This course is an introductory survey of marketing terminology, concepts and practices from an applied perspective. Emphasis is on the activities performed by marketing managers to address real world marketing problems. Primary emphasis is on the identification of marketing opportunities and the planning and execution of marketing mix activities required to target these opportunities. By the end of this course, you will be able to: - Describe the scope of marketing and its role within in the firm and society. - Articulate the scope of tasks, responsibilities and challenges that marketing managers face in the complex and competitive global business environments that currently prevail. - Identify basic marketing terminology and concepts. - Examine the marketing function as a basic and indispensable driver of all business success. To succeed in this course, please be sure to read the entire module and watch the included videos. You will also need to rely on your critical thinking skills and should create a plan for completing the course.

Success in business can be greatly enhanced with an understanding of key entrepreneurial characteristics and competencies solutions. This interactive course provides potential entrepreneurs with the knowledge of succeeding in an entrepreneurial opportunity. Topics include: how creativity, opportunity and feasibility are best evaluated; business strategies for new businesses; importance of a business plan; achieving success in a new business. At the end of the course students will have the skills and confidence to evaluate starting a business, in addition to becoming more enterprising in how they approach their roles should they decide to work in organizations. Upon completing this course, you will be able to: 1. Learn about the many faces of and contexts for entrepreneurship 2. Learn about the entrepreneurial process and how to manage it 3. Learn about what it takes to be an entrepreneur and your own potential to be one 4. Learn to recognize opportunities to generate and assess your own business idea 5. Explain the business planning process 6. Apply entrepreneurial approaches, concepts and methods to your own business idea 7. Learn about the operational issues in developing new business ventures

In this 1-hour long project-based course, you will learn how to build a lead generation chatbot with Email and Google sheets automation which will be able to interact with your customers and generate lead automatically for you. We will be automating the entire process using email automation and Google sheets so that you will receive a mail every time a lead is generated and a copy of the contact information of the lead will be saved on Google sheets. The chatbot will be able to interact with your customers, generate a lead, take a booking, get ticket claims, send us their message and many more. By the end of this project, you will have a fully functioning chatbot deployed to your Facebook page and interacting with your customers through Messenger in real-time. You do not need any programming knowledge because we will be using the flow builder interface from Chatfuel which is very interactive, intuitive and logical. But you do need a Facebook account and a fully functioning Facebook business page in order to test the bot. 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.

This course is all about presenting the story of the data, using PowerPoint. You'll learn how to structure a presentation, to include insights and supporting data. You'll also learn some design principles for effective visuals and slides. You'll gain skills for client-facing communication - including public speaking, executive presence and compelling storytelling. Finally, you'll be given a client profile, a business problem, and a set of basic Excel charts, which you'll need to turn into a presentation - which you'll deliver with iterative peer feedback. This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017.

Taught by Rice University communication faculty from the Rice Center for Engineering Leadership (RCEL). This course covers core topics in oral communication: Communication strategy, content, data visualization, and delivery. You’ll learn key principles in • Creating a communication strategy • Developing a clear message and organizing persuasive content • Creating strong visual support • Presenting data effectively • Presenting professionally and confidently • Handling formal presentations, giving pitches, speaking extemporaneously, managing online presentations, and lowering public speaking anxiety Selected materials courtesy of Communication Faculty at Rice University - all rights reserved.

When you hand in work in a professional workspace, employers expect it to be good quality work and done in a timely manner. By taking this short course you will learn about consistency and how to deliver quality work and experiences to clients. In order to deliver good quality work you need to know how to do efficiently do research and how to deliver it. This short course will teach you exactly that, and even more skills that are essential to being able to deliver quality work. The course is designed to teach you how to do this using a five-step process. The skills that this course teaches are fundamental skills that you will need in order to be successful in your professional life. The content you learn in this course will be applicable to your everyday work-life and will be a stepping stone in your path to success. This course is part of the People and Soft Skills for Professional and Personal Success Specialization from IBM.

This Course includes basic information on procurement, Importance of the procurement organization and its’ role in the organization, cost vs. value, processes such as the use of RFQ, RFP, RFX, Differences between direct and indirect procurement, and Stakeholder management The course will supported by videos, readings and a required case that will be assessed by a peer review. In addition, a Practice Assessment (multiple choice) is available to the student. This should be helpful as there is a Final Assessment (40 Multiple Choice) at the end of the specialization in Course 7 that is required to obtain the certification.

This course equips you with critical content creation and management skills. You’ll learn how to create effective social media posts and how to create a strong brand to help you build a social media presence. You’ll also learn how to establish an ongoing process to manage your content. This includes setting up a content calendar, managing and moderating your posts, analyzing data for insights and iteration, and how to increase post effectiveness. You will end the course with real-world application of your skills through a content management project. By the end of this course, you will be able to: • Establish and manage a social media presence • Create a Facebook business page and an Instagram account for business • Understand how and why to create content for social media • Create a brand, tone, and voice for a social media presence • Manage a content calendar for your social media presence • Evaluate the performance of your content on social media and to iterate and optimize the performance • Create a content calendar for your social media presence • Manage social media content using real world data This course is intended for people who want to learn how to create and manage a business presence on social media, including creating content, interacting and engaging with customers on social media and evaluating the results of different posts. Learners don't need marketing experience, but they have basic internet navigation skills and are eager to participate and connect in social media. Having a Facebook or Instagram account helps and ideally learners already completed course 1 (Introduction to Social Media Marketing) in this program.

Machine learning runs the world. It generates predictions for each individual customer, employee, voter, and suspect, and these predictions drive millions of business decisions more effectively, determining whom to call, mail, approve, test, diagnose, warn, investigate, incarcerate, set up on a date, or medicate. But, to make this work, you've got to bridge what is a prevalent gap between business leadership and technical know-how. Launching machine learning is as much a management endeavor as a technical one. Its success relies on a very particular business leadership practice. This means that two different species must cooperate in harmony: the business leader and the quant. This course will guide you to lead or participate in the end-to-end implementation of machine learning (aka predictive analytics). Unlike most machine learning courses, it prepares you to avoid the most common management mistake that derails machine learning projects: jumping straight into the number crunching before establishing and planning for a path to operational deployment. Whether you'll participate on the business or tech side of a machine learning project, this course delivers essential, pertinent know-how. You'll learn the business-level fundamentals needed to ensure the core technology works within - and successfully produces value for - business operations. If you're more a quant than a business leader, you'll find this is a rare opportunity to ramp up on the business side, since technical ML trainings don't usually go there. But know this: The soft skills are often the hard ones. After this course, you will be able to: - Apply ML: Identify the opportunities where machine learning can improve marketing, sales, financial credit scoring, insurance, fraud detection, and much more. - Plan ML: Determine the way in which machine learning will be operationally integrated and deployed, and the staffing and data requirements to get there. - Greenlight ML: Forecast the effectiveness of a machine learning project and then internally sell it, gaining buy-in from your colleagues. - Lead ML: Manage a machine learning project, from the generation of predictive models to their launch. - Prep data for ML: Oversee the data preparation, which is directly informed by business priorities. - Evaluate ML: Report on the performance of predictive models in business terms, such as profit and ROI. - Regulate ML: Manage ethical pitfalls, such as when predictive models reveal sensitive information about individuals, including whether they're pregnant, will quit their job, or may be arrested - aka AI ethics. NO HANDS-ON AND NO HEAVY MATH. Rather than a hands-on training, this course serves both business leaders and burgeoning data scientists alike by contextualizing the core technology, guiding you on the end-to-end process required to successfully deploy a predictive model so that it delivers a business impact. There are no exercises involving coding or the use of machine learning software. WHO IT'S FOR. This concentrated entry-level program is for anyone who wishes to participate in the commercial deployment of machine learning, no matter whether you'll do so in the role of enterprise leader or quant. This includes business professionals and decision makers of all kinds, such as executives, directors, line of business managers, and consultants - as well as data scientists. LIKE A UNIVERSITY COURSE. This course is also a good fit for college students, or for those planning for or currently enrolled in an MBA program. The breadth and depth of the overall three-course specialization is equivalent to one full-semester MBA or graduate-level course. IN-DEPTH YET ACCESSIBLE. Brought to you by industry leader Eric Siegel - a winner of teaching awards when he was a professor at Columbia University - this curriculum stands out as one of the most thorough, engaging, and surprisingly accessible on the subject of machine learning. VENDOR-NEUTRAL. This specialization includes illuminating software demos of machine learning in action using SAS products. However, the curriculum is vendor-neutral and universally-applicable. The contents and learning objectives apply, regardless of which machine learning software tools you end up choosing to work with. PREREQUISITES. Before this course, learners should take the first of this specialization's three courses, "The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats."

This course examines macroeconomic performance in the short and long run based on the economy’s institutional and policy environment. First, we will develop a model of macroeconomy in the short run when the price level has its own momentum and does not respond much to supply and demand forces. Then, we’ll begin analyzing the long-run equilibrium by examining the foreign exchange market. The third module examines the drivers of aggregate output in the long run and the mechanisms of adjustment from the short run to the long run. Finally, we will discuss the characteristics of desirable macroeconomic policies and the reasons why actual policies deviate from them. You will be able to: • Understand how the market for aggregate goods and services interacts with the money market to shape the macroeconomic equilibrium which determines income, interest rate, and exchange rate in the short run • Assess the dynamic effects of macroeconomic policies and understand the roles of globalization, government policies, institutions, and expectations in macroeconomic outcomes This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.