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• Business

  Beginner

  Getting Started with Pinterest

  In this project, you will be able to set up an account on Pinterest, edit and customize your profile, identify Pinterest settings and some related options. Throughout this project, you will be able to search for pictures on a certain topic on different sites, add them to your thematic collections, edit your boards and customize them on Pinterest, as well as being able to subscribe to other users. You will also be able to react to pins and write comments. This project is for beginners in creative industries (such as marketers, photographers and designers). Along the way, you will be able to apply pinterest tools and features as well as create boards and pins to use to display your talents and portfolio of work resulting in advancements in your career through more exposure and discovery. Pinterest can help in your career as a resource to change careers, research organizations/ companies or discover freelance work. Besides supporting and assisting your career, your new skills will come in handy for inspiration and creative ideas in any topic of interest.

  90 min

  View details: Getting Started with Pinterest
• Technology

  All levels

  Uso de bases de datos con Python

  Este curso presentará a los estudiantes los conceptos básicos del lenguaje de consulta estructurado (Structured Query Language, SQL), así como el diseño básico de bases de datos para almacenar datos como parte de una iniciativa de varios pasos para recopilar, analizar y procesar datos. El curso utilizará SQLite3 como base de datos. También crearemos rastreadores web y procesos de visualización y recopilación de datos de varios pasos. Utilizaremos la biblioteca D3.js para realizar la visualización básica de datos. Este curso abarcará los capítulos de 14 y 15 del libro “Python para todos”. Para que le vaya bien en este curso, debe estar familiarizado con el material cubierto en los capítulos 1 a 13 del libro de texto y los primeros tres cursos de esta especialización. Este curso abarca Python 3.

  View details: Uso de bases de datos con Python
• Technology

  Advanced

  Transformer Models and BERT Model - 繁體中文

  這堂課程將說明變換器架構，以及基於變換器的雙向編碼器表示技術 (BERT) 模型，同時帶您瞭解變換器架構的主要組成 (如自我注意力機制) 和如何用架構建立 BERT 模型。此外，也會介紹 BERT 適用的各種任務，像是文字分類、問題回答和自然語言推論。課程預計約 45 分鐘。

  420 min

  View details: Transformer Models and BERT Model - 繁體中文
• Technology

  Intermediate

  Object-Oriented Analysis and Design: Patterns and Principles

  An applied analysis and design class that addresses the use of object-oriented techniques. Topics include domain modeling, use cases, architectural design and modeling notations. Students apply techniques in analysis and design projects. Focus is on key object-oriented design patterns and principles. This course can be taken for academic credit as part of CU Boulder’s Masters of Science in Computer Science (MS-CS) degrees offered on the Coursera platform. This fully accredited graduate degree offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

  1500 min

  View details: Object-Oriented Analysis and Design: Patterns and Principles
• Business

  Beginner

  Templates in Adobe Express

  Learn how to design with confidence and speed using Adobe Express. This course shows you how to transform your ideas into professional-quality visuals by starting with ready-made templates. You’ll discover how to quickly create, customize, resize, and adapt designs for multiple platforms, ensuring your content always looks polished and on-brand. Along the way, you’ll explore how color, typography, and layout work together to elevate your visuals, helping you design with both efficiency and creative flair. By the end of the course, you’ll be able to create cohesive, eye-catching designs that communicate your message clearly and consistently across any format.

  180 min

  View details: Templates in Adobe Express
• Business

  Intermediate

  Lancer une campagne publicitaire sur Pinterest

  Dans ce projet guidé, nous avons découvert Pinterest et son importance pour lancer une campagne publicitaire en plusieurs étapes, d'abord créer un compte professionel puis choisir une cible pour notre publicité,ensuite nous avons déterminé notre audience, encore nous avons détfinniser l'obejctif et l'emplacement et enfin le budget et calendrier de notre nouveau annonce. À la fin de ce projet, vous aurez appris à comment lancer une campagne publicitaire sur Pinterest.

  View details: Lancer une campagne publicitaire sur Pinterest
• Technology

  Intermediate

  Control Page Access

  In today's collaborative work environment, unauthorized access to sensitive pages can expose confidential information, create costly data breaches averaging $4.88 million in damages, and disrupt team workflows. This intermediate-to-advanced course equips IT managers and team leaders with essential skills to protect shared pages while maintaining productive collaboration. You'll learn to identify when page-level restrictions are necessary—whether protecting confidential information or managing work-in-progress content—and discover how targeted access controls address real-world security challenges without over-restricting your teams. Through interactive lessons and hands-on practice, you'll confidently assign editor and viewer roles, verify that restrictions are properly applied, and implement access policies that scale with your organization's growth. By the end of this course, you'll be able to make informed decisions about page access and apply controls that strengthen security, clarify accountability, and enable your teams to work together securely and efficiently.

  View details: Control Page Access
• Business

  Advanced

  Advanced Tableau - LOD Calculations

  This Advanced Tableau course provides next-level training to be able to prep and display data in an efficient way. In this course, you’ll utilize Tableau to break down and solve the types of business problems that BI analysts and financial analysts typically face. This course will open the hood of Tableau’s SQL processing to give you a deeper understanding of how these calculations work. You’ll also be applying what you learn to 7 different business scenarios, which we hope you’ll publish into a Tableau Public profile to show off your work. By the end, you’ll have a deeper understanding of Tableau and the confidence to tackle a huge variety of problems. Upon completing this course, you will be able to: • Define level of detail and other critical concepts • Identify the grain and level of detail of a data set • Troubleshoot common errors • Apply fixed, include, and exclude LOD calculations to business scenarios • Identify how different LODs are affected by context and dimension filters • Compare LOD calculations to table calculations This Tableau course is perfect for professionals who have a solid understanding of data analysis and want to expand their skill set to include Tableau’s world-leading visualizations. This course is designed to equip anyone who desires to begin a career in business analysis—or other roles that require displaying and analyzing data sets—with the advanced skills to create dynamic data-viewing experiences.

  View details: Advanced Tableau - LOD Calculations
• Technology

  Intermediate

  Machine Learning with Python

  Python is a core skill in machine learning, and this course equips you with the tools to apply it effectively. You’ll learn key ML concepts, build models with scikit-learn, and gain hands-on experience using Jupyter Notebooks. Start with regression techniques like linear, multiple linear, polynomial, and logistic regression. Then move into supervised models such as decision trees, K-Nearest Neighbors, and support vector machines. You’ll also explore unsupervised learning, including clustering methods and dimensionality reduction with PCA, t-SNE, and UMAP. Through real-world labs, you’ll practice model evaluation, cross-validation, regularization, and pipeline optimization. A final project on rainfall prediction and a course-wide exam will help you apply and reinforce your skills. Enroll now to start building machine learning models with confidence using Python.

  1620 min

  View details: Machine Learning with Python
• Technology

  Beginner

  Python for Data Analytics

  This comprehensive course guides students through the complete data analytics workflow using Python, combining programming fundamentals with advanced statistical analysis. The curriculum is structured across five interconnected modules that build upon each other, using real-world datasets to provide practical, hands-on experience. Starting with programming fundamentals, you'll learn essential Python concepts while working with real datasets like public library revenue and restaurant safety inspections. The course introduces the Jupyter Notebook environment and transitions students from spreadsheet-based analysis to powerful programmatic approaches. Students master core programming concepts including variables, functions, and control flow structures. This course helps you bridge the gap between theoretical knowledge and practical application, enabling you to become proficient in using Python for comprehensive data analysis, from basic data manipulation to advanced statistical modeling and forecasting.

  View details: Python for Data Analytics
• Technology

  Beginner

  Foundational Mathematics for AI

  This course offers a comprehensive introduction to the mathematical principles that form the foundation of artificial intelligence and machine learning. Designed for learners with a variety of academic backgrounds, the course bridges essential mathematical concepts with real-world AI applications, empowering students to understand and implement mathematical techniques critical for AI development. By the end of this course, learners will be able to apply functions, matrices, and vectors to represent and analyze data relationships. Students will be able to use descriptive statistics and visualization techniques to explore and summarize datasets, solve systems of linear equations and model complex relationships using linear regression of single and multiple variables, and understand and implement foundational principles of probability, including Bayes' Theorem. The course builds to advanced mathematical techniques in Calculus, and develops derivatives and integrals to analyze rates of change and distributions, essential for optimization and modeling in AI. Concepts from Linear Algebra are used to explore advanced concepts like eigenvectors, determinants, and linear transformations for dimensionality reduction and classification algorithms. This course is specifically tailored for aspiring AI practitioners. Unlike traditional math courses, this curriculum focuses on mathematical techniques directly applicable to artificial intelligence and machine learning, bridging theory with practice. Through interactive modules, real-world datasets, and tools like Python and Excel, you’ll not only understand the concepts but also apply them to solve practical problems. With clearly defined modules such as Descriptive Statistics, Linear Algebra, Probability, and Optimization, this course allows you to build knowledge progressively while connecting each concept to AI use cases. Each topic is introduced with AI-related examples, like using linear regression to model salaries or applying optimization techniques in clustering algorithms, with then a focus on applications of the theory. This course equips you with the mathematical fluency necessary for more advanced AI courses and research, such as deep learning or natural language processing. Whether you’re an engineer, data scientist, or simply interested in breaking into AI, this course provides the mathematical foundation you need to understand and contribute to the rapidly evolving field of artificial intelligence.

  View details: Foundational Mathematics for AI
• Technology

  Intermediate

  TensorFlow 2 시작하기

  TensorFlow 2 시작하기 과정에 오신 것을 환영합니다! 이 과정에서는 순차 API를 사용한 모델 구축, 훈련, 평가 및 예측, 모델 검증, 정규화, 콜백 구현, 모델 저장 및 로딩 등 Tensorflow를 사용하여 딥 러닝 모델을 개발하기 위한 완벽한 엔드-투-엔드 워크플로우를 배우게 됩니다. 배운 개념을 실용적인 실습형 코딩 자습서에서 바로 연습할 것이며 이는 대학원 조교에게 안내를 받게 될 것입니다. 또한 기술을 통합할 수 있는 일련의 자동 채점 프로그래밍 과제가 있습니다.\n\n과정이 끝나면 이미지 분류기 딥 러닝 모델을 처음부터 개발하는 Capstone 프로젝트에 많은 개념을 통합할 것입니다. Tensorflow는 오픈 소스 머신 라이브러리이며 딥 러닝에 가장 널리 사용되는 프레임워크 중 하나입니다. Tensorflow 2의 출시는 초심자에서 고급 수준에 이르기까지 모든 사용자의 사용 편의성에 중점을 둔 제품 개발의 단계적 변화를 나타냅니다. 이 과정은 Tensorflow 1.x에 대한 경험이 있는 사용자뿐만 아니라 경험이 없는 사용자 모두를 대상으로 합니다. 이 과정에서 성공하기 위해서는 파이썬 프로그래밍 언어(이 과정에서는 파이썬 3 사용), 일반적인 머신 러닝 개념(예: 과적합/과소적합, 지도 학습 작업, 검증, 정규화 및 모델 선택), 전형적인 모델 아키텍처(MLP/피드포워드 및 컨볼루션 신경망), 활성화 함수, 출력 레이어 및 최적화를 포함한 딥 러닝 분야의 실무 지식을 갖추고 있어야 합니다.

  View details: TensorFlow 2 시작하기