The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Pontificia Universidad Católica del Perú
Gestión de Emprendimientos Gastronómicos
Al finalizar el curso "Gestión de Emprendimientos Gastronómicos", serás capaz de navegar con confianza por el complejo mundo de la gastronomía, desde la concepción de una idea hasta la operación exitosa de un negocio culinario. Este curso está diseñado para ofrecerte una comprensión amplia de los fundamentos estratégicos necesarios para iniciar y gestionar emprendimientos gastronómicos con éxito. A través de tres módulos cuidadosamente estructurados, podrás adquirir los conocimientos esenciales sobre la introducción al emprendimiento gastronómico, exploración de tipos de negocios en el sector y la innovación, y los fundamentos estratégicos para una gestión eficaz. Además, aprenderás a identificar oportunidades en el sector gastronómico, evaluar diferentes modelos de negocio y desarrollar estrategias de gestión que abarquen desde la logística y administración hasta el control de costos y marketing. Este enfoque integral te permitirá identificar el tipo de negocio más adecuado según tus objetivos y recursos, evaluar las opciones más rentables y con menos riesgo, y aplicar herramientas prácticas para el éxito de tu emprendimiento.
The University of Melbourne
Essentials of Corporate Finance Capstone
The Capstone Project is the final part of the Essentials of Corporate Financial Analysis and Decision-Making MOOC Specialization. The Capstone is designed to allow students to bring together the skills acquired and knowledge gained over the preceding four courses of the Specialization by taking on the role of a financial analyst tasked with advising a wealthy private client on a significant strategic investment in a large listed firm operating across the globe. View the MOOC promotional video here: http://tinyurl.com/j9fqv25
University of Illinois Urbana-Champaign
Financial Analysis of Organizations
This course focuses on adopting and implementing a financially analytic mindset when analyzing organizational activities, position and performance. This course begins with an overview of an organization’s financial statements, including the balance sheet, income statement, cash flow statement, as well as the transactions that comprise these statements. You will learn about tools and ratios that help analyze these financial statements and transactions. Financial statement analysis will help you understand how the company has performed in the past and its current position. This analysis - as well as course content on forecasting both short- and long-term performance - enables you to draw inferences, make predictions about the organization's future performance and value. Ultimately, this course provides a "deep-dive" into the multi-dimensional nature of financial analysis and how it used to assess the value of organizations.
National Academy of Sports Medicine
Nutrition for Optimal Mental Health
In this course, you'll embark on an enlightening journey to discover how the foods you eat can significantly impact your mental well-being and cognitive performance. With a focus on evidence-based dietary strategies, you'll learn how to fuel your brain for optimal function, enhance your mood, and protect against cognitive decline. From exploring the benefits of the Mediterranean and MIND diets to understanding the role of specific nutrients in mental health, this course offers practical insights and actionable steps to transform your diet and support a healthier, sharper mind. Get ready to unlock the secrets of nutrition and take control of your mental health—one meal at a time! With over 30 years as a leader in fitness and wellness education, the National Academy of Sports Medicine (NASM) has built its reputation on providing an evidence-based curriculum that is both relevant and applicable for those seeking the skills and knowledge required to promote optimal health.
Google Cloud
Unleash Team Potential: Assess Learning Needs Using GenAI
Unleash Team Potential: Assess Learning Needs Using GenAI offers practical guidance on using generative AI to perform skill assessment and career development recommendations, thus empowering leaders to elevate team performance, foster talent growth, and bridge skill gaps to achieve success.
Dassault Systèmes
SOLIDWORKS Feature Patterns and Sweeps
Welcome to SOLIDWORKS Feature Patterns and Sweeps, the fourth course in the SOLIDWORKS 3D CAD for Education Specialization. Prior knowledge from the earlier courses is strongly recommended. This course teaches powerful modeling tools for creating repetitive or complex geometry efficiently. Upon completion of this learning module, you will be able to: - Create mirror feature - Apply linear pattern - Apply circular pattern - Create sweep / sweep cut This course is perfect for learners looking for advanced design scenarios and time-saving model creation. Software Prerequisites: SOLIDWORKS Desktop EDU Access powerful capabilities for Engineering with SOLIDWORKS Desktop at a low price, $60 (excluding taxes), follow this link : https://go.3ds.com/CSW1
Icahn School of Medicine at Mount Sinai
Dynamical Modeling Methods for Systems Biology
An introduction to dynamical modeling techniques used in contemporary Systems Biology research. We take a case-based approach to teach contemporary mathematical modeling techniques. The course is appropriate for advanced undergraduates and beginning graduate students. Lectures provide biological background and describe the development of both classical mathematical models and more recent representations of biological processes. The course will be useful for students who plan to use experimental techniques as their approach in the laboratory and employ computational modeling as a tool to draw deeper understanding of experiments. The course should also be valuable as an introductory overview for students planning to conduct original research in modeling biological systems. This course focuses on dynamical modeling techniques used in Systems Biology research. These techniques are based on biological mechanisms, and simulations with these models generate predictions that can subsequently be tested experimentally. These testable predictions frequently provide novel insight into biological processes. The approaches taught here can be grouped into the following categories: 1) ordinary differential equation-based models, 2) partial differential equation-based models, and 3) stochastic models.
Coursera
Selecting the Right LLM with Hugging Face
There are literally thousands of Large Language Models or LLMs available out there that can be used for a plethora of purposes. Hugging Face is the de-facto hub for language models, offering a huge collection where you can find and use almost any model you need. Choosing the right model can be an arduous task given models come in various shapes, sizes and configurations and each model is specialized at something different. So, when you approach Hugging Face in search of the right Model for your requirement, you have to know the art of this matchmaking. In this course, we will learn how to navigate through the Hugging Face Hub for Models, matching their configurations to your needs. We will understand key characteristics of Models (LLMs), such as Size, Computational Requirements, Specializations, Licensing and so on. We will look into various families of Models and their specializations, performance and variants. We will also learn how to use various models from Hugging Face and Evaluate them based on your requirements. This course is designed for professionals deeply involved in the field of AI and machine learning, including Data Scientists, Machine Learning Engineers, AI Engineers, LLM RAG Application Developers, Software Developers, and IT Engineers. It targets individuals who are actively building or plan to build applications leveraging Large Language Models (LLMs) and seek to enhance their ability to select and utilize the most appropriate models for their specific needs. Participants should have a strong foundation in Python programming and a basic understanding of Large Language Models (LLMs) and their programmatic use, as the course will build on these concepts with practical coding exercises and advanced topics like model selection, comparison, and evaluation. By the end of this course, learners will have achieved four key objectives. They will master navigating the Hugging Face ecosystem, gaining proficiency in finding and understanding various models. They will also learn to effectively use these models, comparing them based on multiple factors and practical considerations. Additionally, the course will guide participants in testing and evaluating different models, enabling them to score and assess the results based on specific parameters. Ultimately, learners will be equipped to select the most suitable model for a given task, ensuring optimal performance in their applications.
Skillshare
Premium Logo Animation in Adobe After Effects: 2D Projects
Take your logo animation skills to the next level by exploring dynamic 2D motion design. In this course, Valeri Visuals will teach you how to create a variety of polished, professional logo animations using advanced 2D techniques in Adobe After Effects. You’ll discover how to integrate animations seamlessly into videos, apply creative transitions, and bring brand identities to life. By the end of this course, you will be able to: * Design multiple styles of animated logos for diverse branding needs. * Integrate animations with photos and video footage. * Use timing, easing, and effects to make animations feel fluid and engaging. This course is designed for learners with basic After Effects knowledge, such as completing Premium Logo Animation: Fundamentals or equivalent experience. Through project-based lessons, hands-on tasks, and Valeri’s practical tips, you’ll leave with a versatile collection of 2D logo animations to use in your own work or for clients. Instructor bio: Valeri Visual is a freelance Motion Graphics Designer and educator specializing in Adobe After Effects. With a background in visual communication—spanning graphic design, illustration, and animation—Valeri brings both professional and teaching experience to his courses. After working in an animation studio and later as a full-time freelancer, Valeri discovered a passion for teaching. He has since taught at branding companies, mentored students, and built a global audience through tutorials on YouTube and Instagram. Over the past two years, he has developed digital courses designed to help graphic designers, illustrators, and aspiring motion designers expand their skills and grow their careers. Valeri’s mission is to empower creative professionals and entrepreneurs to increase their opportunities and income by mastering motion design with After Effects.
University of Glasgow
Fundamental MATLAB Programming for AI
This course introduces the fundamentals of the programming platform of this course, MATLAB. Through MATLAB’s toolboxes, engineers can make use of AI techniques bypassing intricate programming and achieve superior results. After learning this course (3 modules), students will be ready to learn AI techniques using MATLAB in terms of programming skills. In this course, MATLAB fundamentals, particularly those that are useful for applying AI techniques using MATLAB, are introduced. This includes manipulating variables and matrices in MATLAB, MATLAB scripts, graphs, using built-in functions, defining and using custom functions, conditionals and program control, loops, table arrays and cell arrays to manipulate data, categorical data and one-hot encoding of them, etc. Case studies will be provided for writing objective functions in engineering optimization and data cleaning for building machine learning models, which are the fundamentals of Courses 2 and 3. In partnership with MathWorks, enrolled students have access to MATLAB for the duration of the course.
Johns Hopkins University
Advanced Techniques in Data Visualization
In the course "Advanced Techniques in Data Visualization", you will explore advanced data visualization techniques that will elevate your ability to communicate complex data. Building upon foundational skills, you’ll learn to harness the power of color, interactivity, and specialized visualization methods, such as hierarchical structures, networks, and geospatial data. The course covers the essential role of color theory in visualization, teaching you how to enhance data clarity and accessibility. You will also dive into the world of interactive visualizations, gaining practical experience in creating user-driven data experiences. As you explore hierarchical and network visualizations, you'll discover how to represent complex relationships in a way that is easy to understand. The course will guide you through the principles of mapping data, allowing you to transform spatial data into compelling visual narratives. Finally, you will learn to visualize textual data, uncovering patterns and insights that might otherwise remain hidden. With hands-on experience using popular tools such as Tableau and Power BI, this course prepares you to create sophisticated, effective, and impactful visualizations for any audience.
Deep Teaching Solutions
Critical Thinking & Logic: Real-World Skills
Enhance your logical reasoning skills with "Critical Thinking & Logic: Real-World Skills." This innovative course, led by professors Barbara Oakley, Adam Trybus and Terrence Sejnowski, offers a deep dive into the practical applications of critical thinking and logic. Explore the intricacies of deductive, inductive, and abductive reasoning, learning how to apply each in various real-world scenarios. Master the art of argument analysis, from recognizing premises and conclusions to standardizing complex arguments for clarity. Through engaging examples, you'll learn to identify rhetorical devices and logical fallacies that can obscure sound reasoning. What sets this course apart is its focus on practical application. You'll tackle real-life examples, from business innovation like the creation of Shazam to everyday problem-solving. The course also delves into the challenges of language and definitions in logical reasoning, helping you navigate the complexities of communication in critical thinking. By the end of the course, you'll have a comprehensive toolkit for analyzing arguments, making informed decisions, and approaching problems creatively. Whether you're in business, academia, or simply looking to sharpen your analytical skills, this course will equip you with advanced logical reasoning tools applicable to a wide range of real-world situations.
University of Illinois Urbana-Champaign
Foundations of Professional Identity
Many find themselves frustrated in their careers by lack of preparation for dealing with predictable dilemmas that regularly arise in the world of work. Two in five professionals fired in their jobs after college are terminated for lying, or misuse of technology. Easy to avoid! Or is it? What if you find you have to compromise your values to keep your job? What if they ask you to lie or cheat, even though you know if you are found out you will be fired? What if you find out the company is breaking the law? Successful people know about and have the skills taught in this specialization. You should, too. Those who wish to make a difference, build positive reputations, become leaders, and advance in their careers must cultivate professional success skills, along with their specific job skills. The central themes of this course – knowing yourself and your values, recognizing and meeting ethical challenges, using an analytical decision-making framework, identifying potential pitfalls, and developing tools to use in the moment – are essential soft skills for succeeding at work. In short, an ethical framework is necessary, and not just nice; smart ethics, as we define them, are integral to success.
Coursera
Einführung in Marketing Design mit Canva
Nach Abschluss dieses Projekts wirst du gelernt haben eine Grafik für soziale Medien mit Hilfe der Gratis Version von Canva zu kreieren, welche du in den verschiedenen Social media Plattformen teilen kannst. Die web basierte Plattform Canva bietet alle nötigen Werkzeuge um visuell attraktive und organisierte Produkte alleine, oder als Team zu kreieren und zu teilen. Mit Hilfe von Canva wirst du lernen Fotos, Text und die Farbpalette deiner Marke in dein Projekt einzufügen, um den Wiedererkennungswert deiner Marke in den sozialen Medien zu steigern. User von sozialen Netzwerken werden im heutigen Zeitalter von Informationen und Bildern regelrecht überschwemmt. Aufgabe des Social Media Marketings ist es daher, kreative Wege zu finden um die Aufmerksamkeit der User für ihre Produkte und Dienstleistungen zu gewinnen. Dies erfolgt oftmals auf Basis eines sehr geringen Marketing Budgets.
EDUCBA
Regression & Forecasting for Data Scientists using Python
Course Description: This course provides comprehensive training in regression analysis and forecasting techniques for data science, emphasizing Python programming. You will master time-series analysis, forecasting, linear regression, and data preprocessing, enabling you to make data-driven decisions across industries. Learning Objectives: • Develop expertise in time series analysis, forecasting, and linear regression. • Gain proficiency in Python programming for data analysis and modeling. • Analyze the techniques for exploratory data analysis, trend identification, and seasonality handling. • Figure out various time-series models and implement them using Python. • Prepare and preprocess data for accurate linear regression modeling. • Predict and interpret linear regression models for informed decision-making. There are Four Modules in this Course: Module 1: Time-Series Analysis and Forecasting Module description: The Time-Series Analysis and Forecasting module provides a comprehensive exploration of techniques to extract insights and predict trends from sequential data. You will master fundamental concepts such as trend identification, seasonality, and model selection. With hands-on experience in leading software, they will learn to build, validate, and interpret forecasting models. By delving into real-world case studies and ethical considerations, participants will be equipped to make strategic decisions across industries using the power of time-series analysis. This module is a valuable asset for professionals seeking to harness the potential of temporal data. You will develop expertise in time series analysis and forecasting. Discover techniques for exploratory data analysis, time series decomposition, trend analysis, and handling seasonality. Acquire the skill to differentiate between different types of patterns and understand their implications in forecasting. Module 2: Time-Series Models Module description: Time-series models are powerful tools designed to uncover patterns and predict future trends within sequential data. By analyzing historical patterns, trends, and seasonal variations, these models provide insights into data behavior over time. Utilizing methods like ARIMA, exponential smoothing, and state-space models, they enable accurate forecasting, empowering decision-makers across various fields to make informed choices based on data-driven predictions. You will acquire the ability to build forecasting models for future predictions based on historical data. Discover various forecasting methods, such as ARIMA models and seasonal forecasting techniques, and implement them using Python programming. Develop the ability to formulate customized time-series forecasting strategies based on data characteristics. Module 3: Linear Regression - Data Preprocessing Module description: The Linear Regression - Data Preprocessing module is a fundamental course that equips participants with essential skills for preparing and optimizing data before applying linear regression techniques. Through hands-on learning, participants will understand the importance of data quality, addressing missing values, outlier detection, and feature scaling. You will learn how to transform raw data into a clean, normalized format by delving into real-world datasets, ensuring accurate and reliable linear regression model outcomes. This module is crucial to building strong foundational knowledge in predictive modeling and data analysis. You will gain insights into various regression techniques such as linear regression, polynomial regression, and logistic regression, and their implementation using Python programming. Identify missing data and outliers within datasets and implement appropriate strategies to handle them effectively. Recognize the significance of feature scaling and selection and learn how to apply techniques such as standardization and normalization to improve model convergence and interpretability. Module 4: Linear Regression - Model Creation Module description: The Linear Regression - Model Creation module offers a comprehensive understanding of building predictive models through linear regression techniques. You will learn to choose and engineer relevant features, apply regression algorithms, and interpret model coefficients. By exploring real-world case studies, you will gain insights into model performance evaluation and acquire how to fine-tune parameters for optimal results. This module empowers you to create robust linear regression models for data-driven decision-making in diverse fields. You will understand how to identify and select relevant features from datasets for inclusion in linear regression models. Acquire the skills to interpret model coefficients, recognize their significance, and deliver the implications of these coefficients to non-technical stakeholders. Discover how to fine-tune model parameters, and regularization techniques, and perform cross-validation to enhance model generalization. Target Learner: This course is designed for aspiring data scientists, analysts, and professionals seeking to enhance their skills in regression analysis, forecasting, and Python programming. It is suitable for those looking to harness the power of temporal data and predictive modeling in their careers. Learner Prerequisites: • Basic knowledge of Python programming. • Familiarity with fundamental data analysis concepts. • Understanding statistical concepts is beneficial but not mandatory. Reference Files: You will have access to code files in the Resources section and lab files in the Lab Manager section. Course Duration: 5 hours 44 minutes Total Duration: Approximately 4 weeks • Module 1: Time-Series Analysis and Forecasting (1 week) • Module 2: Time-Series Models (1 week) • Module 3: Linear Regression - Data Preprocessing (1 week) • Module 4: Linear Regression - Model Creation (1 week)
Red Hat
Fundamentals of Red Hat JBoss EAP
Learn about the features provided by Red Hat JBoss Enterprise Application Platform (JBoss EAP) 8, and perform basic management of JBoss EAP services. Course objectives: View steps to install and manage a Red Hat JBoss Enterprise Application Platform server, and explore a key set of the latest features that it provides. Describe the main issues to consider in a migration to JBoss EAP. Analyze applications, measure migration efforts, and refactor Java package names by using the Migration Toolkit for Applications (MTA). Migrate server configurations from previous JBoss EAP versions by using the JBoss EAP Server Migration Tool. Identify legacy security components that need to migrate to Elytron, and use the Elytron CLI tool to help with the migration.