Courses tagged with "Business" (1739)

Offering an intensive introduction to the complex world of M&A, this course will provide an invaluable foundation in strategy, regulation, finding a deal, corporate valuation, and more.

You will learn about buyer strategies, how M&A can increase business value, and how to start the acquisition process, as well as identify successful acquisitions.

Taught by instructors with decades of experience on Wall Street, this M&A course will equip analysts and associates with the skills they need to rise to employment in the M&A field. Additionally, directors and managers who have transitioned, or hope to transition, to M&A from other areas such as equities or fixed income can use this course to eliminate skill gaps.

This course is part of the New York Institute of Finance’s popular Mergers & Acquisitions Professional Certificate program.

One of the primary functions of a broker-dealer’s M&A desk is advisory services – consulting clients as they seek to grow through M&A.

In this course, you will learn to use the Free Cash Flow metric to evaluate acquisition opportunities. You will learn about the components of Free Cash Flow and its relationship with market value. You will also learn about the process of capital budgeting and guidelines to follow.

This course is part of the New York Institute of Finance’s popular Mergers & Acquisitions Professional Certificate program.

Learn exactly how and why different M&A deals come together, and how to determine the ideal capital structure for every deal in which you participate.

In this course, we will look at the various corporate documents involved in the M&A process and understand the purpose of the engagement letter. We’ll look at the three legal structures of M&A and understand the difference between triangular and reverse triangular structures. We’ll also learn the difference between stock and asset purchase, learn what tax-free deals are and how there are accomplished.

The course will conclude with an understanding of accounting rules and the categories of advanced structuring.

This course is part of the New York Institute of Finance’s popular Mergers & Acquisitions Professional Certificate program.

Machine Learning is the basis for the most exciting careers in data analysis today. You’ll learn the models and methods and apply them to real world situations ranging from identifying trending news topics, to building recommendation engines, ranking sports teams and plotting the path of movie zombies.

Major perspectives covered include:

• probabilistic versus non-probabilistic modeling
• supervised versus unsupervised learning

Topics include: classification and regression, clustering methods, sequential models, matrix factorization, topic modeling and model selection.

Methods include: linear and logistic regression, support vector machines, tree classifiers, boosting, maximum likelihood and MAP inference, EM algorithm, hidden Markov models, Kalman filters, k-means, Gaussian mixture models, among others.

In the first half of the course we will cover supervised learning techniques for regression and classification. In this framework, we possess an output or response that we wish to predict based on a set of inputs. We will discuss several fundamental methods for performing this task and algorithms for their optimization. Our approach will be more practically motivated, meaning we will fully develop a mathematical understanding of the respective algorithms, but we will only briefly touch on abstract learning theory.

In the second half of the course we shift to unsupervised learning techniques. In these problems the end goal less clear-cut than predicting an output based on a corresponding input. We will cover three fundamental problems of unsupervised learning: data clustering, matrix factorization, and sequential models for order-dependent data. Some applications of these models include object recommendation and topic modeling.

Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. This area is also concerned with issues both theoretical and practical.

In this course, we will present algorithms and approaches in such a way that grounds them in larger systems as you learn about a variety of topics, including:

• statistical supervised and unsupervised learning methods
• randomized search algorithms
• Bayesian learning methods
• reinforcement learning

The course also covers theoretical concepts such as inductive bias, the PAC and Mistake‐bound learning frameworks, minimum description length principle, and Ockham's Razor. In order to ground these methods the course includes some programming and involvement in a number of projects.
 
By the end of this course, you should have a strong understanding of machine learning so that you can pursue any further and more advanced learning. 

This is a three-credit course.

Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?

In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.

Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.

Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.

All programming examples and assignments will be in Python, using Jupyter notebooks.

Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.

This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.

In this macroeconomics course, you will learn to predict macroeconomic variables such as inflation, growth or consumption, and to create statistical models in economics and use them to predict responses to economic policy.

You will learn from hands-on demonstrations of model-building, forecasting and policy analysis, using data sets from a wide variety of countries. Demonstrations and applications will be conducted using EViews—a popular software for estimating and simulating forecasting models on Windows. Free, temporary licenses for EViews will be made available for the duration of the course.

Macroeconometric Forecasting is offered by the IMF with financial support from the Government of Belgium.

The macroeconomy is the sum of all our productive efforts, spending, and income. Economic outcomes are the result of our complex interactions with other people, businesses, the government, as well as with people and businesses globally. In this economics course, you will learn the basic stylized framework that economists use to think about, account for, measure and explain these complex interactions and outcomes.

In the first half of the course, we consider how households decide how much to work and how to spend and save money. We will also look at how businesses make economic decisions such as how many workers to hire and how many machines and buildings to use to produce their products.

In the second half of the course, we consider how different policies can potentially enhance or distort market outcomes by offsetting, alleviating, or amplifying these inefficiencies. Our focus will be on five aspects of economic policy:

• labor market policies and unemployment
• R&D and innovation policies
• fiscal policies and taxation
• monetary policy and inflation 
• free-trade policies

This course satisfies the Social-Behavioral Sciences (SB) general studies requirement at Arizona State University. This course may satisfy a general education requirement at other institutions; however, it is strongly encouraged that you consult with your institution of choice to determine how these credits will be applied to their degree requirements prior to transferring the credit.

In this engineering course, you will learn about magnetic materials and devices. Applications presented include magnetic data storage, motors, transformers, and spintronics.

This course is part of a three-part series, which explains the basis of electrical, optical, and magnetic properties of materials including semiconductors, metals, organics, and insulators. We will show how devices are built to take advantage of these properties. This is illustrated with a wide range of devices, placing a strong emphasis on new and emerging technologies.

Part 1 - 3.15.1x: Electronic Materials and Devices
Part 2 - 3.15.2x: Optical Materials and Devices

Humans have leveraged the power of cells for millennia to produce staples such as bread, cheese, beer and wine. Yet only recently have we begun to utilize cells as factories for the production of protein therapeutics.

These biologic drugs are able to treat otherwise untreatable diseases. In this course, you will learn how these life saving medicines are made.

We will connect the engineering fundamentals to real-world application by showing real pieces of biomanufacturing equipment in action and listening to experts describe real-world engineering challenges.

Around the globe, there are public servants and civic leaders who want to create a better future for their fellow citizens. The challenge is how to deliver—how to create new practices, build new institutions, implement new policies, and transform incentives to sustain transformation.

This course is about the “hows” of generating institutional change in hard places. Each week we focus on a different kind of challenge. You will read a case study, examine a problem in detail, help create a “solutions" toolkit, and then apply these insights to a second case.

The course introduces concepts and insights from applied political economy and the science of delivery. Topics include:

• Reducing delay, error, and diversion of funds in citizen services
• Using citizen monitoring and community-driven projects to improve services in rural areas
• Preventing conflicts of interest or self-dealing from blocking institutional reform; building trust and community and changing public expectations
• Overcoming capacity traps (what to do when brain drain, political turbulence, or other problems de-skill government)
• Facilitating coordination at the cabinet level
• Developing a strategy and the incentives to sustain change.

Drawn from actual experience around the world, each case starts with the problems a reform leader faced and traces the steps taken to address these. You will have a chance to assess the process and decide whether the solutions might work in your own context, as well as offer new proposals.

Through quizzes and open response assignments, you will be able to share ideas with others and practice what you have learned.

No certificates, statements of accomplishment, or other credentials will be awarded in connection with this course.

In this six-week course, you will learn the basics of photography and gain intriguing new perspectives on the visual world.  The course will include video tutorials, accompanied by photography assignments. Learners will upload their images to small, online working groups for discussion and review.  You will discover how subtle changes in lighting, composition, and background contribute to creating more compelling images that help communicate science visually. The course also includes interviews with noteable image makers and art directors.
 
While previous experience with a camera will be helpful, it is not essential. In order to complete the course assignments, you will need access to a single-lens reflex camera (a camera that can accept interchangeable lenses), a 105 macro lens, a flatbed scanner, and a smartphone or tablet with camera. Learners without access to this equipment can still benefit from the course concepts. However, full participation in the image making assignments will create more meaningful hands-on experience. 

In public discussions, climate change is a highly controversial topic. However, in the scientific community, there is little controversy with 97% of climate scientists concluding humans are causing global warming.

• Why the gap between the public and scientists?
• What are the psychological and social drivers of the rejection of the scientific consensus?
• How has climate denial influenced public perceptions and attitudes towards climate change?

This course examines the science of climate science denial.

We will look at the most common climate myths from “global warming stopped in 1998” to “global warming is caused by the sun” to “climate impacts are nothing to worry about.”

We’ll find out what lessons are to be learnt from past climate change as well as better understand how climate models predict future climate impacts. You’ll learn both the science of climate change and the techniques used to distort the science.

With every myth we debunk, you’ll learn the critical thinking needed to identify the fallacies associated with the myth. Finally, armed with all this knowledge, you’ll learn the psychology of misinformation. This will equip you to effectively respond to climate misinformation and debunk myths.

This isn’t just a climate MOOC; it’s a MOOC about how people think about climate change.

This five-week course will help you identify reliable information in news reports and become better informed about the world we live in. We will discuss journalism from the viewpoint of the news audience.

Together, we will examine the following topics:

• What makes news? The blurred lines between news, promotion and entertainment.
• Why does news matter? Social sharing and the dynamics of the news cycles.
• Who provides information? How to evaluate sources in news reports.
• Where is the evidence? The process of verification.
• When should we act? Recognizing our own biases.
• How do we know what we know? Becoming an active news audience.

If you are interested in becoming a more discerning news consumer, please join us and sign up today.

How can we eradicate malaria? Explore the scientific and technological underpinnings of malaria, as well as the historical, political, social, and economic contexts in which control, elimination, and eradication efforts unfold.

Through foundational lectures and supplemental interviews, this course provides participants with a toolbox of knowledge and skills. Learners will be guided through the analysis of real-world data and its effective use in problem-solving. Analytical approaches focus on how to develop and implement evidence-based intervention strategies to contribute to national and local malaria eradication efforts.

The target audience for the course includes those with an interest in gaining the technical expertise and leadership skills needed to work in global health and malaria programs around the world.

The self-paced nature of the course will allow learners to access it at their convenience.

In this training course, you will learn how to set up and manage users and groups, known as identities, in Office 365. You will learn the different types of identities that are available to create and configure in Office 365 and the benefits of using each one of them.

For example, Office 365 allows you to synchronize your local Active Directory users to the cloud, so that you only have to manage your users in one place and the changes are synchronized to the cloud automatically. You will also learn the implications of using a specific identity type and how to manage the passwords for those users. Office 365 offers a rich set of security features for identities to ensure your data is protected.

This course introduces different ways of managing finances within an organisation with the aim of enhancing business performance.

It will allow you to develop your knowledge and understanding of how to make financing and investment decisions and help you to understand:

• How organisations finance their operations
• How to plan and control cash flows
• How to make the best use of working capital
• The principles of making capital investment decisions

Completion of this course will also prepare you for the ACCA ‘Management Accounting’ exam (FMA/F2), which leads to a Diploma in Accounting and Business.

To check availability of this course in your country please click here.

This course does not offer an edX certificate.

Those learners who would like to earn an award will have the opportunity to register with ACCA as a student, take computer based exams and gain the ACCA Diploma in Accounting and Business.

You can find your nearest ACCA exam centre on the ACCA website.

Across organizations, managers are expected to have sound knowledge of finance and accounting. As part of their job, managers use large volumes of information produced by accounting systems to make business decisions every day.

This business and management course will show you how accounting information is relevant to managers, and how it can be processed and analyzed for effective managerial decision-making. By examining accounting information that is extensively used across three key managerial functions of planning, decision-making and controlling, the course equips non-finance managers with basic accounting and finance skills. This course also discusses activity based costing, which provides insight on the cost structure of products and services.

What sets this course apart is the practicing manager-centric approach that is a part of each week of the course. Whether you are a student or a practicing manager, this course will allow you to easily follow all topics and directly apply concepts in practice.

Learn management skills to support workplace diversity and inclusion in a public library setting.

You will learn about theories and frameworks that explain the underlying mechanisms of the impacts of diversity and learn how to understand and address the needs of women and underrepresented minorities (e.g. race, color, national origin, religion, sex, gender identity, marital status, age, sexual orientation, and citizenship).

You will learn how employment practices such as recruitment, selection, promotion, salary, training and development impact an organization’s ability to attract, retain, and manage a diverse workforce.

Lastly, you will recognize what organizational changes can be made to help organizations maximize the potential of all workers.