The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Amazon Web Services
Amazon Connect Instance Fundamentals
In this course, you will walk through design considerations and basic steps to create an Amazon Connect cloud contact center customized to your business needs. The course includes guidance on region selection, single or multiple instance design best practices, identity management considerations, data storage, and telephony configuration settings. By the end of this course you will: - Recognize the meaning of key instance concepts. - Explore considerations for creating instances. - Identify the steps required to create an instance. - Explore data storage, administrator, application data, and channel configuration settings. - Identify additional application settings to expand your contact center functionality.
Politecnico di Milano
Project Management: Beyond planning and control
Project Management is a fundamental theme to understand and work in any business environments. Projects are the organizational way to make innovation happen and to realize any kind of custom solution or to change how an organization work. Project Management is the set of capabilities, skills and tools to properly work on projects. The course aims to define the concept of a project and to show how, in the management of a successful business, project management and process management must coexist and integrate. During the course the project is analyzed as a managerial tool for the management of change and innovation and its links with the company strategy are emphasized.
University of Illinois Urbana-Champaign
Sports Turf Management: Best Practices
The Sports Turf Management: Best Practices course will cover the construction, management, and challenges in maintaining athletic fields intended for football, soccer, and baseball. You will learn the fundamental management practices for maintaining athletic fields, such as fertilization, irrigation, mowing, and pest control. An overview of athletic field construction, highlighting the advantages and disadvantages of native soil versus modified soil fields, will be provided. Lastly, you will explore the effects of traffic and compaction on athletic fields and the development of artificial turf. This course is a non-credit course that is part of the College of ACES suite of online programs. To learn more about online programs from the College of ACES and explore ways to apply your work toward a degree program at the University of Illinois, visit acesonline.illinois.edu.
Georgia Institute of Technology
Lesson | Small Talk & Conversational Vocabulary
This lesson is part of a full course, Speak English Professionally: In Person, Online & On the Phone. Take this lesson to get a short tutorial on the learning objectives covered. To dive deeper into this topic, take the full course. In this lesson, you will review professional conversational vocabulary.
Google Cloud
Analyzing Findings with Security Command Center
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you learn about Security Command Center by exploring the service’s analyzed assets and export features.
Packt
Deep Learning - Artificial Neural Networks with TensorFlow
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This course delves into deep learning and artificial neural networks using TensorFlow. - It begins with foundational machine learning concepts, covering linear classification and regression, before exploring neurons, model learning, and predictions. - Core modules focus on forward propagation, activation functions, and multiclass classification, with practical examples like the MNIST dataset for image classification and regression tasks. - It also covers model saving, Keras usage, and hyperparameter selection. - The final sections provide an in-depth look at loss functions and gradient descent optimization techniques, including Adam. - Key outcomes include understanding machine learning concepts, implementing ANN models, and optimizing deep learning models using TensorFlow. This course suits those interested in deep learning, TensorFlow 2, and foundational concepts for advanced neural networks like CNNs, RNNs, LSTMs, and transformers. Proficiency in Python and familiarity with NumPy and Matplotlib are required.
Packt
Intermediate Rust Programming and Web Server Development
Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Elevate your Rust programming expertise and dive into web server development with this comprehensive course. You’ll begin by solidifying your understanding of Rust through a crash course that covers intermediate to advanced concepts, including enums, structs, traits, lifetimes, and smart pointers. Each section is packed with practical coding exercises designed to reinforce your learning and ensure you can apply Rust's powerful features in real-world scenarios. Once you’ve mastered Rust, the course transitions into web development, where you’ll learn to build a web server using Actix Web, a high-performance framework that simplifies building scalable web applications. From setting up your project and defining data structures to implementing full CRUD operations and securing user authentication, you’ll gain hands-on experience in creating a robust web server. You’ll also explore advanced topics like managing state with Mutex, handling async API calls, and integrating a database. By the end of this course, you’ll have a deep understanding of intermediate Rust programming and the practical skills needed to build and deploy high-performance web servers. Whether you’re looking to enhance your web development capabilities or advance your career as a Rust developer, this course will provide you with the tools to succeed. This course is ideal for developers with basic Rust knowledge who want to advance their skills and learn web server development. It’s perfect for those aiming to build robust, scalable applications using Rust and Actix Web. Prerequisites include familiarity with Rust basics and an interest in web development.
Amazon
Database Management with Java and SQL
This is the fourth course in the Amazon Junior Software Developer Professional Certificate. In this course on Introduction to Databases and Basic SQL Queries, you will learn essential knowledge and skills for working with relational databases and querying data using SQL (Structured Query Language). You'll start by understanding fundamental concepts like tables, rows, and columns and learn to write basic SQL queries for operations such as selecting, inserting, updating, and deleting data. You'll interact with the command line to create, populate, and query a simple database. Moving on to SQL Queries, you'll explore advanced topics, including retrieving data from multiple tables using JOINs, filtering data with WHERE clauses, and sorting/grouping data using ORDER BY and GROUP BY clauses, enabling efficient data manipulation within databases. Subsequently, you will delve into JDBC Fundamentals, gaining insights into JDBC (Java Database Connectivity), setting up JDBC drivers and connections, executing SQL queries and commands with JDBC statements, establishing database connections using DriverManager and DataSource, managing database connections effectively, and executing DDL and DML statements for database schema management and data manipulation. By the end of this course, you will be proficient in working with databases, writing SQL queries, and utilizing JDBC to interact with databases in Java applications. After completing this course, you’ll be able to: • Discuss different types of common database configurations. • Manipulate datasets with Java programming tools and techniques. • Illustrate the process of data querying and retrieval using SQL with JDBC.
University of Maryland, College Park
Master Class for Corporate Entrepreneurs
The Master Class experience is designed to serve as the final project experience for the Corporate Entrepreneurship Specialization. Alternatively, professionals with experience in opportunity analysis, business modeling, and corporate finance are invited to complete the Master Class experience without the preliminary courses. With maturing technologies and aging product portfolios requiring established companies to create, develop, and sustain innovative new businesses, graduates of the Master Class will develop an understanding of how to create new businesses and initiatives within the corporate environment. In collaboration with our award-winning faculty, and a vibrant peer group, learners will explore and apply the skills, tools, and best practices for: • Identifying and developing the entrepreneurial opportunities; • Building business models; • Creating strategies for leading innovation; and • Financing and profiting from innovation. The Master Class experience is differentiated from typical Coursera courses and MOOCs in that our faculty and staff are actively engaged with learners by providing individual feedback on assignments. Our faculty and staff will review and offer feedback on the major assignment submissions, if you wish, in an effort to assist you in developing and launching your corporate ventures. Try this course for FREE at https://www.coursera.org/learn/corporate-entrepreneurship-project
Meta
Front-End Developer Capstone
The Capstone project enables you to demonstrate multiple skills from the Certificate by solving an authentic real-world problem. Each module includes a brief recap of, and links to, content that you have covered in previous courses in this program. This course will test your knowledge and understanding, and provide you with a platform to show off your new abilities in front-end web development using React. During this course, you will be guided through the process of building an app, combining all the skills and technologies you've learned throughout this program to solve the problem at hand. On completion of the Capstone project, you’ll have a job-ready portfolio that you can show to recruiters, demonstrate during interviews and impress potential employers. To complete this course, you will need front-end developer experience. Additionally, it always helps to have a can-do attitude!
Packt
Python Data Analysis
This course introduces the core concepts of data analysis using Python, equipping learners with essential skills to perform data manipulation and analysis. Data analysis is a crucial skill in today's tech-driven world, and this course empowers professionals with the tools they need to extract insights from data. Throughout this course, you will gain hands-on experience using key Python libraries such as NumPy and pandas, making complex data analysis tasks accessible. You’ll learn how to clean, process, and analyze data sets, setting you up for success in real-world data projects. What sets this course apart is its combination of theory and practice, using real-world examples to guide you. You'll not only learn the fundamental concepts but also how to apply them to solve actual data problems. This course is perfect for programmers, scientists, and engineers with a basic understanding of Python and data science concepts. If you're looking to expand your data analysis skills with Python, this course is designed for you.
Simplilearn
LLM Fine-Tuning and Customization Training
This LLM Fine-Tuning course equips you with the skills to optimize and deploy domain-specific large language models for advanced Generative AI applications. Begin with foundational concepts—learn supervised fine-tuning, parameter-efficient methods (PEFT), and reinforcement learning with human feedback (RLHF). Master data preparation, hyperparameter tuning, and key evaluation strategies. Progress to implementation using LLM frameworks and libraries, and apply best practices for model selection, bias monitoring, and overfitting control. Conclude with hands-on demos—fine-tune Falcon-7B and build an image generation app using LangChain and OpenAI DALL·E. You should have a solid background in Python, deep learning fundamentals, and prior exposure to large language models. By the end of this course, you will be able to: - Fine-tune LLMs using PEFT, RLHF, and supervised methods - Prepare datasets and optimize hyperparameters for tuning - Evaluate and deploy fine-tuned models using GenAI frameworks - Apply tuning concepts in real-world use cases like Falcon-7B and DALL·E apps Ideal for AI developers, ML engineers, and GenAI researchers.
Alfaisal University | KLD
الجداول والرسوم التوضيحية في مايكروسوفت إكسل
برنامج (Microsoft Excel) هو برنامج تم ابتكاره ليصبح أداة قوية وفعالة لتجميع وتحليل البيانات من قبل العديد من الفئات العاملة في المجالات المالية وغيرها، مثل العاملين في مجال الموارد البشرية والمخازن وغيرهم. يتطلب تجميع البيانات ترتيبَها بشكل منظم ليتمكن المستخدم من إجراء التحليل المطلوب لها والوصول إلى النتائج الصحيحة التي تساعد مجلس إدارة المنشأة في اتخاذ القرارات المالية والتشغيلية المستقبلية. وأفضل الطرق لتنظيم البيانات - سواء أكانت بيانات محاسبية أو بيانات خاصة بالأفراد العاملين في المنشأة - هو وضعها داخل جداول (Tables) ورسوم توضيحية (Illustrations) لتسهل قراءتها ومقارنتها وعرضها فيما بعد بالعديد من الطرق المتاحة في البرنامج. هذه الدورة هي دورة تمهيدية؛ فهي تلقي الضوء على أساسيات الموضوع بشكل عام بهدف التعريف به وبمحاوره الأساسية التي يجب الإلمام بها. إذا كنت من المهتمين بفهم الجداول والرسوم التوضيحية في مايكروسوفت إكسل، أو كان مجال عملك يتطلب توظيف ذلك في سياق عملك، فهذه الدورة ستكون مثالية لإغناء خبرتك وتطوير مهاراتك بشكل فعال ومؤثر. حيث ستزودك هذه الدورة باطلاع واسع ودقيق على مجموعة من المحاور المتعلقة بهذا الموضوع، مثل: شرح كيفية عرض تلك البيانات، توضيح كيفية إضافة رسوم توضيحية، التعرف على كيفية التعامل مع الجداول والتحكم فيها، تبيان طرق إضافة الجداول.
Universidad de los Andes
Fundamentos de estadística aplicada
El curso está orientado a profesionales de diferentes campos, que estén interesados en adquirir conceptos fundamentales de estadística aplicada. El contenido del curso será particularmente útil para profesionales que estén interesados en adelantar estudios de postgrado en ingeniería, administración o economía, entre otras profesiones, y que requieran de una adecuada fundamentación en estadística. También será de utilidad para estudiantes universitarios que deseen reforzar o complementar su formación básica en estadística, aprovechando los diferentes recursos con los que cuenta este MOOC. o La estadística es un campo de la matemática aplicada que se ocupa de la recolección, descripción y análisis de datos. Actualmente, esta disciplina no es solo fundamental para el ejercicio de la ingeniería, la economía y las ciencias básicas, sino que cada vez es más importante en aspectos de la vida moderna. Múltiples artículos son publicados diariamente en periódicos y revistas a través de los cuales se pretenden explicar tendencias sociales o económicas, siendo evidente que la estadística no solo es importante para ser un buen profesional, sino también para ser un miembro de la sociedad bien informado. o Las aplicaciones de la Estadística van desde la organización de grandes cantidades de datos, pasando por la caracterización de los clientes de una compañía o individuos de una región, hasta el diseño de campañas de mercadotecnia más eficientes, y el desarrollo de políticas sociales. Algo a lo que se atribuye el gran éxito de los japoneses en la industria de la manufactura, durante el siglo XX, es al uso de métodos estadísticos y al pensamiento estadístico del personal gerencial, lo cual permitió enfocar la atención en el análisis y uso de los datos para mejorar la calidad y eficiencia de sus procesos de fabricación. o El curso tiene como objetivo principal que los participantes adquieran una formación sólida en los conceptos más importantes de estadística, y sus aplicaciones. En este curso haremos especial énfasis en que logres una adecuada comprensión del análisis descriptivo de datos estadísticos, así como de los métodos básicos para la estimación de parámetros poblacionales, finalizando con el entendimiento de los modelos de Regresión Lineal Simple y Múltiple, y las oportunidades de aplicación de dichos modelos. o El curso tiene un buen balance entre el rigor en el tema y la presentación del contenido de una forma sencilla, con base en ejemplos que abordan situaciones reales simplificadas, y cuenta con videos y ejercicios orientados a facilitar la comprensión de los conceptos que se cubren en este curso.
Siemens
Basics of Robotics
Robotics Basic is an introductory course that provides a structured, hands-on overview of industrial robotics. Over 13 compact modules, learners explore the mechanical, electrical, and digital components that make up modern robotic systems. You will learn what defines a robot, how different robot types are classified, and how they are used in industrial environments. The course covers robot kinematics, motion strategies (PTP, CP, CIRC), drive systems, end effectors, and measurement technologies. Special focus is placed on human-robot collaboration, programming principles, and practical safety in accordance with international standards such as the EU Machinery Directive and ISO 10218. Each module includes real-world examples, visual aids, and short quizzes to reinforce learning. The course concludes with a graded final quiz. Prerequisites: No prior experience with robotics is required. Basic technical understanding and familiarity with industrial or mechanical concepts are helpful but not mandatory. Comfort with using a computer and navigating online learning platforms will support a smooth learning experience. Target Audience: This course is ideal for technicians, engineering students, early-career professionals, and anyone interested in automation and robotics. By the end of the course, you will be able to understand, evaluate, and apply the key principles of robotics in a modern industrial context.
Google Cloud
Managing Security in Google Cloud en Français
"Ce cours en auto-formation présente une étude approfondie des contrôles et techniques de sécurité sur Google Cloud. À travers des présentations enregistrées, des démonstrations et des ateliers pratiques, les participants explorent et déploient les composants d'une solution Google Cloud sécurisée (Cloud Identity, Resource Manager, Cloud IAM, les pare-feu de cloud privé virtuel, Cloud Load Balancing, l'appairage cloud, Cloud Interconnect et VPC Service Controls, par exemple). Ceci est le premier cours de la série ""Security in Google Cloud"". Après l'avoir terminé, inscrivez-vous au cours ""Security Best Practices in Google Cloud""."