The Global Scholarly Directory.
Discover world-class academic programs curated for the modern intellectual. Search through 19877+ degrees and professional certificates.
Coursera
Financial Analysis: Portfolios, Risks, Strategic Decisions
Understanding the basics of financial strategies, portfolio design, and risk management is key to making informed investment decisions and building a solid financial foundation. This knowledge is fundamental for anyone looking to navigate the financial markets effectively and crafting portfolios that are resilient to market fluctuations. The importance of this understanding ensures that their financial decisions align with their long-term goals and risk tolerance. The process of designing a portfolio to meet specific investment goals is a critical step that requires careful consideration of various factors, including risk tolerance, investment horizon, and financial targets. By examining real-life examples and actual portfolios, one can gain insight into the practical application of theoretical principles, learning how different strategies can be tailored to achieve desired outcomes. Finance professionals, from investment bankers to finance students, are united in their passion for navigating the financial landscape. With diverse backgrounds, they strive to optimize strategies and enhance portfolio performance, whether for high-net-worth clients or market analysis. Their commitment to mastering finance is evident in their collaborative, innovative approach and dedication to continuous learning. To engage in portfolio analysis and management effectively, individuals need a strong grasp of financial concepts including asset valuation, market dynamics, and investment instruments. Understanding investment principles like diversification, asset allocation, and risk-return trade-offs is crucial. Proficiency in financial mathematics and statistics is necessary for applying quantitative methods in portfolio optimization and risk assessment, facilitating professional growth in finance.
KodeKloud
AWS Certified AI Practitioner
Welcome to the transformative journey that is the AWS Certified AI Practitioner Course! In today's rapidly changing AI landscape, having a firm grasp of AI concepts is critical, but knowing how to implement these concepts on AWS is where the challenge—and opportunity—lies. If you've ever felt overwhelmed by the complexities of integrating AI into AWS, you're not alone. Each tutorial can seem straightforward, only to reveal its true difficulty when you're down in the weeds, applying AI to your AWS solutions. This course is crafted to address just that. Designed for those who already possess a foundational understanding of AWS, we focus on bridging the gap between theoretical knowledge and real-world AWS applications. Through practical, scenario-based learning, you'll gain the skills to navigate and excel in the AWS AI ecosystem, advancing beyond the basics with valuable, applicable insights. Additionally, this course will prepare you to confidently appear for the AWS Certified AI Practitioner exam, equipping you with the knowledge and skills to achieve this credential and validate your expertise in AI-powered AWS solutions. Course Modules 1. Fundamentals of AI and ML Delve into essential AI concepts, understanding the distinctions between AI, machine learning, and deep learning. You'll engage with various data types, learning methods, and identify practical AI and ML use cases, laying a robust foundation for your AI endeavors on AWS. 2. Fundamentals of Generative AI Focus on the unique attributes of generative AI, including tokens, embeddings, and foundation models' lifecycle. Discuss cost considerations and AWS infrastructure specific to generative AI, alongside real-world applications, advantages, and constraints. 3. Applications of Foundation Models Learn about designing and customizing applications using foundation models. From selecting and fine-tuning pre-trained models to implementing retrieval-augmented generation and vector databases, gain insights into effective AI model deployment on AWS. Explore best practices in prompt engineering and metrics for evaluating model performance. 4. Guidelines for Responsible AI Explore foundational principles and tools for creating responsible AI applications. Discuss responsible model selection, legal risk management, and bias mitigation, ensuring your AI solutions are both safe and ethical, grounded in transparent, human-centered design. 5. Security, Compliance, and Governance for AI Solutions Address key aspects of securing AI systems on AWS, from best practices in data engineering to regulatory compliance and governance strategies, ensuring your AI applications are secure, compliant, and trustworthy. 6. Conclusion and Next Steps Summarize key concepts, complete a final assessment, and explore resources for ongoing learning in the dynamic AWS AI/ML space. Reflect on AI's future impact within AWS and beyond, preparing you for continued advancement in this exciting field. Equip yourself with the skills to master AI on AWS through this highly practical, hands-on course, where theory meets the complexity of real-world application. Whether you're looking to enhance your current role or forge new paths in AI, this course is your launchpad into the future of AI on AWS.
New York Institute of Finance
Reinforcement Learning for Trading Strategies
In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, and incorporate RL into a momentum trading strategy. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).
Logical Operations
Tableau Desktop: Part 1
As technology progresses and becomes more interwoven with our businesses and lives, more and more data is collected about business and personal activities. This era of "big data" exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantage. The creation of data-backed visualizations is a key way data scientists, or any professional, can explore, analyze, and report insights and trends from data. Tableau® software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Tableau's data connection capabilities and visualization features go far beyond those that can be found in spreadsheets, allowing users to create compelling and interactive worksheets, dashboards, and stories that bring data to life and turn data into thoughtful action. This course is designed for professionals in a variety of job roles who are currently using desktop or web-based data-management tools to perform numerical or general data analysis. This includes capturing and reporting on data to peers, executives, and clients. These professionals must also provide data visualizations in reports or explain data analysis through visualizations. This course is also designed for students who plan to obtain the Tableau Desktop Specialist certification, which requires candidates to pass the Tableau Desktop Specialist exam, or the Tableau Certified Data Analyst certification, which requires candidates to pass the Tableau Certified Data Analyst exam. In this course, you will: identify basic Tableau capabilities; connect to and prepare data; explore data with views and visualizations; manage, sort, and group data; save, publish, and share data sources and workbooks; filter data in views; customize visualizations with annotations, highlights, and advanced features; create and enhance dashboards in Tableau; and create and enhance stories in Tableau. This course requires that you have access to Tableau Desktop through a trial Tableau account. You should also have access to Microsoft Office, particularly Excel and PowerPoint. The course setup instructions provided in the first module of the course go into more detail about the hardware and software requirements.
EDUCBA
Analyze Data Using R for Statistical and Predictive Modeling
By the end of this course, learners will be able to analyze data using R, apply statistical methods, build predictive models, and interpret analytical results for real-world decision-making. Learners will gain hands-on experience with R programming fundamentals, data manipulation, visualization techniques, and advanced analytics such as regression, decision trees, and time series analysis. This course is designed to guide learners from the basics of R—its origin, architecture, syntax, and data structures—to practical data analysis and business applications. Through structured modules, learners will work with vectors, data frames, loops, functions, and charts, and then progress to statistical analytics, distribution functions, and predictive modeling techniques. Real-world scenarios, including insurance industry case studies, help learners understand how analytics is applied in professional environments. What makes this course unique is its balanced focus on both programming and analytics, making it suitable for beginners as well as professionals transitioning into data analytics roles. With clearly aligned learning objectives, graded assessments, and practice quizzes, learners will build job-ready skills in R that can be applied across industries such as finance, insurance, and data science. Completing this course equips learners with a strong analytical mindset and practical R skills to confidently explore data, generate insights, and support data-driven decisions.
EDUCBA
Master SQL Server Concepts for Database Management
By the end of this course, learners will be able to explain relational database concepts, install and configure Microsoft SQL Server, design databases and tables, enforce data integrity using constraints, and write both basic and advanced SQL queries to retrieve and manipulate data effectively. This course provides a structured, beginner-friendly pathway to understanding Microsoft SQL Server – Important Concepts, making it ideal for students, aspiring data professionals, and working professionals who want to build strong database fundamentals. Learners will gain hands-on exposure to SQL Server architecture, services, and tools, while progressively developing skills in Data Definition Language (DDL), data insertion, querying, and advanced SQL operations such as joins, grouping, and aggregation. What makes this course unique is its concept-first approach combined with practical SQL execution, ensuring learners not only understand how SQL works but also why it works. The course follows a carefully sequenced learning design, reinforced with practice quizzes, graded assessments, and real-world SQL use cases. Upon completion, learners will be well-prepared to work with relational databases, support data-driven applications, and confidently pursue advanced SQL or database administration learning paths.
Microsoft
Automation and Scripting with Python
Description: This course focuses on automating tasks and improving efficiency using Python. You'll learn how to write scripts for file manipulation, data extraction, web scraping, and interacting with APIs. Benefits: Automate repetitive tasks, streamline workflows, and increase productivity in various domains using Python scripting. By the end of this course, you'll be able to: • Write scripts to automate file operations and data extraction. • Perform web scraping using BeautifulSoup and Scrapy. • Interact with REST APIs using the requests library. • Integrate with third-party services like email and cloud storage. • Schedule automated tasks using cron jobs and Task Scheduler. • Optimize and scale automation scripts for increased efficiency. Tools/Software: Python, os, shutil, glob, BeautifulSoup, Scrapy, requests, smtplib, imaplib, cron, Task Scheduler This course is for entry-Level professionals looking to build a foundational understanding and experience with Python, while seeking employment as a Python developer. No prior work experience or degree is required.
Coursera
Hands-On Python Challenge: TrendWave Media
This project-based course challenges you to demonstrate your data science mastery through a comprehensive real-world project using TrendWave Media's dataset. Beginning with industry expert insights into professional workflows, you'll establish a structured analytical approach to media engagement data before applying your skills independently in a guided project. The course combines authentic business context with technical application, allowing you to integrate and showcase the full spectrum of your Python data science capabilities. Through hands-on analysis and focused assessment, you'll experience the complete lifecycle of a data science project—from initial exploration to delivering actionable recommendations—creating tangible evidence of your ability to derive value from complex datasets in professional contexts. Upon completion, you'll be able to: • Apply Python data science techniques to extract meaningful insights from real-world media engagement data • Implement professional data science workflows that follow industry best practices • Develop a portfolio-ready project that demonstrates your ability to solve business problems through data analysis • Demonstrate mastery of key data science concepts and techniques through comprehensive assessment
University of Michigan
Debugging: Hunting and Squashing Bugs
Learning how to debug is the most valuable skill to develop as you learn to program. This four-week course from the University of Michigan will help you improve your programming ability by providing you with the skills you need to understand and debug code. What’s more, you’ll learn the crucial techniques to help minimize mistakes and problems in your code. Most modern development environments contain a debugger, which you can use to find bugs and understand what is happening in your code. However, many people still rely on print statements when they debug. This course will help you gain confidence in using debuggers, so you can spend less time seeking out and fixing bugs and focus on building exciting new programming projects. The majority of coding errors occur when the programmer doesn’t understand the code or makes mistakes with the language, resulting in bugs. In this course, you’ll gain the knowledge and skills needed to spot and solve semantic and syntax errors more easily. You’ll also streamline your coding process by learning to write and run unit tests to examine and check your code. This course is designed for those interested in developing their Python skills or communicating with other programmers in a professional setting.
Epic Games
Game Development and Prototyping
In this course, you will be introduced to game development and prototyping for games. Courses 1-4 are highly recommended while Courses 5-7 create the foundational Unreal Engine project, assets and code used throughout this course. This course requires no previous experience and aimed at beginners. This course explores 6 different game modes: Stealth Survival, Platformer, Capture the Flag, Action Combat, Crafting, and Story. This course will include a pre-production phase where learners will break down the design of each mode using Obsidian. Understanding the core gameplay experience each mode is intended to design. This pre-production phase will not only outline gameplay features but also how you can reuse assets and code for quick prototyping. After pre-production, there is a module dedicated to creating each game mode. This will include game mode-specific code, design and iteration. By the end of this course you will package your project to be in a visually presentable format for your portfolio.
The University of Edinburgh
Intellectual Humility: Science
It’s clear that the world needs more intellectual humility. But how do we develop this virtue? And why do so many people still end up so arrogant? Do our own biases hold us back from becoming as intellectually humble as we could be—and are there some biases that actually make us more likely to be humble? Which cognitive dispositions and personality traits give people an edge at being more intellectually humble - and are they stable from birth, learned habits, or something in between? And what can contemporary research on the emotions tell us about encouraging intellectual humility in ourselves and others? Experts in psychology, philosophy and education are conducting exciting new research on these questions, and the results have important, real-world applications. Faced with difficult questions people often tend to dismiss and marginalize dissent. Political and moral disagreements can be incredibly polarizing, and sometimes even dangerous. And whether it’s Christian fundamentalism, Islamic extremism, or militant atheism, religious dialogue remains tinted by arrogance, dogma, and ignorance. The world needs more people who are sensitive to reasons both for and against their beliefs, and are willing to consider the possibility that their political, religious and moral beliefs might be mistaken. The world needs more intellectual humility. In this course, we will examine the following major questions about the science of intellectual humility: • How do we become intellectually humble? • What can human cognition tell us about intellectual humility? • How does arrogance develop, and how can we become more open-minded? • How do emotions affect our ability to be intellectually humble? All lectures are delivered by leading specialists, and the course is organised around a number of interesting readings and practical assignments which will help you address issues related to humility in your daily life. This course can be taken as a part of a series which explores the theory, the science and the applied issues surrounding intellectual humility. In the previous course on the theory behind intellectual humility, we considered how to define intellectual humility, the nature of an intellectual virtue, and how we know who is intellectually humble. If you are interested, complete all three courses to gain a broader understanding of this fascinating topic. Look for: • Intellectual Humility: Theory - https://www.coursera.org/learn/intellectual-humility-theory • Intellectual Humility: Practice - https://www.coursera.org/learn/intellectual-humility-practice Learners can apply for Financial Aid directly with Coursera to assist with the cost of accessing the full course and gaining a certificate for successfully completing the course.
Coursera
OpenAI Assistant: Create a Code to UML-Diagram generator
Your department is steadily inundated with projects and has tight deadlines to meet. The last thing you want is to sift through non-technical user stories, translate them into technical requirements, and discuss them internally in your department. Using an AI-UML Diagram Generator will simplify the process of creating UML diagrams, making it easier for developers to visualize and understand the structure and relationships of their projects. The AI-UML Diagram Generator can read and interpret code, then translate it into a visually understandable UML diagram. It also provides a way for non-technical stakeholders to comprehend the intricate details of the system's architecture. By automating the creation of UML diagrams, the tool will save time, reduce errors, and improve collaboration. Provided that this Assistant will enhance the capabilities of ChatGPT, the adoption success of the developers, software and system architectures is guaranteed. Let's dive into this AI-UML generator starting with ChatGPT, moving to the playground, and ultimately implementing an Assistant with whom we can interact using a custom UI. If you are a developer interested in diving into creating an Assistant with OpenAI--especially one that leverages code interpreter capabilities, then join us as we develop a new tool to aid our team. Learners should be able to understand an entity Relationship UML diagram and have experience using libraries in Python.
National Taiwan University
東亞儒家：人文精神一(East Asian Confucianisms: Humanism (1))
本課程從現代觀點探討東亞儒家人文傳統之核心價值，包括孔子、孟子、朱子及日韓儒者的生命智慧，以及作為儒家對照系統的道家與佛教的生命智慧等主題，討論儒家人文傳統在臺灣及其與21世紀的互動。藉由講授、單元作業等，提昇修課學生對於東亞人文精神的熟悉度，奠定其運用傳統文化精神資源，以因應21世紀新挑戰的能力。
Starweaver
Retail Sales Psychology: The Essentials of Selling More
This course redefines B2B sales training through a blend of neuroscience, AI, and behavioral psychology. Designed for busy professionals, each 90-second lesson delivers a pivotal insight that reshapes how sellers engage, persuade, and close. Grounded in how modern buyers actually make decisions, the course offers practical, evidence-based techniques that can be applied immediately. Backed by research and optimized for attention, this high-impact format drives completion rates of over 85%—far exceeding traditional training. You'll gain AI-enhanced methods to decode buyer behavior, sharpen your messaging, and elevate your sales effectiveness across any channel. Whether you're a sales leader or early-career rep, this course gives you a competitive edge in today’s fast-evolving B2B landscape.
University of Western Australia
Assessment, Interviewing and Onboarding
Developing a robust, responsive recruitment process is one of several integrated organizational activities that must be embedded to achieve greater diversity and inclusion. In this course, you will learn about the pivotal role recruitment plays in building and sustaining a diverse workforce and inclusive workplace. By examining some of the dominant traditional approaches to recruitment, you will understand how, in the contemporary global, social, and technological environment, many are no longer "fit for purpose," limited in their capacity to seek out diversity or recognize the employee attributes that support inclusion. For example, this course will examine how unconscious bias can compromise efforts unless expressly addressed in the recruitment process. This course is one of four that comprise the Recruiting for Diversity and Inclusion Specialization, offered by the University of Western Australia. Complete them all to gain an in-depth understanding of this fascinating and important topic.
Logical Operations
Adobe Photoshop CC: Part 2
Adobe® Photoshop® is a leading graphic creation application, popular among graphic designers, illustrators, and photographers. Photoshop's numerous features work together to provide a comprehensive toolset for you, the design professional. This course delves into some of the more advanced image creation and editing techniques, and offers you hands-on activities that demonstrate how these techniques can be used in combination to create exciting visual effects. This course is a great component of your preparation for the Adobe Certified Professional (ACP) in Visual Design Using Adobe Photoshop exam. Target students include professional or amateur photographers who want to use the robust features of Photoshop to enhance, modify, and organize their photographs, and anyone interested in working toward the Visual Communication with Adobe Photoshop exam certification. In this course, you will: se brushes, gradients, and tool presets to create raster images; apply vector paths, shape drawing tools, type, and type special effects; apply advanced layer techniques with masks, filters, layers, and smart objects; apply actions and batch processing to automate tasks; edit video by using timelines, transitions, graphics, titles, and animation; and set project requirements by identifying the purpose, audience, copyright rules, and project management tasks. This course requires that you have Adobe Photoshop installed on a Windows PC. The course setup instructions provided in the first module of the course go into more detail about the hardware and software requirements.