts, making you a highly influential leader.

Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. Your first model will focus on minimizing default risk, and your second on maximizing bank profits. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model. The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. Your role as a data-analyst is to reduce uncertainty for decision-makers by a financially valuable increment, while quantifying how much uncertainty remains. You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classification error rates, entropy of information, and confidence intervals for linear regression. All the data you need is provided within the course, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. The course will give you enough practice with Excel to become fluent in its most commonly used business functions, and you’ll be ready to learn any other Excel functionality you might need in the future (module 1). The course does not cover Visual Basic or Pivot Tables and you will not need them to complete the assignments. All advanced concepts are demonstrated in individual Excel spreadsheet templates that you can use to answer relevant questions. You will emerge with substantial vocabulary and practical knowledge of how to apply business data analysis methods based on binary classification (module 2), information theory and entropy measures (module 3), and linear regression (module 4 and 5), all using no software tools more complex than Excel.

By the end of this project, you will be able to create an automatic table of contents using Microsoft Word. You will learn to insert and use: page numbers, footnotes, endnotes, and comments. In addition, you will utilize a unique feature to translate your document and to track changes for editing purposes. This guided project will teach you step by step on how to make good use of all these tools to make exceptional word documents.

The capstone project is designed to give you the opportunity to apply what you've learned in Types of Conflict, Conflict Resolution, and Intercultural Communication and Conflict Resolution. In this course you will prepare a conflict management portfolio illustrating the nature of a specific conflict, the different roles of participants in the conflict and the significance of those roles, the perceived incompatible goals, power imbalances, and communication skills needed for the effective management of the conflict. Upon completing this course, you will be able to: 1. Create a well organized and complete case study 2. Analyze key organizational issues with an integrated action plan for conflict resolution 3. Identify appropriate communication skills needed for conflict resolution skills 4. Present a portfolio that incorporates concepts learned throughout the Specialization 5. Reflect on what you've learned throughout the Specialization

By the end of this project, you will be able to create two different types of timelines that display easy to read information with aesthetically pleasing designs within Microsoft PowerPoint. You will learn when to utilize a horizontal versus a vertical timeline to effectively communicate information in a visual format to your intended audience. The timelines will include the goals, steps and timeframes in which projects are to be completed. In this project, we will choose a timeline from pre-created ones given by Microsoft PowerPoint and use simple shapes to design our own. Each one will be customized according to your own needs. Afterwards, you will improve the timelines by adding design elements and colors.

By the end of this project, you will create a high-quality website with Wix. Wix is a free program that helps you design and build your own personalized website. This project will teach you how to maximize the design features of Wix to create a business website. Wix can help you to create a professional website to highlight your company’s brand, mission, and products/services. A strong online presence can help to solidify a company’s brand, attract new customers, and provide important information to the public. This project will walk you through the website development process with Wix from start to finish. From creating an account to launching your website, this project will cover it and get you on your way to better managing your company’s online presence and brand! Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Students are introduced to the field of financial accounting through defining the foundational activities, tools, and users of financial accounting. Students learn to use the accounting equation and are introduced to the four major financial statements. Additional topics include ethical considerations, recording business transactions, and the application of credit/debit rules.

This course covers the basic procedures involved in recording financial entries in Journals and Ledgers. Upon completing this course, you will be able to analyze and record various business transactions. You will also learn about the accounting cycle, posting transactions, accrual accounting, and cash accounting. You will also have the opportunity to practice these skills through a series of activities that provide real world experience.

This is the first course in PwC GST Taxation Executive Professional Certificate. This is a good place to start if you want to become a GST professional in India. In this course, you will first learn about the genesis of GST, the need for its introduction, and the Constitutional and legal framework under which it was introduced. You will then learn the concept of ‘supply’ under GST along with its related definitions and concepts. This course provides a platform for learners planning to launch their careers in tax or sharpen their skills with the technical understanding of the GST law in India. The course is a part of the PwC GST Taxation Executive Professional Certificate which is industry agnostic and relevant for anyone looking to acquire basic knowledge of GST. It will provide you with the skills required for entry level jobs in the fields of finance, tax, or law. By the end of this course, you will: - Know the shortcomings of the earlier indirect tax regime and why GST was introduced - Know the basic framework of GST in India and the changes brought in the Indian Constitution for introducing GST - Understand the concept of supply under GST and related definitions like goods, services, and consideration - Understand which goods and services are included or excluded from GST - Understand the various types of supplies (viz. inter-State, intra-State, exempt, non-GST, composite, and mixed supplies), and how they impact the computation of GST.

Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine. All of these applications have in common that dynamic behavior needs to be related to process models. Hence, we refer to this as "data science in action". The course explains the key analysis techniques in process mining. Participants will learn various process discovery algorithms. These can be used to automatically learn process models from raw event data. Various other process analysis techniques that use event data will be presented. Moreover, the course will provide easy-to-use software, real-life data sets, and practical skills to directly apply the theory in a variety of application domains. This course starts with an overview of approaches and technologies that use event data to support decision making and business process (re)design. Then the course focuses on process mining as a bridge between data mining and business process modeling. The course is at an introductory level with various practical assignments. The course covers the three main types of process mining. 1. The first type of process mining is discovery. A discovery technique takes an event log and produces a process model without using any a-priori information. An example is the Alpha-algorithm that takes an event log and produces a process model (a Petri net) explaining the behavior recorded in the log. 2. The second type of process mining is conformance. Here, an existing process model is compared with an event log of the same process. Conformance checking can be used to check if reality, as recorded in the log, conforms to the model and vice versa. 3. The third type of process mining is enhancement. Here, the idea is to extend or improve an existing process model using information about the actual process recorded in some event log. Whereas conformance checking measures the alignment between model and reality, this third type of process mining aims at changing or extending the a-priori model. An example is the extension of a process model with performance information, e.g., showing bottlenecks. Process mining techniques can be used in an offline, but also online setting. The latter is known as operational support. An example is the detection of non-conformance at the moment the deviation actually takes place. Another example is time prediction for running cases, i.e., given a partially executed case the remaining processing time is estimated based on historic information of similar cases. Process mining provides not only a bridge between data mining and business process management; it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development. The course uses many examples using real-life event logs to illustrate the concepts and algorithms. After taking this course, one is able to run process mining projects and have a good understanding of the Business Process Intelligence field. After taking this course you should: - have a good understanding of Business Process Intelligence techniques (in particular process mining), - understand the role of Big Data in today’s society, - be able to relate process mining techniques to other analysis techniques such as simulation, business intelligence, data mining, machine learning, and verification, - be able to apply basic process discovery techniques to learn a process model from an event log (both manually and using tools), - be able to apply basic conformance checking techniques to compare event logs and process models (both manually and using tools), - be able to extend a process model with information extracted from the event log (e.g., show bottlenecks), - have a good understanding of the data needed to start a process mining project, - be able to characterize the questions that can be answered based on such event data, - explain how process mining can also be used for operational support (prediction and recommendation), and - be able to conduct process mining projects in a structured manner.