The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Packt
Manufacturing & Engineering
This course 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. In this course, you'll learn key manufacturing and engineering concepts, starting with effective communication and rights and responsibilities in industrial environments. Explore topics such as teamwork, planning, LEAN methodology, action planning, and continuous improvement. You'll also dive into specific tools like Fishbone diagrams, flow charts, and flow process analysis to solve problems and improve efficiency. The course emphasizes understanding health and safety legislation, risk assessment, and managing hazards in manufacturing operations. You’ll gain insights into how LEAN principles, such as eliminating non-value-added activities, can benefit businesses and employees alike. This course is perfect for those in manufacturing and engineering roles, helping you develop key skills to enhance operations. By the end, you'll be equipped to optimize processes, improve teamwork, and apply LEAN practices for greater competitiveness in the global market.
Packt
Fundamentals of Azure Databricks
Updated in May 2025. This course now features Coursera Coach — your interactive learning companion that helps you test your knowledge, challenge assumptions, and deepen your understanding as you progress. Build a strong foundation in Azure Databricks, the unified analytics and data engineering platform used across modern cloud environments. Designed for beginners, this hands-on course guides you through setting up your Databricks workspace, creating Spark clusters, and integrating Azure services so you can process and manage data efficiently at scale. You’ll begin by reviewing the course prerequisites and exploring the core resources you’ll use throughout your learning journey. With step-by-step guidance, you’ll set up your Azure cloud account, configure your Databricks workspace, and learn to navigate the Azure portal — giving you the essential groundwork to use the platform confidently. As you progress, you’ll start working directly inside the Databricks workspace, creating and configuring Spark clusters and writing code in Databricks notebooks. You’ll explore notebook features such as magic commands, the Databricks Utilities package, and interactive data processing workflows that make Databricks a powerful environment for big data engineering. By the end of this course, you will have: - Set up and configured an Azure Databricks workspace from scratch. - Created and managed Spark clusters for scalable data processing. - Used Databricks notebooks, magic commands, and Databricks Utilities to streamline workflows. - Integrated Databricks with Azure services for end-to-end data engineering tasks. - Gained practical experience needed to begin working confidently with Azure Databricks. This course is ideal for aspiring data engineers, cloud practitioners, and beginners who want hands-on skills with Azure Databricks. No prior experience is required, though familiarity with cloud or data concepts is helpful.
28DIGITAL
Mastering Digital Twins
This nano course provides a general understanding of Digital Twins, offering a high-level introduction to the topic suitable for participating in discussions, panels, and strategic decision-making. It is designed to give learners the foundational knowledge needed to grasp the key concepts, applications, and business implications of digital twins. You will explore the fundamentals of Digital Twins and how they represent an integrated view of product-related data. The course highlights how digital twins respond to the increasing digitalisation of product development, production, and the products themselves. Modern products are complex, interconnected systems that not only fulfil their intended functions but also communicate via networks with other components, products, clouds, and services. These smart products integrate services and are continuously supported throughout their lifecycle. Course chapters include: • What is a Digital Twin and who invented it? • Key applications and use cases • Business benefits and impact • Industrial success stories • Enabling technologies and trends
Peking University
离散数学概论 Discrete Mathematics Generality
离散数学是计算机科学的基础理论，离散结构的基础知识和逻辑思维的形式化是信息技术类学生的基本功，离散数学的基本概念是理科专业学生进行信息类课程学习的重要基础。 本课程介绍计算机科学和信息技术理论基础的概念和思想方法，介绍数理逻辑、集合论、图论、抽象代数和形式语言与自动机等各部分的基本概念，介绍离散数学基本概念和空间信息技术之间的联系与结合，培养学生理解和掌握离散数学基本概念，采用形式化方法分析问题，并能自觉运用逻辑分析、结构层次分析和同构类比等思想方法解决问题的能力。
University of Illinois Urbana-Champaign
Emergence of Life
How did life emerge on Earth? How have life and Earth co-evolved through geological time? Is life elsewhere in the universe? Take a look through the 4-billion-year history of life on Earth through the lens of the modern Tree of Life! This course will evaluate the entire history of life on Earth within the context of our cutting-edge understanding of the Tree of Life. This includes the pioneering work of Professor Carl Woese on the University of Illinois Urbana-Champaign campus which revolutionized our understanding with a new "Tree of Life." Other themes include: -Reconnaissance of ancient primordial life before the first cell evolved -The entire ~4-billion-year development of single- and multi-celled life through the lens of the Tree of Life -The influence of Earth system processes (meteor impacts, volcanoes, ice sheets) on shaping and structuring the Tree of Life This synthesis emphasizes the universality of the emergence of life as a prelude for the search for extraterrestrial life.
University of Colorado Boulder
Market Research and Analysis for Tech Industries
Developing a revolutionary design or product or software often becomes an all-consuming pursuit in industry. Yet, many gifted engineers and technologists are eventually bewildered to discover, only too late, that their innovative product is wholly insufficient. A great design accomplishes nothing if it fails to address critical needs and the only means of aligning those is a deep understanding of the consumer or business customer. Fully 94% of executives admit that their organizations fail to truly understand the customer. They are, strategically, running full-steam in complete darkness. This course can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.
Google Cloud
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation - Français
Ce cours apporte aux professionnels du machine learning les techniques, les bonnes pratiques et les outils essentiels pour évaluer les modèles d'IA prédictive et générative. L'évaluation des modèles est primordiale pour s'assurer que les systèmes de ML fournissent des résultats fiables, précis et de haut niveau en production. Les participants acquerront une connaissance approfondie de diverses métriques et méthodologies d'évaluation, ainsi que de leur application appropriée dans différents types de modèles et tâches. Le cours mettra l'accent sur les défis uniques posés par les modèles d'IA générative et proposera des stratégies pour les relever efficacement. Grâce à la plate-forme Vertex AI de Google Cloud, les participants apprendront à implémenter des processus d'évaluation rigoureux pour la sélection, l'optimisation et la surveillance continue des modèles.
Packt
Cloud Security for IT Professionals
This course 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. In this course, you will dive into the fundamentals of cloud security, starting with the basics of cloud computing and its models. You’ll explore the importance of cloud security and the core principles that protect cloud environments. You’ll work with tools and services like AWS to configure Identity and Access Management (IAM) policies, encryption, and access control mechanisms. As you progress, you’ll learn best practices for data protection, network security, application security, and threat detection, including encryption, data segmentation, and security event monitoring. You’ll also configure logging pipelines and integrate SIEM systems for cloud security management. This course is perfect for IT professionals looking to enhance their cloud security skills. Prior experience in IT or cloud computing is helpful but not required. By the end of the course, you will be able to implement cloud security best practices and effectively secure cloud infrastructures
Coursera
Crea una tarjeta de negocios en Canva
Al final de este proyecto, tendrás todos los conocimientos básicos para crear una tarjeta de negocios utilizando la plataforma Canva, una herramienta de creación y edición de mercadeo en línea. Podrás crear una tarjeta de negocio personalizada utilizando las distintas herramientas de diseño, colores y gráficos que ofrece Canva.
EDUCBA
Splunk Knowledge Objects: Analyze & Visualize Data
By the end of this course, learners will be able to define Splunk knowledge objects, implement lookups, apply regex and delimiter-based field extractions, execute workflow actions, categorize data with tags and event types, design automated alerts, manage scheduled reports, develop dashboards, create reusable macros, and build accelerated data models with pivot visualizations. This advanced-level course is designed for professionals who want to move beyond basic Splunk searches and analyze, enrich, and visualize data with precision. Participants will benefit by gaining practical, hands-on skills in transforming raw event data into structured insights, enabling faster investigations and more effective decision-making. What makes this course unique is its modular approach, where each section builds progressively from foundational knowledge objects to advanced data models and pivot analytics. Learners will not only master technical configurations but also understand how to optimize Splunk for scalable, real-world business use cases. Whether you are a data analyst, security professional, or IT operations specialist, this course empowers you to leverage Splunk as a strategic platform for operational intelligence.
Imperial College London
Probabilistic Deep Learning with TensorFlow 2
Welcome to this course on Probabilistic Deep Learning with TensorFlow! This course builds on the foundational concepts and skills for TensorFlow taught in the first two courses in this specialisation, and focuses on the probabilistic approach to deep learning. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real world datasets. This is a crucial aspect when using deep learning models in applications such as autonomous vehicles or medical diagnoses; we need the model to know what it doesn't know. You will learn how to develop probabilistic models with TensorFlow, making particular use of the TensorFlow Probability library, which is designed to make it easy to combine probabilistic models with deep learning. As such, this course can also be viewed as an introduction to the TensorFlow Probability library. You will learn how probability distributions can be represented and incorporated into deep learning models in TensorFlow, including Bayesian neural networks, normalising flows and variational autoencoders. You will learn how to develop models for uncertainty quantification, as well as generative models that can create new samples similar to those in the dataset, such as images of celebrity faces. You will put concepts that you learn about into practice straight away in practical, hands-on coding tutorials, which you will be guided through by a graduate teaching assistant. In addition there is a series of automatically graded programming assignments for you to consolidate your skills. At the end of the course, you will bring many of the concepts together in a Capstone Project, where you will develop a variational autoencoder algorithm to produce a generative model of a synthetic image dataset that you will create yourself. This course follows on from the previous two courses in the specialisation, Getting Started with TensorFlow 2 and Customising Your Models with TensorFlow 2. The additional prerequisite knowledge required in order to be successful in this course is a solid foundation in probability and statistics. In particular, it is assumed that you are familiar with standard probability distributions, probability density functions, and concepts such as maximum likelihood estimation, change of variables formula for random variables, and the evidence lower bound (ELBO) used in variational inference.
Packt
Chatbots Development with Amazon Lex
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 offers a comprehensive guide to creating intelligent chatbots using Amazon Lex. It begins with an introduction to Amazon Web Services (AWS), explaining how cloud services can enhance chatbot development. You'll explore key AWS offerings, their flexibility, and scalability, and learn the core components of building and deploying chatbots. The journey starts with understanding the basics of Amazon Lex bots, their architecture, and their integration within the AWS ecosystem. As you advance, the course delves deeper into the technicalities of chatbot creation, connecting Lex with AWS Lambda and Twilio. You'll gain insights into how to manage intents, slots, and utterances to create a seamless user experience. Through hands-on examples, you'll learn to develop and test various chatbot components, set up response cards, and handle custom slot types, ensuring your bots can respond efficiently to user inputs. By integrating Lambda functions, you'll enhance chatbot functionality, enabling dynamic and context-aware interactions. Towards the course's conclusion, you’ll deploy your chatbot across platforms, including websites and WhatsApp, using tools like Twilio and Kommunicate.io. You’ll also explore Python’s Boto library for code-based deployment. By the end, you will have mastered chatbot building, testing, and deployment strategies, ready to create powerful AI-driven bots for business or personal use. This course is ideal for developers, AI enthusiasts, and technical professionals interested in creating chatbots using Amazon Lex. Basic knowledge of AWS and Python is recommended.
Coursera
Build Predictive & Supervised Models
Transform your data science career by mastering production-ready machine learning workflows. This Short Course was created to help data analysis professionals accomplish reliable demand forecasting and model governance in business environments. By completing this course, you'll be able to build robust random forest models that hit business targets, implement automated model monitoring systems, and create reproducible ML pipelines that stand the test of time. By the end of this course, you will be able to: - Build cross-validated random forest models that achieve business-defined accuracy targets Evaluate and monitor model drift using statistical metrics to ensure long-term reliability Implement standardized cross-validation pipelines for multiple supervised algorithms Assess feature selection techniques to balance model accuracy with interpretability This course is unique because it bridges the gap between academic machine learning and real-world production requirements, emphasizing business metrics and operational reliability. To be successful in this project, you should have a background in Python programming and basic statistics.
Pearson
Hands-on AWS VPC Labs: Essential Lab Exercises
Master AWS Virtual Private Clouds (VPCs) with the Hands-on AWS VPC Labs Essentials Video Course, a must-have for cloud computing professionals and AWS certification seekers. AWS VPCs provide the foundation for creating isolated, secure sections within the cloud, enabling seamless deployment and management of resources. This series of interactive labs is designed to elevate your networking skills through practical exercises that cover configuration, management, and troubleshooting of AWS VPCs. Video tutorials provide clear, step-by-step guidance through real-world scenarios, helping you build confidence in configuring and optimizing AWS VPCs. Each lab is carefully designed to give you experience with AWS VPC architecture, subnets, route tables, and security groups directly within the AWS environment.
ISC2
Security Principles
Welcome to course 1 of 5 of this Specialization, Security Principles. After completing this course, the participant will be able to: Discuss the foundational concepts of cybersecurity principles. - Recognize foundational security concepts of information assurance. - Define risk management terminology and summarize the process. - Relate risk management to personal or professional practices. - Classify types of security controls. - Distinguish between policies, procedures, standards, regulations and laws. - Demonstrate the relationship among governance elements. - Analyze appropriate outcomes according to the canons of the ISC2 Code of Ethics when given examples. - Practice the terminology and review security principles. Agenda Course Introduction Module 1: Information Assurance Module 2: Risk Management Process Module 3: Security Controls Module 4: Governance Module 5: ISC2 Code of Ethics Module 6: Course Summary This training is for IT professionals, career changers, college students, recent college graduates, advanced high school students and recent high school graduates looking to start their path toward cybersecurity leadership by taking the Certified in Cybersecurity entry-level exam. There are no prerequisites to take the training or the exam. It is recommended that candidates have basic Information Technology (IT) knowledge. No work experience in cybersecurity or formal education diploma/degree is required.
Goodwill Industries International
Building Your Community Resources
This course, co-developed by Goodwill Industries International and World Education, is for anyone that wants to develop a comprehensive approach to assessing digital skills needs and equipping individuals and communities with the tools and resources needed to navigate the digital divide. The third course in the Digital Navigator Specialization Certificate will prepare you with the skills and knowledge to identify and provide resources to others and bolster their digital skills needed for workforce readiness, evaluate digital skills competencies for various stakeholders, and select tools that are appropriate for building digital skills literacy. No matter what your background is, this course will be useful if you are or want to become a community advocate, a direct-service professional, or someone who is passionate about addressing digital disparities. Learners should complete the first two courses of the specialization before beginning this course.