Online courses directory (1728)

In the first half of this course, we'll investigate DNA replication, and ask the question, where in the genome does DNA replication begin? You will learn how to answer this question for many bacteria using straightforward algorithms to look for hidden messages in the genome.

In the second half of the course, we'll examine a different biological question, and ask which DNA patterns play the role of molecular clocks. The cells in your body manage to maintain a circadian rhythm, but how is this achieved on the level of DNA? Once again, we will see that by knowing which hidden messages to look for, we can start to understand the amazingly complex language of DNA. Perhaps surprisingly, we will apply randomized algorithms to solve problems.

Finally, you will get your hands dirty and apply existing software tools to find recurring biological motifs within genes that are responsible for helping Mycobacterium tuberculosis go "dormant" within a host for many years before causing an active infection.

This course begins a series of classes illustrating the power of computing in modern biology.

*** Este curso será dado em português. ***

Um dos desafios enfrentados diariamente pelas instituições públicas, organizações não governamentais, agências de desenvolvimento e outros agentes que promovem o desenvolvimento econômico e social na América Latina e no Caribe é transformar propostas em realidades concretas que melhorem o bem-estar da sociedade e permitam que esses resultados sejam alcançados dentro do prazo e com os recursos disponíveis.

Este curso apresenta conceitos e ferramentas que podem ser aplicados na gestão de projetos e gerar uma mudança substancial para atingir os objetivos propostos. Assim, este MOOC se propõe a fortalecer a capacidade de gestão de projetos de desenvolvimento na região para que sejam executados de forma eficaz e efetiva.

Este curso inclui casos práticos que ajudam a entender os principais conceitos e ferramentas para o gerenciamento de projetos, apresentações de pessoal certificado como Project Management Professional (PMP)^®, com ampla experiência no assunto, fóruns de discussão e leituras selecionadas.

A base conceitual deste curso é a metodologia PM4R (Project Management for Results), desenvolvida pelo Instituto Interamericano de Desenvolvimento Econômico e Social (INDES), do BID, cujos conteúdos baseiam-se no Project Management Institute, A Guide to the Project Management Body of Knowledge (PMBOK^® Guide) – Fifth Edition, Project Management Institute, Inc., 2013.

Embora essas melhores práticas tenham estado presentes por muitos anos em projetos empresariais privados, nos últimos anos, o BID tem liderado o processo de sua incorporação progressiva ao setor público e aos projetos de desenvolvimento, contribuindo para a construção de realidades que melhoram vidas.

O INDES, como um Registered Education Provider (R.E.P.), foi aprovado pelo Project Management Institute (PMI)^® para fornecer 30 unidades de desenvolvimento profissional (PDUs), caso você obtenha o certificado deste curso.

Se tiver qualquer dúvida, envie um e-mail para idbx@iadb.org.

A preparação deste curso foi financiada pelo Fundo de Fortalecimento da Capacidade Institucional (FISC), graças à contribuição do governo da República Popular da China.

PMBOK é uma marca registrada do Project Management Institute, Inc.

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.

Regression Analysis is the most common statistical modeling approach used in data analysis and it is the basis for more advanced statistical and machine learning modeling.

In this course, you will be given fundamental grounding in the use of widely used tools in regression analysis. You will learn the basics of regression analysis such as linear regression, logistic regression, Poisson regression, generalized linear regression and model selection.

Throughout this course, you will be exposed to not only fundamental concepts of regression analysis but also many data examples using the R statistical software. Thus by the end of this course, you will also be familiar with the implementation of regression models using the R statistical software along with interpretation for the results derived from such implementations.

This course is more about the opportunity for individual discovery than it is about mastering a fixed set of techniques.

This course provides students and professionals in the analytics field with an accelerated introduction to the basics of management and the language of business.

The objective is to enhance an analytics-focused learner's effectiveness in the business world. Designed for students who possess little background in business, the course provides an introduction to the types business issues and problems that challenge management teams today.

The course is taught as a series of business disciplinary modules. The professors who teach the modules represent a diversity of functional areas, including accounting, finance, marketing, international marketing, industry analysis, and business strategy.

Topics covered include:

• basic accounting principles and theory
• financial statement formats, usage and analysis
• cost accounting, variance analysis, and the use of accounting data for decision making
• capital structure and financial analysis techniques
• methods of valuating entrepreneurial ventures, sources of entrepreneurial capital
• the marketing mix (product, price, promotion, and place) and strategic considerations in market planning
• fundamentals of industry analysis, business strategy formulation, and the use of innovation as a competitive weapon.

In this course, you will learn to estimate the expected return of equity and debt. You will also learn to estimate the weighted average cost of capital (WACC), the opportunity cost of capital you should use when discounting the free cash flows to value a firm.

In the process, you will learn to estimate the risk of financial assets and how use this measure of risk to calculate expected returns. You will also learn how the capital structure of a firm affects the riskiness of its equity and debt. Throughout the course, you will learn how to construct Excel models to value firms using hands on activities.

All analytics work begins and ends with a story. Storytelling is the analytics professional’s missing link in delivering the essence of signals and insights from data to executives, management and more for real business results.

In this analytics storytelling course, you’ll learn effective strategies and tools to master data communication in the most impactful way possible—through well-crafted analytics stories.

In this course, learners will begin to apply the lessons and concepts from Introduction to Corporate Finance as they begin to discuss basics of firm valuation.

Follow Professor Wolfenzon’s lead to learn how the free cash flow method is applied to value firms. You will also learn about valuation using multiples. Throughout the course, you will learn how to construct Excel models to value firms by completing hands on activities.