Earn Coins on World-Class Courses

In this course, you’ll learn how to create Tableau dashboards that connect data to decision-making. Starting with stakeholder planning and data requirements, you’ll define goals, success metrics, and key questions. Then, you’ll clean and prepare a real-world tech salary dataset using Tableau’s filtering, aliasing, and data type tools. You’ll turn these insights into impactful dashboards using calculated fields, grouping, and interactivity. Finally, you’ll explore how to interpret and present dashboards effectively through Socratic dialogue—critiquing design choices, analyzing KPIs, and refining your data story. By the end, you’ll be able to deliver dashboards that are insightful, persuasive, and tailored to audience needs.

この一連のコースでは、Looker デベロッパーを目指している人にクラウドと Looker のデータを紹介します。クラウドでデータを管理する方法と、データを使用して組織に価値を生み出す方法の背景が含まれています。学習の過程では、組織のデジタル変換におけるデータの役割を理解し、ビジネス アナリストが Looker を使用してデータを分析および視覚化する方法を学習し、最後に、Looker デベロッパーとして必要なスキルを学び、Looker Modeling Language（LookML）を使用して、組織がセルフサービスのデータ探索、分析、および視覚化を実行できるようにします。

This is a master class in gaining a competitive marketing advantage. Professor Jagdish Sheth, 2020 Padma Bhushan Award winner for Literature and Education, guides you through proven strategies and practical steps for implementing technology, segmentation, differentiation, and positioning into your marketing plan. Professor Sheth shares wisdom and insight from decades of experience, years of research, and recommendations from multiple senior industry leaders to help grow your brand and set your business apart from the competition.

Designing the customer and user experience is essential to creating great products today. Gone is the old paradigm of “form follows function” model of design. The process must be iterative and follow the best product design and development processes. While designing a great user experience can be a lengthy and expensive process, there are approaches to doing it faster and smarter, without compromising results. This essential product management course explains key design thinking principles around personas, story mapping, and prototyping. Product managers need to know and appreciate product designer tools and processes. By combining these principles with good scrum processes, you’ll learn to create great products that don’t sacrifice design for functionality or feasibility. This course enables students to transition from ideas to prototyping and concept testing of their products and services. Students learn how best to effectively translate ideas into marketable offerings so that the best product and service ideas are harnessed and create real value for customers and the organization. Emphasis is placed on an integrated and interdisciplinary approach to engineering design, concurrent engineering, design for manufacturing, industrial design, and the business of new product development. Topics include design methods, modeling and simulation, material and manufacturing process selection, platform and modular design, mass customization, planning and scheduling.

At the center of a good story are the characters in it. In this course aspiring writers will discover how to build and bring to life complex, vivid and unforgettable characters. We will study the choices a writer makes to bring all characters to life on the page, and we will perform written exercises in order to develop a variety of writing and pre-writing techniques, in order to create a variety of characters. We will learn how to use our own life experiences, and the people we know (and how not to!). We will develop inner (thoughts and feelings) and outer (appearance, habits, behavior) lives for our characters and see how that can lead us to richer and more interesting stories. We will breathe life into our characters and let them surprise us.

Thinking and doing the same things faster and better is not enough for innovation; we need creativity. Fortunately, creativity is a skill you can learn. This course will examine when, why, and how you can be creative so you can go through the creative process more efficiently and effectively. It teaches concrete steps to enable you to change your perspective to see new possibilities and solutions. It clarifies what to expect from the creative process and provides support for how you can sustain your progress. It also provides guidance on leading a supportive culture for creativity. The result is an ability to increase your own creativity and that of your teams and organizations so as to recognize and develop new opportunities. You will be able to: - Identify and generate opportunities to be creative and launch the innovation process - Intentionally and confidently enter and proceed through the creative process - Foster and sustain the creativity of others This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/.

In this course, you will use business and industry analysis to understand companies, projects, business models, and financing proposals. You will then prepare qualitative risk analysis for specific companies to use as the basis for financial analysis, project analysis, and risk decisions. Lastly, you will understand how to use financial ratios and financial metrics to evaluate a company or project’s profitability, balance sheet, capital structure, and cash flow to assess overall financial performance and risk profile.

Cryptography is an indispensable tool for protecting information in computer systems. In this course you will learn the inner workings of cryptographic systems and how to correctly use them in real-world applications. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic. We will examine many deployed protocols and analyze mistakes in existing systems. The second half of the course discusses public-key techniques that let two parties generate a shared secret key. Throughout the course participants will be exposed to many exciting open problems in the field and work on fun (optional) programming projects. In a second course (Crypto II) we will cover more advanced cryptographic tasks such as zero-knowledge, privacy mechanisms, and other forms of encryption.

Master the strategies and tools that enable you to form, join and lead teams more effectively. In this five-course specialization, you learn how to: · Recognize aspects of team culture · Draw out the collective wisdom of diverse teams · Handle conflict · Establish common ground rules · Maximize team performance · Create a team culture of continuous learning The program culminates in a capstone project in which you apply the skills you learned. You observe, diagnose and make recommendations to solve a team culture problem in a real-world case provided by N2Growth, a global consultancy focused on cultural transformation and leadership development.

This is a master class in Customer Centricity. Professor Jagdish Sheth, 2020 Padma Bhushan Award winner for Literature and Education, guides you through proven strategies and practical steps for implementing customer centricity practices into your business. Professor Sheth shares wisdom and insight from decades of experience, years of research, and recommendations from multiple senior industry leaders to help grow your business and cut costs by keeping the customers you have by creating a customer centric culture.

This course will highlight the potential of quantitative marketing research for assessing new product opportunities. In addition to focusing on the skills and practices for a successful New Product Development (NPD), the course will illustrate the multi-faceted challenges of NPD using authentic business situations. The first module will provide business practice foundations to help learners devise creative solutions to problems using a design-thinking framework. Learners will experience the idea creation process and then apply the role of surveys for evaluating consumer responses to an idea before introducing a product to market. The second module will explore the technique of conjoint analysis for quantifying the customer benefits, customer values, and the trade-off he or she is willing to make between the price of the product and desired features of the product or service. Concept testing identifies perceptions, wants, and needs of a product or service as the foundation of targeting and positioning a product in the marketplace. The third module will describe a multitude of tools for assessing technology readiness and defining the product features to target the key customer need requirements. Learners will hear an in-depth interview with one of the leading U.S. business executives on the management challenges of innovation. Learners will develop a survey (with appropriate data privacy agreements) and analyze the data for decisions about the pricing and positioning a new product into a focused market. The fourth module will illustrate the use of the tools to create a sales and pricing forecast for a new product. Three new product ideas representing three different types of market unknowns will be analyzed using market research tools. Upon completion of this course, the learner will have defined and redefined their product idea and created a credible sales forecast for use in an overall business case.

Data breaches occur nearly every day. From very large retailers, down to your fantasy football website, and anywhere in between, they have been compromised in some way. How did the attackers get in? What did they do with the data they compromised? What should I be concerned with in my own business or my systems? This course is the second course in the Practical Computer Security. It will discuss types of threats and attack vectors commonly seen in today’s environment. I hate to be the bearer of bad news, but threats are all over the place! This course isn’t designed to insight fear that there is no hope for keeping systems and business secure, but rather educate you on how attacks are carried out so that you have a better sense of what to look out for in your business or with your systems.

In this specialization, you will learn how to define Cybersecurity risk and discuss the threats that create it while you also learn to describe the role of Cybersecurity management in the management of Cybersecurity risk. You will go on to understand the elements of a general risk management framework as well as how to develop and administer a risk management effort. Along the way you will learn about the dominant standards and frameworks in risk management, and the tools used to support them.

In this specialization, you will learn how to define Cybersecurity risk and discuss the threats that create it while you also learn to describe the role of Cybersecurity management in the management of Cybersecurity risk. You will go on to understand the elements of a general risk management framework as well as how to develop and administer a risk management effort. Along the way you will learn about the dominant standards and frameworks in risk management, and the tools used to support them.

Welcome to Data Analytics Foundations for Accountancy II! I'm excited to have you in the class and look forward to your contributions to the learning community. To begin, I recommend taking a few minutes to explore the course site. Review the material we’ll cover each week, and preview the assignments you’ll need to complete to pass the course. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center. Good luck as you get started, and I hope you enjoy the course!

Athletes, lawyers and team executive experts provide insight in how law and regulations intersect with data analytics and sports management techniques for best practices in the sports industry. Several courses provide the basis for how data analytics function within player evaluation, team performance, and roster management. The specialization introduces various regulatory, managerial and legal frameworks that includes athlete representation, facilities, and event management and conclude with various jobs available in sectors of the sports industry.

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales. In this course, you will learn the landscape of relevant systems, the principles on which they rely, their tradeoffs, and how to evaluate their utility against your requirements. You will learn how practical systems were derived from the frontier of research in computer science and what systems are coming on the horizon. Cloud computing, SQL and NoSQL databases, MapReduce and the ecosystem it spawned, Spark and its contemporaries, and specialized systems for graphs and arrays will be covered. You will also learn the history and context of data science, the skills, challenges, and methodologies the term implies, and how to structure a data science project. At the end of this course, you will be able to: Learning Goals: 1. Describe common patterns, challenges, and approaches associated with data science projects, and what makes them different from projects in related fields. 2. Identify and use the programming models associated with scalable data manipulation, including relational algebra, mapreduce, and other data flow models. 3. Use database technology adapted for large-scale analytics, including the concepts driving parallel databases, parallel query processing, and in-database analytics 4. Evaluate key-value stores and NoSQL systems, describe their tradeoffs with comparable systems, the details of important examples in the space, and future trends. 5. “Think” in MapReduce to effectively write algorithms for systems including Hadoop and Spark. You will understand their limitations, design details, their relationship to databases, and their associated ecosystem of algorithms, extensions, and languages. write programs in Spark 6. Describe the landscape of specialized Big Data systems for graphs, arrays, and streams

The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp. Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization.

The Data Mining specialization is intended for data science professionals and domain experts who want to learn the fundamental concepts and core techniques for discovering patterns in large-scale data sets. This specialization consists of three courses: (1) Data Mining Pipeline, which introduces the key steps of data understanding, data preprocessing, data warehouse, data modeling and interpretation/evaluation; (2) Data Mining Methods, which covers core techniques for frequent pattern analysis, classification, clustering, and outlier detection; and (3) Data Mining Project, which offers guidance and hands-on experience of designing and implementing a real-world data mining project. Data Mining can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder. Specialization logo image courtesy of Diego Gonzaga, available here on Unsplash: https://unsplash.com/photos/QG93DR4I0NE

This program is designed to provide the learner with a solid foundation in probability theory to prepare for the broader study of statistics. It will also introduce the learner to the fundamentals of statistics and statistical theory and will equip the learner with the skills required to perform fundamental statistical analysis of a data set in the R programming language. This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder. Logo adapted from photo by Christopher Burns on Unsplash.

Data analysis skills are widely sought by employers, both nationally and internationally. This specialization is ideal for anyone interested in data analysis for improving quality and processes in business and industry. The skills taught in this specialization have been used extensively to improve business performance, quality, and reliability. By completing this specialization, you will improve your ability to analyze data and interpret results as well as gain new skills, such as using RStudio and RMarkdown. Whether you are looking for a job in data analytics, operations, or just want to be able to do more with data, this specialization is a great way to get started in the field. Learners are encouraged to complete this specialization in the order the courses are presented. This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

The Exam Prep DP-100: Microsoft Certified Azure Data Scientist Associate course is designed for professionals aiming to apply data science and machine learning to Azure workloads. This course equips learners with the skills to design, implement, and optimize machine learning solutions using Azure Machine Learning, MLflow, and Azure AI services. Participants will gain hands-on experience in data ingestion, preparation, model training, deployment, and monitoring. The specialization is divided into four key courses: Azure ML: Designing & Preparing Machine Learning Solutions Azure ML: Explore & Configure the Machine Learning Workspace Azure ML: Deploying, Managing, and Experimenting with Models Azure AI & ML: Optimize Language Models for AI Applications These courses are further divided into Modules, Lessons, and Video Items. All the courses have a set of Practice and Graded assignments available that test the candidate's ability to understand the concepts and grasp the topics discussed in the courses. This course aims to achieve the Microsoft Certified: Azure Data Scientist Associate Certification. This certification validates your ability to: Design and implement a data science environment. Prepare and explore data for ML workflows. Train and evaluate models using MLflow & Azure AI services. Deploy and monitor ML models for scalable AI applications. By earning this certification, you have positioned yourself as a skilled Azure Data Scientist

In the capstone, students will engage on a real world project requiring them to apply skills from the entire data science pipeline: preparing, organizing, and transforming data, constructing a model, and evaluating results. Through a collaboration with Coursolve, each Capstone project is associated with partner stakeholders who have a vested interest in your results and are eager to deploy them in practice. These projects will not be straightforward and the outcome is not prescribed -- you will need to tolerate ambiguity and negative results! But we believe the experience will be rewarding and will better prepare you for data science projects in practice.

A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures. A few examples of questions that we are going to cover in this class are the following: 1. What is a good strategy of resizing a dynamic array? 2. How priority queues are implemented in C++, Java, and Python? 3. How to implement a hash table so that the amortized running time of all operations is O(1) on average? 4. What are good strategies to keep a binary tree balanced? You will also learn how services like Dropbox manage to upload some large files instantly and to save a lot of storage space!

Computer science legend Donald Knuth once said “I don’t understand things unless I try to program them.” We also believe that the best way to learn an algorithm is to program it. However, many excellent books and online courses on algorithms, that excel in introducing algorithmic ideas, have not yet succeeded in teaching you how to implement algorithms, the crucial computer science skill that you have to master at your next job interview. We tried to fill this gap by forming a diverse team of instructors that includes world-leading experts in theoretical and applied algorithms at UCSD (Daniel Kane, Alexander Kulikov, and Pavel Pevzner) and a former software engineer at Google (Neil Rhodes). This unique combination of skills makes this Specialization different from other excellent MOOCs on algorithms that are all developed by theoretical computer scientists. While these MOOCs focus on theory, our Specialization is a mix of algorithmic theory/practice/applications with software engineering. You will learn algorithms by implementing nearly 100 coding problems in a programming language of your choice. To the best of knowledge, no other online course in Algorithms comes close to offering you a wealth of programming challenges (and puzzles!) that you may face at your next job interview. We invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs.

One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses. By the end, you will know how to structure your data analysis projects to ensure the fruits of your hard labor yield results for your stakeholders. You will also know how to streamline your analyses and highlight their implications efficiently using visualizations in Tableau, the most popular visualization program in the business world. Using other Tableau features, you will be able to make effective visualizations that harness the human brain’s innate perceptual and cognitive tendencies to convey conclusions directly and clearly. Finally, you will be practiced in designing and persuasively presenting business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles.

In this final course of the PostgreSQL for Everybody specialization, you’ll explore how modern databases are built and scaled. You’ll begin by examining PostgreSQL’s architecture, including how it implements CRUD operations, indexing, transactions, and ACID (Atomicity, Consistency, Isolation, Durability) guarantees. Then you’ll shift to NoSQL systems using the Deno environment. You’ll learn how Deno implements a distributed Key-Value store and how it applies BASE (Basic Availability, Soft State, Eventual Consistency) principles. Through hands-on projects, you’ll deploy your own Deno KV service on Deno’s global infrastructure and build a Deno client to interact with it. By the end, you’ll understand the design tradeoffs between ACID and BASE databases and gain practical experience deploying and scaling both relational and NoSQL systems.

Whether you are a beginning programmer with an interest in Data Science, a data scientist working closely with content experts, or a software developer seeking to learn about the database layer of the stack this specialization is for you! We focus on the relational database which is the most widely used type of database. Relational databases have dominated the database software marketplace for nearly four decades and form a core, foundational part of software development. In this specialization you will learn about database design, database software fundamentals, and how to use the Structured Query Language (SQL) to work with databases. The specialization, will conclude with an overview of future trends in databases, including non-relational databases (NoSQL) and Big Data. Upon completion of this specialization you will be well prepared to design and create efficient and effective relational databases, fill them with data, and work with them using SQL.

By the end of the specialization, you will be able to: Apply creative thinking to a variety of workplace situations and challenges. Decide between various alternatives, determining which is most appropriate given your situation. Display problem-solving abilities in response to specific workplace situations and challenges.

This course covers deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project. The first phase of the course will include video lectures on different DL and health applications topics, self-guided labs and multiple homework assignments. In this phase, you will build up your knowledge and experience in developing practical deep learning models on healthcare data. The second phase of the course will be a large project that can lead to a technical report and functioning demo of the deep learning models for addressing some specific healthcare problems. We expect the best projects can potentially lead to scientific publications.

This specialization is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.

Este es el primer curso en una línea de especialización de Coursera que trata el desarrollo de aplicaciones Web. Este curso le dará los conocimienots básicos, la terminología y los conceptos fundamentales que son necesarios para construir aplicaciones web integradas modernas. Un desarrollador de aplicaciones web integradas está familiarizado con cada "capa" de las tecnologías de software que participan en una aplicación web, incluidas las tecnologías de modelado de datos y bases de datos, los componentes del entorno de servidor web y middleware, protocolos de red, la interfaz de usuario y diseño visual básicos, y los conceptos de interacción del usuario. En este curso vamos a aprender practicando. Vamos a empezar por el aprendizaje de los principales componentes de las arquitecturas de aplicaciones web, junto con los patrones de diseño fundamentales y filosofías que se utilizan para organizarlos. El alumno construirá y perfeccionará continuamente una aplicación web integrada totalmente funcional a medida que avanzamos a través de los módulos de este curso. En el camino el alumno levará a cabo prácticas ágiles de desarrollo de softwar, numerosas herramientas que los ingenieros de software deben sabe cómo utilizar, y un marco de desarrollo de aplicaciones web integradas modernas.

In this Specialization, you will master design thinking competencies in an engaging hands-on, project-based format. We will guide you through a detailed 14-Step process where you will tackle a human-centered problem that you want to solve. You will learn and practice all of the most important tools from the field of human-centered design to generate ideas and connect with your customers on a human level. You will then deepen your practice by taking an in-depth journey through six key phases of the design thinking process, from immersion to learning-in-action, and explore the shifts in mindsets and skillsets that accompany them.

In this MOOC, we will learn the basic cyber security concepts, how to identify vulnerabilities/threat in a network system. We will apply CIA basic security services in the triage of recent cyberattack incidents, such as OPM data breach. We will learn the risk management framework for analyzing the risks in a network system, and apply the basic security design principles to protect the data and secure computer systems. We will examine the trustworthiness of programs and data installed in our systems and show the proper way to verify their integrity and authenticity. We will apply principle of least privileges for controlling the shared access given to different groups of users and system processes. On Amazon Cloud instances, we will use GnuPG software to generate public/private key pair for signing/verifying documents and open source software, and for encrypting documents. We will learn how to publish software, the related signature and release key on web server and publish public key to PGP key server for others to retrieve. We will learn Public Key Infrastructure (PKI) and Linux utility to serve as a CA for an organization, learn how to sign certificate request for clients or servers in secure email and web applications.

The capstone course, Design and Build a Data Warehouse for Business Intelligence Implementation, features a real-world case study that integrates your learning across all courses in the specialization. In response to business requirements presented in a case study, you’ll design and build a small data warehouse, create data integration workflows to refresh the warehouse, write SQL statements to support analytical and summary query requirements, and use the MicroStrategy business intelligence platform to create dashboards and visualizations. In the first part of the capstone course, you’ll be introduced to a medium-sized firm, learning about their data warehouse and business intelligence requirements and existing data sources. You’ll first architect a warehouse schema and dimensional model for a small data warehouse. You’ll then create data integration workflows using Pentaho Data Integration to refresh your data warehouse. Next, you’ll write SQL statements for analytical query requirements and create materialized views to support summary data management. For data integration workflows and analytical queries, you can use either Oracle or PostgreSQL. Finally, you will use MicroStrategy OLAP capabilities to gain insights into your data warehouse. In the completed project, you’ll have built a small data warehouse containing a schema design, data integration workflows, analytical queries, materialized views, dashboards and visualizations that you’ll be proud to show to your current and prospective employers.

The course "Design & Construction of Hydropower Structures" provides an in-depth exploration of hydropower projects, covering systems, components, and essential design principles. It begins with the history of hydropower, Indian projects, and site selection criteria, followed by hydrological studies, geological and geotechnical analyses, and hydropower potential assessment. Learners will study the design and construction of diversion and storage headworks, water conductor systems, tunnels, caverns, and hydromechanical equipment. The course also covers energy dissipators, galleries, surge tanks, penstocks, pressure shafts, and cross-drainage works, emphasizing hydraulic and structural design fundamentals. Additionally, it explores economic diameter selection, seepage control, geotechnical surveys, and stability assessments to ensure efficient project execution. By the end, participants will develop comprehensive skills to analyze, design, and manage hydropower projects, integrating theoretical concepts with practical applications. Target Learners:  Undergraduate students of Civil Engineering  Post-Graduate Students of Integrated Water Resources Management  Post-Graduate Students of Structural Engineering  Faculties of Civil Engineering Domain  Working Professionals in the above domain & other aspiring learners Pre-requisites:  Fundamental knowledge on Fluid Mechanics, Applied Hydraulics, Water Resources Engineering  Exposure to Indian codal standards

Evidence-based effective science communication is increasingly necessary. In this specialization, learn how to engineer science communication activities using evidence from the learning sciences. We'll also discuss best practices for various science communication modalities.

Dans cette spécialisation, les développeurs d'applications apprennent à concevoir, développer et déployer des applications qui intègrent de manière transparente les services gérés de Google Cloud Platform (GCP). Grâce à une combinaison de présentations, de démonstrations et d'ateliers pratiques, les participants apprennent à utiliser les services GCP et les API de machine learning pré-formées pour créer des applications cloud natives sécurisées, évolutives et intelligentes. Les apprenants peuvent choisir de terminer les travaux pratiques dans leur langage préféré : Node.js, Java ou Python. Ce cours est destiné aux développeurs d'applications qui souhaitent créer des applications cloud natives ou reconcevoir des applications existantes qui s'exécuteront sur Google Cloud Platform.

The courses in this specialization can also be taken for academic credit as ECEA 5385-5387, part of CU Boulder’s Master of Science in Electrical Engineering degree. Enroll here. In this specialization, you will engage the vast array of technologies that can be used to build an industrial internet of things deployment. You'll encounter market sizes and opportunities, operating systems, networking concepts, many security topics, how to plan, staff and execute a project plan, sensors, file systems and how storage devices work, machine learning and big data analytics, an introduction to SystemC, techniques for debugging deeply embedded systems, promoting technical ideas within a company and learning from failures. In addition, students will learn several key business concepts important for engineers to understand, like CapEx (capital expenditure) for buying a piece of lab equipment and OpEx (operational expense) for rent, utilities and employee salaries.

This course offers seasoned and up-and-coming leaders a clear, concise overview of the challenges of organizational leadership and practical strategies for improving as leaders. The lessons are structured around essential leadership responsibilities, including defining leadership, understanding what it is not, and understanding how to construct a leadership framework utilizing the elements of the 4D Leadership Development Framework. In addition, articles, self-evaluation forms, discussion post activities, and practice questions encourage participants to apply leadership principles to their situations. With a strong foundation in leadership theory and the most recent research, the program is designed for immediate practical application.

This course will expose you to the transformation taking place, throughout the world, in the way that products are being designed and manufactured. The transformation is happening through digital manufacturing and design (DM&D) – a shift from paper-based processes to digital processes in the manufacturing industry. By the end of this course, you’ll understand what DMD is and how it is impacting careers, practices and processes in companies both large and small. You will gain an understanding of and appreciation for the role that technology is playing in this transition. The technology we use every day – whether it is communicating with friends and family, purchasing products or streaming entertainment – can benefit design and manufacturing, making companies and workers more competitive, agile and productive. Discover how this new approach to making products makes companies more responsive, and employees more involved and engaged, as new career paths in advanced manufacturing evolve. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the first course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA

Master strategic marketing concepts and tools to address brand communication in a digital world. This Specialization explores several aspects of the new digital marketing environment, including topics such as digital marketing analytics, search engine optimization, social media marketing, and 3D Printing. When you complete the Digital Marketing Specialization you will have a richer understanding of the foundations of the new digital marketing landscape and acquire a new set of stories, concepts, and tools to help you digitally create, distribute, promote and price products and services. In 2016, this was one of the top 10 specializations in terms of enrollments. INC Magazine rated the first course, Marketing in a Digital World, as one of The 10 Hottest Online Classes for Professionals in 2015. In addition, this course was also ranked in the top five courses across multiple MOOC providers. Finally, the Digital Marketing Certificate was the top coveted certificate on Coursera in 2015. Get more updates on the specialization at http://digitalmarketingprofs.com/ This Specialization is part of the University of Illinois Masters of Business Administration degree program, the iMBA. Learn more about the admission into the program here.

This four-week Capstone of the Digital Marketing Specialization is designed to help you apply the principles you have learned in the previous courses. This capstone course is designed to give you hands-on experience in executing a digital marketing campaign for a fictitious firm selling electronics. In the previous courses on analytics and channels, you came up with strategies to identify a firm’s objectives, specify a few key ones, research alternatives to reaching the customer in their decision journey and finally propose a multi-channel digital marketing plan. In this capstone, you will execute a campaign, rather than creating another "plan". You will use an online simulation to do this. You will be a marketing manager for a firm selling digital cameras online through their webstore. You will be reviewing the products, pricing, margins, and historical sales. You will create a targeted ad campaign after researching appropriate keywords for the products you are selling. You will also review the basics of landing page design and search engine optimization. You will then create and execute an email campaign. Once these campaigns are executed, you get feedback on the KPI's such as revenue, profits, traffic, conversions. You will get an opportunity to redo this campaign, with new strategies, to improve your KPI's in the second round. This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu.

This Specialization is intended for both current and new product managers working in digital who want to apply a portfolio of modern practices to developing their products and teams. Through five courses, you will cover applications of product design, hypothesis-driven development and agile, all at the heart of modern product management.

Digital transformation is a hot topic--but what exactly is it and what does it mean for companies? In this course, developed at the Darden School of Business at the University of Virginia, and led by top-ranked Darden faculty and Boston Consulting Group global management experts, we talk about digital transformation in two ways. First we discuss the pace of change and the imperative it creates for businesses. Next we provide the context for this transformation and what it takes to win in the digital age. Then we walk through BCG's proprietary framework, which helps you identify key areas to digitize, including strategy, core processes, and technology. By the end of this course, you'll be able to: --describe the underlying economics of innovation, technology, and market disruptions --weigh the pros and cons of current digital technologies driving advancement --utilize BCG's digital transformation framework as a "how-to" for digitizing your organization

In this capstone project course, we ask YOU to apply everything you have learned in this specialization to analyze a real world company and to develop a digital transformation strategy for this company. You will have the possibility to choose between four different case companies, that varies in size (from small start-up to large financial service providers), industry (banking, financial trading, insurance) and geographical location. For one of these -- only one -- you will create a concise recommendation of a strategy to leverage the digital transformation of financial services. To do this well, you will need to summon ideas appropriately from the earlier three courses in the specialization.

Die digitale Transformation ist ein brandaktuelles Thema – aber was genau ist das und was bedeutet es für Unternehmen? In diesem Kurs, der an der Darden School of Business an der University of Virginia entwickelt wurde und von renommierten globalen Management-Experten der Darden-Fakultät und der Boston Consulting Group geleitet wird, sprechen wir in zweierlei Hinsicht über digitale Transformation. Zunächst befassen wir uns mit der Geschwindigkeit des Wandels und den daraus resultierenden Anforderungen für die Unternehmen. Als nächstes zeigen wir die Rahmenbedingungen für diesen Wandel auf und erläutern, was es braucht, um im digitalen Zeitalter erfolgreich zu sein. Im Anschluss daran sehen wir uns das firmeneigene Framework von BCG an, das Ihnen hilft, Schlüsselbereiche für die Digitalisierung zu identifizieren, einschließlich Strategie, Kernprozesse und Technologie. Am Ende dieses Kurses werden Sie Folgendes beherrschen: – Beschreibung der zugrundeliegenden ökonomischen Bedeutung von Innovation, Technologie und Marktumwälzungen – Abwägen der Vor- und Nachteile der derzeitigen digitalen Technologien, die den Fortschritt vorantreiben – Nutzung des digitalen Transformations-Framework von BCG als „How-to“ für die Digitalisierung Ihres Unternehmens

View the Specialization trailer: https://youtu.be/nbbgAkJUbRo Digitalisation is changing our society and the working world, creating new processes and radically altering existing workflows. Aerospace is being impacted like every other scientific field and innovation without digitalisation is no longer conceivable. The three-part MOOC series “Digitalisation in Aeronautics and Space” is thus devoted to examining the transformations that have already occurred and forthcoming likely changes, posing the question: what will aerospace science be like in future and what will the influence of digitalisation be on research? An array of research fields are focused on in relation to this question, including artificial intelligence in earth observation, robots in production and digital avionics networks, among others.

Dino 101: Dinosaur Paleobiology is a 12-lesson course teaching a comprehensive overview of non-avian dinosaurs. Topics covered: anatomy, eating, locomotion, growth, environmental and behavioral adaptations, origins and extinction. Lessons are delivered from museums, fossil-preparation labs and dig sites. Estimated workload: 3-5 hrs/week.

Diversity is a fact. It is also paradoxical. We need to be capable of seeing and hearing differences in order to reap the benefits of diversity. But seeing and hearing differences hone our discriminating reflexes and can also lead to discrimination. If you take this MOOC, you will: 1. understand this paradox, 2. understand its dynamics, and 3. identify ways to manage it, so that you can better channel the diversity potential in the workplace for greater performance and innovation.

La diversité est une réalité indéniable dans le monde d'aujourd'hui. Les mouvements de femmes, le militantisme pour les droits civiques, Black Lives Matter, la mondialisation et bien d'autres encore ont tous contribué à attirer l'attention sur l'importance de la diversité et de l'inclusion. Les questions de diversité occupent systématiquement les deux faces d'une même pièce. D'une part, les mouvements sociaux ont historiquement mis en lumière les inégalités subies par les femmes et les groupes minoritaires. D'autre part, la diversité apporte des perspectives différentes et potentiellement nouvelles, qui peuvent être source d'innovation et de changement. Sur le plan cognitif, la relation entre la diversité et l'inclusion est paradoxale. Des études ont montré que nous devons être capables de voir et d'entendre les différences afin de profiter des avantages de la diversité. Cependant, le fait de voir et d'entendre les différences aiguise nos réflexes de discrimination et peut aboutir à la discrimination. Il s'agit d'un cours d'introduction à la diversité et à l'inclusion qui fournit des informations sur les raisons pour lesquelles il s'agit d'une question importante pour les organisations, sur les façons dont nous pouvons comprendre conceptuellement la diversité et l'inclusion, et sur certaines initiatives et meilleures pratiques pour aborder la diversité et l'inclusion sur le lieu de travail. Ce cours propose une approche cognitive et vous permettra de : - comprendre pourquoi la diversité et l'inclusion constituent un défi important pour les organisations, - comprendre les processus cognitifs qui sous-tendent nos réactions à la différence, - comprendre la relation paradoxale entre la diversité et l'inclusion, - gérer la diversité et l'inclusion afin de mieux canaliser le potentiel de diversité et encourager l'inclusion pour plus de performance et d'innovation.

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts).

In the Effective Communication Capstone learners apply the lessons of Business Writing, Graphic Design, and Successful Presentation to create a portfolio of work that represents their mastery of writing, design, and speaking and that expresses their personal brand. The portfolio includes three individual elements—a written memo, a slide deck, and a presentation—integrated around a single topic. We provide the elements for a basic capstone, but we also invite our learners to create their own project if they so choose. This self-designed "Challenge Capstone" allows learners to engage meaningfully in their world by choosing a project relevant to their current job or by volunteering to write, design, and speak for a social organization of their choice. By successfully undertaking the Capstone, learners will accomplish three main goals: 1. They will hone their writing, design, and speaking skills and build a portfolio for a job search and/or professional application; 2. They will shape these skills into a unique brand identity; and, if they choose, 3. They will undertake a transformative effect in the world around them. Ultimately, the importance of Capstone portfolio is greater than the sum of its individual parts. Its true goal lies in each student’s personal transformation and expression of their best selves. We invite you to unleash your skills and we can't wait to see the results! This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Scala is an expressive, versatile, and safe programming language. In this course, you will learn how to get the most out of Scala to solve common programming tasks such as modeling business domains, breaking down complex problems into simpler problems, manipulating data, or running parallel tasks. Along the journey, you will also learn the best practices for writing high-quality code that scales to large applications, how to handle errors, how to write tests, and how to leverage a productive development environment. This comprehensive, hands-on, course aims at leveling up your programming skills by embracing both functional programming and object-oriented programming. You will become familiar with the standard library and the common patterns of code used in the real world. Each week contains about 1h30 of video lectures. Each lecture is a ~10 min video focused on a specific skill or concept. We always start by looking at concrete problems, and then explain how language features or libraries make you more productive to solve these problems in general. Lectures are generally followed by a quiz to assess your progress. At the end of each week, a graded assignment inspired by real-world applications will give you an opportunity to put things in practice. The course covers Scala 3, and it mentions the differences with Scala 2.

This course familiarizes you with standards and policies of the electric utility industry, and provides you with basic vocabulary used in the business. It introduces the electric power system, from generation of the electricity all the way to the wall plug. You will learn about the segments of the system, and common components like power cables and transformers. This course is for individuals considering a career in the energy field (who have a high school diploma, at minimum, and basic knowledge of mathematics), and existing energy sector employees with less than three years of experience who have not completed similar training and would benefit from a course of foundational industry concepts. The course is a combination of online lectures, videos, readings and discussions. This is the first course in the Energy Production, Distribution & Safety specialization that explores various facets of the power sector, and features a culminating project involving creation of a roadmap to achieve a self-established, energy-related professional goal. To learn more about the specialization, check out a video overview at https://www.youtube.com/watch?v=2Yh9qIYiUDk.

The objective of this specialization is to provide an understanding of interface design approaches and architectures for creating solid user experiences in embedded system prototypes and products. For both machine and user interfaces, we will look at the best practices for the interface design process, including considerations of the nature and content of interaction, whether between devices, between a device and a user, or in more complex systems.

The courses in this specialization can also be taken for academic credit as ECEA 5340-5343, part of CU Boulder’s Master of Science in Electrical Engineering degree. Enroll here. Embedding Sensors and Motors will introduce you to the design of sensors and motors, and to methods that integrate them into embedded systems used in consumer and industrial products. You will gain hands-on experience with the technologies by building systems that take sensor or motor inputs, and then filter and evaluate the resulting data. You will learn about hardware components and firmware algorithms needed to configure and run sensors and motors in embedded solutions.

Risk Management and Innovation develops your ability to conduct empathy-driven and data-driven analysis in the domain of risk management. This course focuses on the process of managing enterprise risk, in which understanding both data and stakeholder enriches each step. The course introduces the three lines of defense, tools to identify and assess risks, risk responses, key risk indicators, and risk reporting. You will use tools like risk statements, bowtie analysis, matrices, and heat maps to apply these concepts, and use data visualization in Tableau to practice applying data analysis to better manage risks.

In this third course in the Social Marketing Specialization - "The Engagement & Nurture Marketing Strategies" - you will learn two of the most effective social strategies used by organizations today. You'll see real-world best practice examples and learn what metrics they use to gauge success. You will also learn the importance of infographics and the impact a well-designed landing page can have on your bottom line. All of the social skills you have learned thus far will be put into action with a multimedia filter and focus blog that you will create to demonstrate how social can enable real-time marketing results. After this MOOC, you will have developed a plan to reach your target consumer markets and know when it is best to either use or avoid specific social marketing strategies. Additional MOOC 3 faculty include: * Randy Krum (Data Visualization & Infographics Designer | Consultant | Author | Speaker | President, InfoNewt) * Stanford Smith (CEO, Pushing Social) * Andy Crestodina (Co-Founder & Strategic Director, Orbit Media Studios) * Ellen Valentine (Veteran Marketing Leader & Evangelist, Silverpop, IBM)

Engineering Maintainable Android Apps, which is a 4 week MOOC that shows by example various methods for engineering maintainable Android apps, including test-driven development methods and how to develop/run unit tests using JUnit and Robotium (or equivalent automated testing frameworks for Android), as well as how to successfully apply common Java/Android software patterns to improve the extensibility and clarity of Android apps. Students will work on the appropriate automated unit quizzes, based on the material covered in the lecture videos. These lessons will demonstrate the benefits of good software engineering practices that are targeted at creating maintainable code for mobile apps. There will be roughly 3-4 hours of student engagement time per week, including video lectures, and quizzes. The ordering of the modules within the course is designed to be flexible. In particular, students can watch the videos in whatever order suits their experience and needs, e.g., they may want to watch the unit testing videos prior to the software pattern videos if they prefer to learn about unit testing first.