The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Northeastern University
Applied Natural Language Processing in Engineering Part 1
Welcome to this course on applied natural language processing in engineering. This course is designed to provide you with an in-depth understanding of NLP, a pivotal area of artificial intelligence that empowers computers to comprehend, interpret, and generate human language. Throughout this course, you will explore a wide range of topics, from fundamental NLP tasks like text classification and Named Entity Recognition (NER) to advanced techniques in neural machine translation and optimization methods critical for machine learning. We will delve into the complexities of teaching language to machines, addressing challenges like ambiguity, grammar, and cultural nuances. By the end of this part 1 course, you will have a foundational understanding of how modern NLP systems work - particularly those involving machine learning and deep learning. These topics will equip you to build, analyze and improve NLP systems across many applications.
Coursera
Building a Machine Learning Solution
Welcome to Building a Machine Learning Solution, where you'll journey through the complete lifecycle of a machine learning project. This capstone course covers critical steps from problem definition to deployment and maintenance. You'll learn to define clear problem statements, collect and preprocess data, perform exploratory data analysis (EDA), and engineer features to enhance model performance. The course guides you in selecting and implementing appropriate models, comparing classical machine learning, deep learning, and generative AI approaches. Emphasizing real-world considerations, you'll address scalability, interpretability, and ethical implications. You'll gain hands-on experience with tools like scikit-learn, TensorFlow, PyTorch, and more, ensuring you can deploy and monitor models effectively. By the end of this course, you'll be equipped to build end-to-end ML solutions that transform data into actionable insights, making informed decisions at each stage of development.
Columbia University
Decision Making and Reinforcement Learning
This course is an introduction to sequential decision making and reinforcement learning. We start with a discussion of utility theory to learn how preferences can be represented and modeled for decision making. We first model simple decision problems as multi-armed bandit problems in and discuss several approaches to evaluate feedback. We will then model decision problems as finite Markov decision processes (MDPs), and discuss their solutions via dynamic programming algorithms. We touch on the notion of partial observability in real problems, modeled by POMDPs and then solved by online planning methods. Finally, we introduce the reinforcement learning problem and discuss two paradigms: Monte Carlo methods and temporal difference learning. We conclude the course by noting how the two paradigms lie on a spectrum of n-step temporal difference methods. An emphasis on algorithms and examples will be a key part of this course.
Infosec
C++ Superpowers and More
Explore the C and C++ languages. Look at the specificity of the C/C++ languages and how this impacts security, ways C/C++ can interact with the external world, error handling, the execution environment and much more.
Google Cloud
Work with Gemini Models in BigQuery - 日本語版
이 과정은 BigQuery에서 생성형 AI 작업에 AI/ML 모델을 사용하는 방법을 보여줍니다. 고객 관계 관리와 관련된 실제 사용 사례를 통해 Gemini 모델로 비즈니스 문제를 해결하는 워크플로를 설명합니다. 이해를 돕기 위해 SQL 쿼리와 Python 노트북을 사용하는 코딩 솔루션을 단계별로 안내합니다.
Coursera
Deploy, Manage, and Orchestrate Your Models
Containerization is more than a deployment tool—it’s the backbone of reliable, scalable machine learning systems. In this intermediate-level course, you’ll learn how to package, deploy, and manage ML models using Docker and Kubernetes. You’ll start by exploring why containerization matters—how it ensures reproducibility and stability across environments. Then, you’ll move into orchestration, learning how Kubernetes automates deployment, scaling, and monitoring for real-world applications. Through concise videos, guided readings, and a hands-on project, you’ll write a Dockerfile, publish your image to an internal registry, and deploy it to a cluster using a Kubernetes configuration file. You’ll also practice testing and reflecting on your deployment process to strengthen your operational mindset. By the end, you’ll be able to build, deploy, and manage containerized ML applications confidently—skills essential for engineers, data scientists, and anyone bringing AI models into production.
Google Cloud
生成式 AI：掌握幕後技術與環境
「生成式 AI：掌握幕後技術與環境」是 Generative AI Leader 學習路徑的第三門課程。生成式 AI 正在改變我們的工作方式,以及我們如何與周遭的世界互動。身為領導者,您要如何駕馭 AI 強大的功能,創造實際業務成果?在本課程中,您將認識建構生成式 AI 解決方案時的各個層面、Google Cloud 產品,以及選擇解決方案時應考量的因素。
University of Colorado Boulder
Data Collection and Integration
The "Data Collection and Integration" course provides students with comprehensive techniques for gathering data from diverse sources, including files, relational databases, web pages, and APIs. Participants will gain practical experience in collecting and integrating data for further processing and analysis. The course emphasizes the utilization of appropriate tools and packages, such as Pandas, Beautiful Soup, and SQL, to effectively handle real-life datasets and address data integration challenges.
Universidad de Chile
Inclusión social de personas con discapacidad desde un enfoque de derechos.
La OMS en el año 2011 publicó el Informe Mundial sobre la Discapacidad, en el cual se evidencia un aumento en la prevalencia de discapacidad de un 15% (anteriormente se estimaba entre un 7 y un 10% de la población). Las personas que viven en situación de discapacidad presentan mayores niveles de deprivación en diferentes ámbitos: inserción al mercado del trabajo, nivel educacional, etc. Esto nos obliga como sociedad a repensar nuestro trabajo en esta materia desde un enfoque que garantice igual trato para todos. Pues, una sociedad que espere promover igualdad de oportunidades y espacios de desarrollo para todos sus miembros, debe poner especial atención con aquellos sectores que han sido postergados durante generaciones, esto ocurre con especial fuerza en nuestros países del tercer mundo. No obstante comprender el actual enfoque de Derechos permite orientar la acción hacía planes y programas que permitan garantizar accesibilidad e inclusión social para personas en situación de discapacidad. Nosotros buscamos promover que la labor social, laboral o profesional se enmarque en los principios y fundamentos del enfoque de Derechos en discapacidad, por lo que los estudiantes que desarrollen este curso desarrollen una mirada crítica de las prácticas de apoyo de las personas en situación de discapacidad. Posterior a 10 años del nacimiento de la Convención sobre los derechos de las personas con discapacidad, se hace urgente su difusión, comprensión y crítica por parte de los ciudadanos a objeto de modificar prácticas que hoy resultan contradictorias, ilegítimas e innecesarias, las que suelen atentar, en contra de la autonomía y derechos de las personas con discapacidad. El propósito del curso es promover que la labor social, laboral o profesional se enmarque en los principios y fundamentos del enfoque de Derechos en discapacidad. De esta manera los los estudiantes podrán reflexionar sobre el enfoque de Derechos consagrado en la Convención de Naciones Unidas sobre Derechos de las Personas con Discapacidad, las diferencias conceptuales entre modelos, enfoques y teorías en el ámbito de la discapacidad en su proceso de tránsito conceptual. De esta manera, los estudiantes analizarán distintos ámbitos de aplicación de dichos modelos y conceptualizaciones en ámbitos de salud, educación y trabajo, comprendiendo una visión integral del desarrollo humano de una sociedad desde el enfoque de derechos humanos.
University of California, Santa Barbara
Taxation Concepts
Learn the fundamentals of corporate taxation in the United States and how tax rules influence business decisions and compliance. In this course, you’ll explore how federal tax laws are structured and enforced, focusing on the Internal Revenue Code, Treasury Regulations, and the hierarchy of tax guidance used by accountants and tax professionals. You’ll examine how corporate taxation applies to different business structures, including C corporations and S corporations, and review how these entities report financial activity for tax purposes. The course introduces key components of corporate tax compliance, including Forms 1120 and 1120-S, and explains how businesses report income, expenses, depreciation, compensation, and gross receipts. Throughout the course, you’ll analyze practical scenarios that show how tax guidance affects real business decisions. By the end, you’ll understand how corporate tax rules shape compliance, reporting, and planning strategies used by businesses and their advisors. This course is designed for learners seeking a practical introduction to corporate taxation and provides foundational knowledge useful for accounting, tax, and finance careers.
National Taiwan University
職場素養 (Professionalism)
介紹國際職場素養的內涵及相關課題，培育學生應有的職場視野與能力，便利學生融入職場環境，迅速自新手成為高手，裕如地發揮所學與所長。
Google Cloud
Transformer Models and BERT Model - 日本語版
このコースでは、Transformer アーキテクチャと Bidirectional Encoder Representations from Transformers（BERT）モデルの概要について説明します。セルフアテンション機構をはじめとする Transformer アーキテクチャの主要コンポーネントと、それが BERT モデルの構築にどのように使用されているのかについて学習します。さらに、テキスト分類、質問応答、自然言語推論など、BERT を適用可能なその他のタスクについても学習します。このコースの推定所要時間は約 45 分です。
University of Minnesota
Introduction to UX Design MasterTrack Certificate Program
User experience is a highly in-demand field which requires a holistic understanding of the design process. This course is a "sample" of the UX Design MasterTrack certificate program. You will have the opportunities to explore core topics in UX including Ethics and Research, User Research, User Testing, and Visual Literacy as four modules. You can take the opportunity to gain some basic understanding of UX research, and take this course as a pathway to the UX Design MasterTrack certificate program. The assignments you have accomplished in this open course can be carried over to the UX Mastertrack certificate program. If you would like to continue learning after this open course, please visit our UX Design MasterTrack certificate program website: https://www.coursera.org/mastertrack/ux-design-minnesota
University of Colorado System
Fundamentals of Network Communication
In this course, we trace the evolution of networks and identify the key concepts and functions that form the basis for layered architecture. We introduce examples of protocols and services that are familiar to the students, and we explain how these services are supported by networks. Further, we explain fundamental concepts in digital communication, and focus on error control techniques that include parity check, polynomial code, and Internet checksum. Students will be required to have some previous programming experience in C-programming (C++/Java), some fundamental knowledge of computer organization and IT architecture and a background in computer science is a plus.
EDUCBA
PyMongo - Advanced
This advanced, project-based course is designed to empower learners with the skills to apply, analyze, and transform MongoDB data using the PyMongo library in Python. Starting from fundamental data handling operations and culminating in powerful aggregation techniques, the course offers a structured and practical pathway for working with real-world document-oriented databases. Learners will begin by exploring core database concepts, understanding MongoDB’s document model, and mastering the use of PyMongo for basic operations such as inserting, querying, sorting, and pagination. Progressing into more complex topics, the course introduces advanced cursor mechanics, indexing strategies for performance, and efficient result handling using limit, skip, and count operations. In the second phase, learners will construct aggregation pipelines to perform data summarization and transformation tasks. They will also convert raw MongoDB documents into structured pandas DataFrames to enable downstream analysis in Python workflows. Each concept is grounded in hands-on exercises and sample datasets, ensuring not just theoretical understanding but practical fluency. By the end of this course, learners will be equipped to design performant data access patterns, build efficient analytics pipelines, and extract actionable insights from NoSQL databases using Python.
Creo Incubator
Critical Thinking for Decision Making
The CREO Critical Thinking for Decision Making Course supports professionals in developing a structured approach to analysing problems and making well-reasoned decisions. The course focuses on critical thinking as an applied workplace skill—helping learners slow down automatic reactions, challenge assumptions, and evaluate information objectively before choosing a course of action. Participants explore practical tools for defining problems, identifying relevant evidence, and examining different perspectives. The course also addresses common cognitive biases and reasoning errors that can affect judgment, especially under pressure or uncertainty. Through real-world scenarios and applied exercises, learners practise building clear arguments, testing options against criteria, and communicating decisions with rationale. By emphasising systematic thinking and reflective questioning, the course enables learners to approach complex situations with greater clarity, consistency, and confidence. By the end of this course, you will be able to: - Define and frame problems using a structured approach - Identify assumptions, biases, and gaps in reasoning - Analyze information and viewpoints to evaluate options - Apply decision criteria to compare alternatives - Justify decisions using clear and evidence-based reasoning Prerequisites: - No prior training in critical thinking or logic is required. The course is suitable for professionals and emerging leaders who want to improve decision-making in workplace contexts.