Linux Foundation Certified System Administrator (LFCS): Unit 7
This course provides a comprehensive understanding of modern virtualization and containerization technologies. Begin your journey by exploring the evolution of containers from Linux kernel features, and gain hands-on experience in managing container images, storage, and networking. Progress to mastering virtual machines with KVM, learning to create and manage VMs using virt-manager, and automate deployments with cloud-init. This course is packed with practical labs and real-world scenarios to ensure you develop the skills and confidence needed to implement and manage virtualized environments effectively.
The course provides a broad and mainly practical overview of fundamental skills for bioinformatics (and, in general, data analysis). The aim is to support the simultaneous development of quantitative and programming skills for biological and biomedical students with little or no background in programming or quantitative analysis.
Through the course, the student will develop the necessary practical skills to conduct basic data analysis. Most importantly, participants will learn long-term skills in programming (and data analysis) and the guidelines for improving their knowledge on it. The course will include Programming in R, programming in Python, Unix server, and reviewing basic concepts of statistics.
Analyze merger transactions, evaluate enterprise value, construct LTM financials, and build pro forma financial statements to assess acquisition impact. By completing this course, learners will develop practical skills in merger modeling, valuation techniques, and financial statement integration used in real-world investment banking and corporate finance.
This course guides learners step-by-step through the full merger modeling process—from understanding deal structure and calculating offer and transaction values to analyzing target financials and applying valuation multiples. Learners will gain hands-on experience in preparing balance sheet adjustments, calculating goodwill, and building pro forma financial statements that reflect post-merger performance.
What makes this course unique is its case-based approach, using a realistic merger scenario to bridge theory and application. Instead of isolated concepts, learners work through an end-to-end financial model, gaining job-ready skills applicable in M&A, equity research, and financial analysis roles. By the end, learners will confidently evaluate acquisition decisions and interpret their financial impact.
Nossas boas-vindas ao Curso Teoria dos Jogos: Da Teoria à Prática.
Neste curso, você aprenderá que a Teoria dos Jogos é um ramo da Economia que trata da análise da tomada de decisões quando todos os tomadores de decisões são presumivelmente racionais, e cada um procura prever as ações e reações de seus concorrentes. Desta forma, terá subsídios para tomar decisões. Por exemplo, de fazer ou não acordos, desencorajar a entrada no mercado de potenciais concorrentes, de preços quando as condições de demanda e custo apresentam variações ou novos concorrentes entrarem no mercado, dentre outras.
Ao final deste curso, você será capaz de jogar o jogo da estratégia e tomar decisões, levando em consideração que o resultado previsto é a melhor solução para todos os players.
Este curso é composto por quatro módulos, disponibilizados em semanas de aprendizagem. Cada módulo é composto por vídeos, leituras e testes de verificação de aprendizagem. Ao final de cada módulo, temos uma avaliação de verificação dos conhecimentos.
Estamos muito felizes com sua presença neste curso e esperamos que você tire o máximo de proveito dos conceitos aqui apresentados.
Bons estudos!
Unreal Engine: Design & Build 3D Game Worlds for Beginners
This project-driven course introduces beginners to the foundational tools and workflows used in Unreal Engine for designing and building immersive 3D game environments. Through hands-on practice and structured modules, learners will progressively identify, navigate, manipulate, construct, enhance, and compare key elements of Unreal Engine’s level design and game development framework.
Starting with engine setup and interface mastery, the course leads into practical viewport control and scene organization. Learners will then apply transformation tools, construct modular levels, and implement prop placement and lighting to refine game spaces. The course concludes with a cross-engine comparison of Unreal Engine and Unity, giving learners the ability to distinguish workflows and configure project settings confidently.
By the end of the course, learners will have built and polished a playable 3D level while developing a strong conceptual and technical foundation in professional game development practices.
Cloud infrastructure powers nearly every digital interaction today, yet for most professionals AWS remains an opaque set of services that someone else manages. The gap between knowing AWS exists and knowing how to use it confidently is costing teams speed, money, and opportunity.
In this course, taught by AWS Certified DevOps Professional Sean Baier, you'll map the core AWS service categories — compute, storage, networking, databases, analytics, machine learning, application integration, security, and governance — to real business problems. You'll provision a Lambda function, query a live dataset in QuickSight, configure an SNS notification pipeline, and set up IAM users with least-privilege access, building practical confidence with each new service.
By the end of this course, you'll be able to evaluate AWS services against specific use cases, justify architectural choices to technical and non-technical stakeholders, and take your first steps toward deploying and managing cloud resources independently.
Identify Horses or Humans with TensorFlow and Vertex AI
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you use convolutions to recognize features in an image where the subject can be anywhere in the image!
Learn how to analyze spin-off and demerger transactions, build financial models, and value both the spun entity and parent company using practical corporate finance techniques. This course provides hands-on skills in financial separation, pro forma modeling, DCF valuation, cost allocation, and post-spin performance analysis.
The course begins with the foundations of spin-off strategy and financial impact, helping learners understand why companies pursue spin-offs, demergers, and corporate restructuring. Learners will explore how these transactions affect business structure, financial statements, and shareholder value.
As the course progresses, learners examine valuation and strategic decision-making for spin-off entities. The course covers financial separation, cost allocation, Discounted Cash Flow valuation, takeover scenarios, pension liabilities, and other factors that influence transaction outcomes.
Advanced modules focus on parent company analysis after the spin-off, including post-spin valuation, performance assessment, bull and bear case scenarios, and real-world case applications such as Arconic. Learners will develop the ability to interpret valuation results and assess investment implications.
What makes this course unique is its case-driven and application-focused approach to spin-off and demerger modeling. By the end of the course, learners will be able to build robust spin-off models, evaluate restructuring transactions, value parent and spun entities, and support informed investment or corporate finance decisions.
This course teaches you how to build AI agents that can remember, retrieve, and reason using OpenAI’s advanced memory and retrieval capabilities. You will learn how modern intelligent systems store context, embed knowledge, summarize conversations, and access relevant information through Retrieval-Augmented Generation (RAG). These skills form the core of powerful enterprise-grade AI agents capable of long-term coherence, personalized responses, and deep contextual understanding.
Through hands-on lessons and guided demos, you’ll explore how to design short-term and long-term memory pipelines, implement embedding-based vector search, integrate document retrieval, and connect multi-agent workflows using the Model Context Protocol (MCP). You will learn how to combine memory, knowledge retrieval, and reasoning to build agents that are scalable, accurate, and aligned with real-world use cases.
By the end of this course, you will be able to:
- Explain how memory systems, embeddings, and RAG enhance agent intelligence and long-term contextual reasoning.
- Implement short-term and long-term memory pipelines, including session memories, summarization, and vector storage.
- Generate and use embeddings to power semantic search, document retrieval, and hybrid knowledge workflows.
- Build agents that combine retrieval and reasoning, integrating RAG into core decision-making
- Use MCP context fields to connect multiple agents, enabling shared memory and collaborative task execution.
- Evaluate memory quality, retrieval relevance, and hallucination risks using best-practice metrics.
This course is ideal for AI developers, data engineers, software professionals, and technical decision-makers who want to build context-aware, retrieval-driven, and memory-enabled AI agents for production use.
A basic understanding of Python, APIs, and foundational AI prompting concepts is recommended.
Join us to master the essential building blocks of intelligent agents—and create systems that truly understand, recall, and reason.
This is the third and final course in the Linear Algebra Specialization that focuses on the theory and computations that arise from working with orthogonal vectors. This includes the study of orthogonal transformation, orthogonal bases, and orthogonal transformations. The course culminates in the theory of symmetric matrices, linking the algebraic properties with their corresponding geometric equivalences. These matrices arise more often in applications than any other class of matrices.
The theory, skills and techniques learned in this course have applications to AI and machine learning. In these popular fields, often the driving engine behind the systems that are interpreting, training, and using external data is exactly the matrix analysis arising from the content in this course.
Successful completion of this specialization will prepare students to take advanced courses in data science, AI, and mathematics.
This course is designed for novice learners wanting to understand the basics of how security, orchestration, automation, and response (SOAR) are used for enterprise security. Learners will gain insight on how institutions monitor and respond to security threats.
To allow for a self-paced learning experience, this course is video-free. Assignments contain short explanations with images. You'll benefit from instant feedback from a variety of assessment items along the way, gently progressing from quick understanding checks (multiple choice, fill in the blank, and un-scrambling blocks of text) to small, approachable summative assessments that take minutes instead of hours.
Master IPO valuation and financial modeling with practical skills for investment banking, equity research, and finance roles.
Learn how to build financial projections, apply DCF valuation, calculate WACC, and estimate enterprise value.
This course provides a step-by-step approach to IPO valuation, helping learners move from company analysis to a complete financial model and valuation range. You will learn how to analyze industry dynamics, understand business models, interpret financial statements, and use horizontal, vertical, and ratio analysis.
The course covers revenue forecasting, cost modeling, working capital assumptions, capital expenditure schedules, depreciation and amortization, debt and equity schedules, and fully linked financial statements. You will also learn how to calculate free cash flow, estimate WACC, perform DCF valuation, run sensitivity analysis, and apply comparable company valuation.
By the end of this course, you will be able to build a practical IPO financial model, evaluate company value, and communicate valuation insights with confidence. This course is ideal for aspiring investment bankers, equity research learners, financial analysts, and corporate finance professionals.
