The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
EDUCBA
Machine Learning Projects in R with Caret
By the end of this course, learners will be able to prepare datasets, detect and handle missing values, apply imputation strategies, perform correlation analysis, address data imbalance, and implement clustering using the caret package in R. Participants will also gain hands-on experience in reproducing research results, validating data quality, and streamlining machine learning workflows. This course is designed for students, professionals, and data enthusiasts who want to strengthen their applied machine learning skills in R. Unlike typical theory-driven courses, it emphasizes project-based learning, walking learners step by step through a complete workflow — from reading datasets to advanced preprocessing and clustering. What makes this course unique is its focus on real-world problem solving, integrating missing data handling, preprocessing, and unsupervised learning into a single, cohesive framework. Learners will acquire not only technical skills but also the confidence to structure, execute, and interpret machine learning projects effectively.
University of Michigan
Writing and Editing: Revising
This fourth and final course in the “Good with Words: Writing and Editing” series will help you master perhaps the most important step in the writing process: revising. You’ll learn about the difference between editing and proofreading. You’ll practice “un-numbing the numbers” so that data and statistics you use are clear and compelling. And you’ll be introduced to a framework for giving and receiving feedback that helpfully systematizes what should be cut and what should be kept from each draft. As with the other three courses in this series, you will also get access to a wide range of books and other resources you can use even after you finish the course. These include: (1) the readings and exercises provided to the students who have taken the in-person version of this course at the University of Michigan and the University of Chicago; (2) two digital libraries of excellent writing from a diverse collection of journalists, scientists, novelists, poets, historians, and entrepreneurs; and (3) a monthly “Good Sentences” email.
Coursera
Small Business Marketing Using YouTube
In this 1-hour long project-based course, you will learn how to use YouTube to promote your small business, how to create a YouTube channel, how to customize your channel to attract the right audience, how to post videos, how to collaborate with other channels to improve client reach, how to interact with clients, and how to use YouTube analytics. This course will benefit small business owners with limited to no social media marketing experience. 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.
Universitat Autònoma de Barcelona
Arte 3D y animación en videojuegos
VERSIÓN EN ESPAÑOL En este curso abordamos los aspectos artísticos de la creación del videojuego. Para ello, proporcionaremos conocimientos y pautas sobre cómo diseñar la parte artística de un videojuego. Esto incluye diferentes aspectos. Desde la creación de entornos, al diseño de personajes, movimientos e incluso música. Todo el proceso buscará una coherencia que permita transmitir al jugador la experiencia que espera. Para definir y comprender mejor los conceptos se usan, como en el resto de cursos del Programa Especializado, ejemplos y referentes de videojuegos. IMPORTANTE En breve el curso dispondrá de subtítulos en inglés. __________ ENGLISH VERSION In this course we will talk on the video game's creation artistic aspects. In aim to do so, we will provide knowledge and guidelines on how to design a video game's artistic part. This includes different aspects. From the environments creation, to the characters' design, movement and even music. All this process will look for a cohesion which will allow us to give the desired experience to the player. To properly define and understand the concepts we will use -as in the other courses inside the Specialized Program- examples and video game referents. IMPORTANT English subtitles will be soon available.
Google Cloud
HTTPS Content-Based Load Balancer with Terraform
This is a self-paced lab that takes place in the Google Cloud console. This lab shows you how to create a HTTPS load balancer to forward traffic to a custom URL map, which then sends traffic to the region closest to you with static assets being served from a Cloud Storage bucket.
Technical University of Denmark (DTU)
Introduction to advanced tomography
In this course you get the chance to get teaching and hands-on experience with the complete workflow of high-resolution tomography analysis. You will get introduced to data acquisition, 3D reconstruction, segmentation and meshing and, finally, 3D modelling of data to extract physical parameters describing mechanical and flow properties. The teaching and the exercises will take place in close interaction with top experts in the field. Exercises will require some basic programming skills, and will be carried out in a common python environment.
Coursera
Empathic AI Communication and Analysis
Transform your customer communication skills by combining proven empathy frameworks with AI tools like ChatGPT and Claude. Whether you're in customer support, client services, or any people-facing role, you'll master techniques that turn difficult interactions into positive outcomes. You'll learn the LAER framework (Listen, Acknowledge, Explore, Respond)—a structured approach to empathic communication that builds trust and de-escalates conflict. You'll discover how to use ChatGPT to practice responses, analyze conversation sentiment, and identify improvement areas. Through realistic role plays and coach dialogues, you'll practice handling frustrated customers, conduct AI-assisted conversation analysis, and complete quality assessments. Most importantly, you'll develop judgment for when to follow AI suggestions versus trusting your own read. By course completion, you'll confidently apply empathic techniques, use AI tools critically for conversation analysis, and drive ongoing improvement. Essential skills for any customer-facing role in an AI-augmented workplace.
Packt
Service Integration and Management (SIAM) Foundation
Service Integration and Management (SIAM™) is an essential strategy in today’s complex, multi-vendor IT environments. It enables organizations to align diverse service providers under a single management framework, improving collaboration, accountability, and business value. In this course, you will explore the foundational concepts of SIAM, including its structures, principles, and practical implementation strategies. Through a structured learning path, you’ll develop the skills to manage service integration effectively using the SIAM roadmap, models, and aligned frameworks. What sets this course apart is its balance of theory and real-world application. You’ll gain insight into proven SIAM practices, industry-aligned roles, and actionable strategies for overcoming integration challenges and managing risk. This course is ideal for IT service management professionals, consultants, and leaders seeking to optimize service delivery across complex ecosystems. A foundational knowledge of service management frameworks like ITIL or COBIT is recommended. By the end of the course, you will be able to define SIAM principles, evaluate integration models, apply the SIAM roadmap, and design effective service structures and governance models. Copyright © 2021 Claire Agutter The author has asserted the rights of the author under the Copyright, Designs and Patents Act, 1988, to be identified as the author of this work. First edition published in 2017 by Van Haren Publishing. Second edition published in the United Kingdom in 2021 by IT Governance Publishing. Every possible effort has been made to ensure that the information contained in this course is accurate, and the publisher and the author cannot accept responsibility for any errors or omissions, however caused. Any opinions expressed in this book are those of the author, not the publisher. Websites identified are for reference only, not endorsement, and any website visits are at the reader’s own risk. No responsibility for loss or damage occasioned to any person acting, or refraining from action, as a result of the material in this publication can be accepted by the publisher or the author. Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form, or by any means, with the prior permission in writing of the publisher or, in the case of reprographic reproduction, in accordance with the terms of licences issued by the Copyright Licensing Agency. Enquiries concerning reproduction outside those terms should be sent to the publisher at the following address: IT Governance Publishing Ltd Unit 3, Clive Court Bartholomew’s Walk Cambridgeshire Business Park Ely, Cambridgeshire CB7 4EA United Kingdom www.itgovernancepublishing.co.uk
Google Cloud
Exploring the Lineage of Data with Cloud Data Fusion
This is a self-paced lab that takes place in the Google Cloud console. This lab shows how to use Cloud Data Fusion to explore data lineage - the data's origins and its movement over time.
Packt
How to Make Your Voice Heard & Articulating Your Value
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. Effective communication is key to personal and professional success, and this course provides practical strategies to ensure your voice is heard and valued. You’ll learn techniques to enhance vocal strength, presence, and clarity, while also mastering the art of communicating and articulating your value. Whether you're preparing for a public speaking engagement, negotiating, or simply engaging in everyday conversations, this course gives you the tools to speak with confidence and precision. The journey begins with building a solid foundation in confident communication, helping you overcome self-doubt and engage in any conversation with authority. As the course progresses, you'll explore practical speech improvement techniques like recording and analyzing your own speech, adjusting your speaking speed, and mastering dynamic speaking. In the later sections, you’ll learn how to clearly articulate your value in various situations using storytelling and adapting your message to different audiences. This course is ideal for professionals, entrepreneurs, and anyone looking to boost their communication skills. No specific prior knowledge is required, but participants should be interested in improving how they present themselves and their ideas. With a focus on confidence-building, this course is suitable for beginners who are looking to take their speaking abilities to the next level. By the end of the course, you will be able to confidently articulate your worth in any context, master dynamic speaking, and refine your communication for maximum impact in both professional and personal settings.
The University of Melbourne
Corporate Financial Decision-Making for Value Creation
In this course, participants will learn about the key financial decisions modern corporations face, as well as the alternative methods that can be employed to optimize the value of the firm’s assets. This is part of a Specialization in corporate finance created in partnership between the University of Melbourne and Bank of New York Mellon (BNY Mellon).
DeepLearning.AI
Pretraining LLMs
In Pretraining LLMs you’ll explore the first step of training large language models using a technique called pretraining. You’ll learn the essential steps to pretrain an LLM, understand the associated costs, and discover how starting with smaller, existing open source models can be more cost-effective. Pretraining involves teaching an LLM to predict the next token using vast text datasets, resulting in a base model, and this base model requires further fine-tuning for optimal performance and safety. In this course, you’ll learn to pretrain a model from scratch and also to take a model that’s already been pretrained and continue the pretraining process on your own data. In detail: 1. Explore scenarios where pretraining is the optimal choice for model performance. Compare text generation across different versions of the same model to understand the performance differences between base, fine-tuned, and specialized pre-trained models. 2. Learn how to create a high-quality training dataset using web text and existing datasets, which is crucial for effective model pretraining. 3. Prepare your cleaned dataset for training. Learn how to package your training data for use with the Hugging Face library. 4. Explore ways to configure and initialize a model for training and see how these choices impact the speed of pretraining. 5. Learn how to configure and execute a training run, enabling you to train your own model. 6. Learn how to assess your trained model’s performance and explore common evaluation strategies for LLMs, including important benchmark tasks used to compare different models’ performance. After taking this course, you’ll be equipped with the skills to pretrain a model—from data preparation and model configuration to performance evaluation.
Arizona State University
Sustainability Challenges for the Planet and Employers
This course builds on the foundational knowledge gained in the first course in the series. Learners will continue to shape their understanding of global problems like climate change while developing their skills in using sustainability indicators, managing waste streams, addressing challenges, and providing green building recommendations. Mixed modalities continue to be used to provide text, video, interactive activities, and peer reviews so all learners can add to their knowledge around sustainability issues. Content overviews and instructional lecture videos produced with ASU School of Sustainability professors are the cornerstones of the content presented in this course. Topical and practical knowledge is the central combination of elements driving this course. Through interactive learning objects and peer-reviewed submissions, learners have the opportunity to practice their skills and receive feedback from experts and their fellow learners. Learners also participate in regular knowledge checks throughout the course, with mid-course and final assessments to evaluate their overall learning. This course uses interactive activities, hands-on experiences, and opportunities to build tools like checklists and memo templates to help learners gain confidence in their skills and support their entry into the workforce. Building on the skills they have learned in the first course, this learning experience provides learners with more specialized knowledge while still tying it to real-world scenarios and skills that they will need when they get into the field as sustainability analysts.
Whizlabs
AWS: Identity and Access Management
AWS: Identity and Access Management Course is the third course of Exam Prep SCS-C02: AWS Certified Security – Specialty Specialization. This course focuses on designing, implementing, and troubleshooting authentication and authorization for AWS resources. The course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 2:00-2:30 Hours of Video lectures that provide both Theory and Hands-On knowledge. Also, Graded and Ungraded Quizzes are provided with every module in order to test the ability of learners. Module 1: Authorization in AWS Module 2: Authentication in AWS Module 3: Storage Security in AWS Two years of experience in troubleshooting issues involving AWS IAM and Amazon S3. Candidates being certified with AWS Solutions Architect Associate can prepare for this course and appear for the Security specialty exam. By the end of this course, a learner will be able to: - Explore policy evaluation and best practices by using AWS IAM. - Evaluate methods for managing identities and credentials in AWS - Troubleshoot authentication and authorization issues in AWS. - Design resource policies to restrict access to authorized users' using S3 bucket policies.
Scrimba
Intro to Supabase
In this practical and fast-paced course, you’ll learn how to build real-time data-powered applications using Supabase with JavaScript. Starting with a complete Supabase project setup, you'll learn how to interact with the database using supabase-js, perform advanced queries with aggregate functions, and manage state effectively within your app. You’ll then move into formatting the data for visual representation, setting up real-time subscriptions, and implementing form functionality to insert new data live into your database. In this course, you'll work on a project for a sales team. You'll create a database to hold sales data, fetch data for a dashboard visualization, and insert new data in the table via a form. By the end, you'll have a complete, interactive app that responds to changes in the database in real time, making this the perfect project to sharpen your frontend skills while exploring backend functionality.
Packt
Advanced Machine Learning and Deep 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. This advanced machine learning and deep learning course provides a robust foundation in these transformative technologies. Starting with an overview of deep learning, you'll explore its core concepts, real-world applications, and significance in AI's evolution. Practical aspects include neural network layers, activation functions, and performance metrics in model evaluation. Through hands-on coding labs, you'll cover regression, classification, and convolutional neural networks (CNNs), building and fine-tuning models, understanding loss functions, and using optimizers for accuracy. Emphasis is on frameworks like TensorFlow and PyTorch for developing robust neural networks. The course concludes with specialized topics such as autoencoders, transfer learning, and recurrent neural networks (RNNs). Interactive labs and projects will apply knowledge to complex data analysis, time-series prediction, and creating web applications with Shiny. Ideal for data scientists, machine learning engineers, and AI enthusiasts, prerequisites include Python proficiency and basic machine learning knowledge.