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Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
EDUCBA
Analyze and Build Dashboards Using AWS QuickSight
Learners will understand the fundamentals of AWS QuickSight, analyze datasets, apply data visualization techniques, and construct professional, insight-driven dashboards for business decision-making. By the end of this course, learners will be able to transform raw data into meaningful visual insights using industry-standard business intelligence practices. This course is designed to provide a structured, hands-on learning experience with AWS QuickSight, starting from project orientation and core concepts to advanced visualizations and dashboard design. Learners will gain practical exposure to adding datasets, creating charts, working with multiple sheets, applying themes, using tables and conditional formatting, and designing dashboards tailored to different audiences. Completing this course equips learners with in-demand data analytics skills that are directly applicable in real-world business environments. Unlike theory-heavy programs, this course emphasizes practical workflows, guided demonstrations, and best practices for building scalable, cloud-native dashboards. Whether learners are aspiring data analysts, business intelligence professionals, or working professionals seeking to enhance reporting capabilities, this course offers a clear, job-relevant pathway to mastering AWS QuickSight and delivering actionable insights with confidence.
Erasmus University Rotterdam
지속 가능한 금융의 원칙
금융은 더 나은 세상을 향하기 위한 걸림돌로 널리 알려져 있습니다. 지속 가능한 금융의 원칙에서는 이에 대응하기 위해 금융 부문을 동원하는 방법을 설명합니다. 사회적 목표를 달성하기 위해 금융을 수단으로 활용하여 지구 및 경제를 현재의 경로가 아니라 모두가 지속 가능한 세계로 향하도록 방향을 전환할 수 있습니다. 이번 강의를 통해 UN 지속가능발전목표와 사회적 및 환경적 요인을 외부 효과로 간주하지 않는 방법을 학습하게 되고, 지속 가능한 금융 및 자산 관리, 효과적인 소통, 지속 가능성 시나리오 분석 및 장기적 가치 창출에 관한 내용을 더 자세히 배우게 됩니다. 강의 후반부에는 지속 가능한 금융을 지속 가능성으로의 이행을 촉구하는 도구로 활용하는 방법을 이해할 수 있습니다.
Google Cloud
Classify Text into Categories with the Natural Language API
This is a self-paced lab that takes place in the Google Cloud console. In this lab you’ll learn how to classify text into categories using the Natural Language API.
Alfaisal University | KLD
أسرار النجاح في العمل | Secrets of Success at Work
النجاح أمر يسعى إليه جميع الأفراد في مجال عملهم، ولكن من منهم يعرف أسرار الوصول إليه؟ يعمل في المؤسسات عشرات الموظفين، أو المئات أو حتى الآلاف منهم، فكيف تتميز بين كل هؤلاء لتصبح شخصاً محورياً ومؤثراً لا غنى عنه في مجال عملك؟ وكيف يُمكنك اختصار سلم نجاحك بأسلوب مهني وأخلاقي، حتى تُحقق ما تطمح إليه في عدد أقل من السنوات؟ إن نقطة البدء تتمثل في رغبتك الحقيقية بتحقيق النجاح والتميز في عملك؛ تلك الرغبة التي ستدفعك لإعادة اكتشاف مواهبك وقدراتك والاستفادة منها وتوظيفها لتحقيق ما تتمنى. 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 الطاقة الإيجابية، 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: التعرف على مفاتيح النجاح كي تصبح شخصاً محورياً في مجال عملك، شرح الأساليب التي يمكن من خلالها اختصار طريق النجاح بصورة أخلاقية ومهنية، فهم كيفية أن تصبح شخصاً محورياً في العمل والمهارات التي تحتاجها، شرح منطق العمل العميق الذي يتبناه الشخص المحوري في العمل.
The Open University
Critical thinking for sustainable business solutions
This course will help you to discover how to flip your logical thinking and reasoning mind to enable you to generate a wide range of innovative ideas. Using techniques such as the SCAMPER (Substitute, Combine, Adapt, Modify, Put, Eliminate, Reverse) method to assist in generating ideas, you will assess when to apply the different thinking modes appropriately in the ideation process. You’ll apply critical reflective thinking to avoid personal biases and unintended consequences when you develop potential solutions. You will also analyse proto-concepts critically to ensure their suitability and the likelihood of positive impact. Via text-based resources and task books, you’ll gain comprehensive understanding and benefit from in-depth reference points as you formulate your ideas and plans.
Google Cloud
Put It All Together: Prepare for a Cloud Security Analyst Job
You made it! It’s the fifth and final course of the Google Cloud Cybersecurity Certificate. It’s time to start polishing the resume and getting ready for interviews! In this course, you’ll review cloud security-focused career resources designed to get you job ready!
Universidad Austral
Educación ambiental para la biodiversidad
En la actualidad, la crisis ambiental ha adquirido notoria visibilidad y cada vez son más los conflictos sociales y ecológicos a nivel global y local. Este contexto nos demanda problematizar la realidad socio ambiental, repensar formas para reconectarnos con la naturaleza y crear conciencia de la interdependencia y la corresponsabilidad a través de la educación ambiental. Este curso tiene como propósito brindar perspectivas, conocimientos y estrategias en torno a la educación ambiental desde una mirada integral, haciendo foco en la biodiversidad. En un tiempo en el que la trama de la vida se encuentra amenazada, reconocemos la importancia de atender a las metas de los Objetivos de Desarrollo Sostenible (ONU, 2015) y proponemos pensar la educación ambiental para la biodiversidad como herramienta de cambio biocultural promoviendo la conservación, la restauración, el uso sustentable y la regeneración de la naturaleza. A su vez, este curso ofrece distintos lineamientos y estrategias pedagógicas para llevar adelante acciones ambientales participativas en diferentes ámbitos y contextos; tejiendo redes, activando alianzas y teniendo como premisa la participación social y la ciudadanía ambiental. Esta propuesta es accesible a todas las personas con inquietudes ambientales, sociales y educativas. Al ser un curso introductorio, no es necesario contar con conocimientos científicos ni saberes específicos avanzados. Por el contrario, se espera contar con una participación amplia y diversa en términos de formación, trayectorias y expectativas de intervención.
Packt
Intermediate Data Manipulation and Machine Learning
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. In this comprehensive course, you will explore artificial intelligence (AI) and its core concepts, forming a solid foundation for machine learning. You will delve into regression analysis, applying univariate, polynomial, and multivariate regression techniques to real-world problems through interactive labs. Next, you will learn model preparation and evaluation, focusing on underfitting, overfitting, data splitting, and resampling methods, alongside regularization techniques to enhance model performance. The course covers classification methods, including confusion matrices, ROC curves, decision trees, random forests, logistic regression, and support vector machines, all paired with practical labs. You will also explore ensemble models and association rules, like the Apriori algorithm, to uncover hidden data patterns. Designed for data scientists, machine learning enthusiasts, and technical professionals, this course requires a basic understanding of machine learning concepts and Python programming. Learning outcomes include grasping AI and machine learning fundamentals, applying regression analysis, building and evaluating models, implementing classification techniques, performing clustering and dimensionality reduction, uncovering patterns with association rules, and applying reinforcement learning principles.
University of Illinois Urbana-Champaign
Auditing II: The Practice of Auditing
This course provides a continuation of the intensive conceptual and applied introduction to auditing in society begun in Auditing I: Conceptual Foundations of Auditing. It focuses on a conceptual framework that is applied by audit professionals to assess, evaluate, and manage audit risks and evidence.
Codio
Data Security for Web Developers
This course is designed for novice learners looking to broader their knowledge of how to secure data for the web applications they have developed. The course starts with foundational ideas like SSL/TLS certificates, rules governing security like GDPR, and handling secrets. The second module is devoted to cryptography, while the third module covers access control.
Coursera
Databricks Machine Learning Fundamentals
In this course, you will learn the fundamentals of using Databricks for machine learning. You will tackle the challenge of disjointed tools and master production-grade machine learning on Databricks. This course guides you through the complete end-to-end ML lifecycle on a single platform, giving you the practical skills to build robust, deployable solutions. You'll start by building a solid data foundation, using Apache Spark to ingest, clean, and engineer high-quality features. Next, master MLOps by using MLflow to systematically track and compare experiments, bringing reproducibility and rigor to your workflow to identify the best model. Finally, close the loop by deploying your models into production. You will use the MLflow Model Registry for versioning and governance before deploying your model as a live, real-time REST API endpoint. Through a series of hands-on labs and a final capstone project, you'll gain the confidence to build, track, and deploy sophisticated ML models, leaving with a portfolio-ready project that makes you a more effective and valuable data professional. This course is designed for intermediate learners who are familiar with basic machine learning concepts and want to learn how to apply them in Databricks for real-world projects. Learners should have a basic understanding of Python, including Pandas and Scikit-learn, along with fundamental machine learning concepts. By the end of this course, learners will be able to apply the full ML lifecycle on the Databricks platform, from data preparation and analysis to model deployment. They will also gain the skills to track experiments and manage models using Databricks and MLflow, ensuring a streamlined, reproducible workflow. Additionally, learners will be equipped to deploy machine learning models effectively using the MLflow Model Registry and Databricks Model Serving.
University of California San Diego
Genome Assembly Programming Challenge
In Spring 2011, thousands of people in Germany were hospitalized with a deadly disease that started as food poisoning with bloody diarrhea and often led to kidney failure. It was the beginning of the deadliest outbreak in recent history, caused by a mysterious bacterial strain that we will refer to as E. coli X. Soon, German officials linked the outbreak to a restaurant in Lübeck, where nearly 20% of the patrons had developed bloody diarrhea in a single week. At this point, biologists knew that they were facing a previously unknown pathogen and that traditional methods would not suffice – computational biologists would be needed to assemble and analyze the genome of the newly emerged pathogen. To investigate the evolutionary origin and pathogenic potential of the outbreak strain, researchers started a crowdsourced research program. They released bacterial DNA sequencing data from one of a patient, which elicited a burst of analyses carried out by computational biologists on four continents. They even used GitHub for the project: https://github.com/ehec-outbreak-crowdsourced/BGI-data-analysis/wiki The 2011 German outbreak represented an early example of epidemiologists collaborating with computational biologists to stop an outbreak. In this online course you will follow in the footsteps of the bioinformaticians investigating the outbreak by developing a program to assemble the genome of the E. coli X from millions of overlapping substrings of the E.coli X genome.
Google Cloud
Dataproc: Qwik Start - Command Line
This is a self-paced lab that takes place in the Google Cloud console. This lab shows you how to create a Google Cloud Dataproc cluster, run a simple Apache Spark job in the cluster, then modify the number of workers in the cluster, all from the gcloud Command Line. Watch these short videos, Dataproc: Qwik Start - Qwiklabs Preview and Run Spark and Hadoop Faster with Cloud Dataproc.
EDUCBA
Deep Learning with R: Build & Predict Neural Networks
By completing this course, learners will be able to prepare datasets in R, apply statistical and visualization techniques, build regression models, and design, run, and evaluate neural networks. The course begins with data preparation essentials, including working with dataframes, descriptive statistics, and environment setup, ensuring learners can confidently manage their workflow. It then advances to data visualization, where learners generate line graphs, scatter plots, and advanced visualizations to interpret patterns and relationships. Regression modeling concepts are introduced to provide a solid predictive foundation. Finally, the course transitions to deep learning, guiding learners through dataset preparation, neural network coding, multilayer perceptron (MLP) architecture, and predictive testing. What makes this course unique is its balance of theory and hands-on application using R, a widely used tool in both academia and industry. Learners not only gain the technical skills to execute commands and build models but also develop the critical thinking needed to evaluate results in real-world contexts. Whether new to machine learning or seeking to expand into deep learning, this course provides a structured, practical pathway to mastering neural networks with R.
Coursera
Build a Budget and Analyze Variance using Google Sheets
By the end of this project, you will be able to build a simple budget using Google Sheets. You will be able to easily capture variances and identify trends. You will be able to format your budget, identify and communicate drivers of variances and make the budget presentable. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Coursera
Align AI: Finance, Strategy, and Funding
AI projects often stall—not because the technology isn’t ready, but because they fail to align with strategy, prove financial viability, or persuade executives to fund them. Align AI: Finance, Strategy, and Funding equips intermediate-level project and program managers with the skills to bridge that gap. In Lesson 1, you’ll analyze corporate strategy and OKRs to confirm that AI initiatives directly support financial targets. In Lesson 2, you’ll evaluate financial viability using cost-benefit analysis, discounted cash flow, and sensitivity testing to assess whether AI features create measurable value. In Lesson 3, you’ll integrate strategy and financials into a persuasive, executive-ready business case designed to secure funding. Through case studies, readings, hands-on labs, and reflective dialogues with Coursera Coach, you’ll practice real-world tasks like backlog prioritization, financial modeling, and business case drafting. By the end, you’ll be ready to turn promising AI ideas into fundable, strategically aligned initiatives.