In this course you will learn and practice several techniques for user interface evaluation. First we start with techniques that can be applied alone or in a design team, including action analysis, walkthroughs, and heuristic evaluation. Then we move on to user testing, including learning from a series of usability tests carried out in a real usability lab, and techniques to carry out your own tests even without a lab. Finally, we wrap up the discussion of evaluation--and of UI Design in the specialization as a whole--by looking at the question of how to set and measure usability goals, and in turn, when a design is usable enough to release it.
Conheça o BigQuery ML para inferência, saiba por que ele é a melhor opção para analistas de dados, os casos de uso dele e os modelos de ML compatíveis. Você também vai aprender a criar e gerenciar esses modelos de ML no BigQuery.
في هذا المشروع التفاعلي، ستقوم بانشاء حساب ايرتيبل وتخلق جداول مكونة من أنواع حقول مختلفة وتنشئ علاقات لربط الجداول ببعضها، وتتابع التحديثات في قاعدة بياناتك، وتخصص مظهرها باستخدام التصفية والتجميع والتلوين وأدوات أخرى، كما ستضاعف امكانيات قاعدة بياناتك باستخدام التطبيقات والوظائف التلقائية، وتخلق مشاهد مختلفة لقاعدة بياناتك لمشاركتها مع مستخدمين اخرين!
From Control to Emergent Intelligence focuses on helping learners understand how generative AI behavior is shaped, guided, and extended, moving from surface-level interaction to a systems-level perspective. The course begins with how humans control models at inference time through prompting strategies and sampling parameters, then steps back to examine how models are shaped during training through reinforcement learning, fine-tuning, and feedback. Learners develop a clear mental distinction between intelligence that is baked into a model during training and intelligence that emerges at inference time through structure, reasoning, tools, and memory. This framing allows learners to see modern generative AI not as a static tool, but as a dynamic system whose behavior depends on both how it was trained and how it is used.
As the course progresses, learners move beyond single prompts to structured reasoning, model comparison, and evaluation across different architectures and ecosystems, including open-source and mixture-of-experts models. They then explore how tools, memory, and context persistence allow AI systems to operate across time, enabling action-oriented workflows rather than isolated responses. The course concludes with real-world applications across domains such as coding, business, accessibility, and creative work, paired with individual-level ethical reflection on what it means to work alongside AI systems. By the end of Course 2, learners understand not only how to use generative AI effectively today, but how the combination of control, feedback, reasoning, evaluation, and external capabilities gives rise to more autonomous behavior, setting the foundation for agents and more advanced systems explored in Course 3.
It describes the elements of the Leadership model oriented towards human flourishing, in order to develop leaders who achieve better results.
We are facing a world leadership crisis, due to (among other factors) the volatile, uncertain, complex, and ambiguous context we are living in.
The world needs self-aware leaders who are also aware of their environment, immersed in a permanent learning process, who are committed, resilient, with a positive vision of the present and the future, who find meaning in their life mission, and who flourish by contributing to the flourishing of others.
This course will bring the necessary tools to develop a human-flourishing-oriented-leadership.
Microsoft 365: Cloud Basics, Pricing, Licensing & Support
Welcome to Microsoft 365: Cloud Basics, Pricing, Licensing & Support, a foundational and practical course designed for beginners, IT professionals, administrators, and business users who want to build a strong understanding of Microsoft 365 and modern cloud-based productivity solutions.
The Microsoft 365 – Cloud Basics, Pricing, Licensing & Support course is designed for beginners, IT professionals, administrators, and business users who want to build a foundational understanding of Microsoft 365 and cloud computing concepts.
This course introduces learners to essential cloud principles, service models, and deployment strategies, followed by a deep dive into Microsoft 365 offerings, subscription models, pricing, licensing, and support services.
You will explore how Microsoft 365 enables modern workplace productivity, collaboration, and hybrid work environments. The course also covers administrative tasks such as managing licenses, configuring organizational settings, handling billing, and creating support requests using the Microsoft 365 Admin Center.
Through a combination of conceptual explanations, demos, and real-world scenarios, this course provides a practical understanding of how organizations adopt and manage Microsoft 365 services.
The course delivers approximately 6–8 hours of structured video content, organized into two modules. Each module includes quizzes and knowledge checks to reinforce learning and validate understanding.
Enroll in this course to gain a strong foundation in Microsoft 365 and confidently begin your journey into modern workplace administration and cloud services.
Course Modules
Module 1: Cloud Fundamentals & Microsoft 365 Basics
Module 2: Microsoft 365 Pricing, Licensing & Support Management
By the End of This Course, You Will Be Able To:
- Understand fundamental cloud computing concepts and service models
- Differentiate between Microsoft 365 and Office 365 offerings
- Identify Microsoft 365 subscription plans and organizational setup processes
- Manage Microsoft 365 pricing, billing, and licensing models
- Configure and manage licenses for users and services
- Use Microsoft 365 Admin Center for administration tasks
- Create and manage support requests and understand SLAs
- Monitor service health and ensure service reliability
Sales Prospecting Mastery with Lemlist: AI-Driven Strategies
In this intermediate-level guided project, you will master the art of AI-driven prospecting using Lemlist. We will do this by setting up and leveraging Lemlist for automated email and LinkedIn outreach, to create a sales pipeline and enhance your prospecting efficiency. You will learn how to integrate Lemlist’s AI capabilities to personalise and optimise your campaigns. Additionally, you’ll explore best practices for creating and managing automated sales funnels in Hubspot, ensuring a seamless transition from lead generation to customer conversion. By the end of this project, you will have the skills to drive more effective and automated prospecting campaigns. Learners will need a sound understanding of the principles of Sales Prospecting. Some prior experience of AI and HubSpot would be advantageous. Learners will also need to set up accounts in Claude AI, Lemlist, HubSpot and LinkedIn.
Learn how to build a loyal Instagram community through authentic engagement and thoughtful interaction strategies. This course explores the difference between proactive and reactive engagement, offering techniques for managing comments, DMs, and follower interactions effectively. You'll also develop a hashtag strategy to boost content discoverability through Instagram’s search and explore features. With expert guidance and a practical engagement planning activity, you’ll be equipped to foster meaningful connections that support long-term growth.
Implementing and Integrating 5G O-RAN Systems (Advanced)
Implementing and Integrating 5G O-RAN Systems (Advanced) is an advanced, hands-on course designed for experienced network engineers and systems developers ready to master real-world 5G Open RAN deployment. In today’s fast-evolving telecom landscape, O-RAN skills are essential for building agile, multi-vendor networks that drive innovation and performance. This course dives deep into fronthaul protocols (eCPRI, RoE), xApp/rApp integration with the near-RT RIC, and the orchestration challenges of cloud-native, vendor-diverse 5G environments. You’ll analyze landmark case studies (Rakuten, DISH, Vodafone, NTT Docomo), practice integrating and benchmarking O-RAN systems in virtual labs, and develop troubleshooting habits for live deployments. Through immersive videos, scenario-based readings, and hands-on activities, you'll learn to validate performance, manage interoperability, and drive automation at scale. Whether advancing your current role or preparing for future 5G leadership, you’ll build confidence and capability to deliver high-performance O-RAN solutions in the real world.
Excel Formulas for Peak Performance is the advanced course for professionals who need to build models that are not only accurate but exceptionally fast. When datasets scale, standard formulas fail. This course teaches you to master workbook optimization.
You will learn to systematically audit complex spreadsheets, using formula-auditing tools to pinpoint performance bottlenecks caused by volatile functions like OFFSET and inefficient arrays. Then, you’ll master powerful alternatives. You'll leverage SUMPRODUCT for complex multi-conditional calculations and use modern dynamic arrays like FILTER to replace slow helper columns and lookups.
Through hands-on labs, you'll refactor an inherited pricing model and consolidate a large sales dataset, achieving a measurable drop in recalculation time. By the end, you'll transform fragile, lagging workbooks into robust, lightning-fast models ready for demanding professional use. Elevate your Excel skills from proficient to expert.
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you learn the fundamentals of configuring vector search in Spanner.
Deep Learning with TensorFlow: Build Neural Networks
By the end of this course, learners will be able to explain the fundamentals of neural networks, apply TensorFlow to build and train models, implement convolutional neural networks for image processing, and adapt transfer learning strategies for real-world applications.
This course is designed to help learners bridge the gap between theory and practice in deep learning. Starting with perceptrons and core neural network principles, participants will gain hands-on experience in building models, initializing parameters effectively, and processing image data through CNNs. Moving forward, they will learn to classify real-world datasets like dogs vs. cats and master advanced transfer learning techniques to optimize pre-trained models for specialized tasks.
Unlike other tutorials, this course uniquely combines step-by-step TensorFlow implementation with conceptual clarity, ensuring learners not only follow code but also understand the reasoning behind each decision. Whether aiming to enhance AI career prospects or apply deep learning in projects, learners will leave equipped with the skills to design, train, and deploy robust neural network models confidently.
