Aspire Journeys
The Generative AI Cloud Odyssey: Exploring AWS, Azure, and GCP
- 25 Courses | 32h 1m 28s
Generative AI Cloud Odyssey is an immersive journey into the dynamic world of cloud-based Generative AI, designed to inspire and empower participants to unleash their creativity and innovation. This transformative journey traverses the vast landscape of cloud computing, exploring the cutting-edge technologies and platforms such as AWS, Azure and GCP that drive the future of AI. As participants embark on this adventure, they will unravel the concepts of Generative AI, gaining insights into its foundational principles and practical applications. Guided by expert instructors and equipped with state-of-the-art tools and resources, participants will embark on a voyage of discovery, honing their skills and capabilities in building intelligent and creative solutions. With hands-on projects, interactive learning experiences, and real-world case studies, Generative AI Cloud Odyssey offers a comprehensive and immersive learning journey that empowers participants to harness the power of Generative AI on all three major cloud platforms Azure, AWS, and GCP.
Track 1: Demystifying Generative AI
This track serves as a gateway to understanding the fundamental concepts and principles behind Generative AI, empowering the learners to unleash their creativity and innovation. From mastering the foundations of Generative AI modeling to exploring the depths of large language models, each course in this track offers invaluable insights and practical knowledge to kickstart the journey. Whether for a novice or an experienced practitioner, these courses provide a comprehensive and immersive learning experience that will equip them with the skills and expertise to leverage Generative AI for business and beyond.
- 6 Courses | 9h 39m 29s
Track 2: Exploring Generative AI on AWS: Building Intelligent and Creative Solutions
This track offers a curated selection of courses designed to guide the learners through the process of harnessing the power of Generative AI on the AWS platform. From getting started with Generative AI to building advanced models with Amazon SageMaker and Amazon CodeWhisperer, each course equips the learners with the knowledge and skills to develop innovative AI applications. Whether the learners are interested in code generation, music generation, or intelligent chatbots, this track provides practical, hands-on training to help them leverage the full potential of Generative AI on AWS.
- 8 Courses | 8h 56m 7s
Track 3: Generative AI on Azure: Building Intelligent and Creative Solutions
This track offers a series of courses tailored to help the learners to explore and harness the capabilities of Generative AI within the Azure ecosystem. From understanding the fundamentals of Generative AI on Azure to deep-diving into advanced techniques with Azure's Open AI service, each course empowers them to build intelligent and creative solutions. Whether the learners are interested in developing AI-powered chatbots or exploring the depths of Generative AI with Azure Bot Service, this track provides comprehensive training to elevate their skills and drive innovation in the cloud.
- 5 Courses | 5h 41m 57s
Track 4: Generative AI on GCP: Building Intelligent and Creative Solutions
This track presents a curated selection of courses designed to immerse the learners in the world of Generative AI within the GCP environment. From foundational concepts in Generative AI on GCP to advanced techniques using Google Vertex AI, each course equips the learners with the knowledge and skills to create intelligent and creative solutions. Whether it is delving into the intricacies of Generative AI Studio in Vertex AI or exploring the possibilities of building AI-powered apps in GCP, this track offers a transformative learning journey.
- 6 Courses | 7h 43m 55s
COURSES INCLUDED
An Introduction to Generative AI Concepts
This comprehensive course delves deep into the fascinating world of Generative AI. Through a combination of engaging lectures and hands-on practice, participants will gain an in-depth understanding of what generative models are, how they differ from other AI techniques, and the theories and principles underlying them. You will discover various types of generative models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), and explore the process involved in training these models. Then you will examine the strengths, limitations, and practical applications of generative models across various domains, such as image generation, text generation, and data augmentation. Next, you will learn how to evaluate the performance of generative models and focus on ethical considerations in generative AI and the potential societal impact of these technologies. Finally, you will have the opportunity to generate synthetic data using generative models for training and testing purposes and investigate the notion of responsible AI in the generative era. Upon course completion, you will be prepared not just to use these powerful tools, but to use them wisely and ethically.
17 videos |
2h 38m
Assessment
Badge
Generative Modeling Foundations
This course dives deep into the world of generative models, providing learners with a comprehensive understanding of various generative techniques and their applications. This course is carefully designed to bridge theoretical concepts with practical applications, demystifying the methods used in popular generative models like generative adversarial networks (GANs), variational autoencoders (VAEs), and more. Through a combination of rich imagery, illustrative examples, and detailed explanations, participants will explore the differences between generative and discriminative modeling, the foundational framework of generative artificial intelligence (AI), and the various evaluation metrics that gauge the success of these models. Whether you're a budding data scientist, an AI enthusiast, or a seasoned researcher, this course offers a deep dive into the cutting-edge techniques that are shaping the future of artificial intelligence.
14 videos |
1h 57m
Assessment
Badge
Getting Started with Large Language Models (LLMs)
Dive deep into the expansive realm of large language models (LLMs), a pivotal cornerstone in today's artificial intelligence (AI)-driven landscape. This course unravels the intricacies of these models, from their architecture and training methods to their profound implications in real-world scenarios. Begin by exploring the significance of LLMs in the world of AI. Then you will examine the architecture of LLMs, evaluate the impact of data on the effectiveness of LLMs, and fine-tune your LLM for a specific task. Next, you will investigate the ethical implications of using LLMs, including potential biases and privacy issues. Finally, you will discover the potential and limitations of LLMs and learn how to stay updated with the latest advancements in this dynamic field.
13 videos |
1h 36m
Assessment
Badge
Exploring the Depths of Large Language Models in Generative AI
It's important to understand the intricacies of large language models (LLMs) and their pivotal role in the realm of generative artificial intelligence (AI). This course offers an exploration of the architecture, training, and fine-tuning of LLMs. Begin by learning how to implement various techniques tailored for specific generative tasks and delve into the integration of multimodal AI approaches, combining text and visuals. This course not only stresses the technical aspects but also confronts the ethical dilemmas, spotlighting bias and fairness in AI applications. Next, through a blend of theory, demonstrations, and emerging research discussions, explore how the full potential of LLMs can be harnessed and how to prepare for the next wave of AI innovations.
14 videos |
1h 48m
Assessment
Badge
Leveraging Generative AI for Business
In the modern digital era, generative artificial intelligence (AI) emerges as a game-changer, introducing unprecedented capabilities to the business landscape. This course is tailored for professionals seeking to understand the depth and breadth of generative AI's impact on the business world. Dive into the essentials, from the foundational concepts to ethical ramifications and real-world implementations. You will explore the transformative potential of generative AI on business operations, products, and customer experiences and delve into the algorithms propelling these innovations. Discover the possibilities for the interplay of human expertise with AI, managing data for AI deployments, and navigating legal landscapes. At the end of the course, participants will be adept at assessing the business value of generative AI and equipped with the knowledge to strategically integrate it into their organization's digital evolution.
14 videos |
1h 38m
Assessment
Badge
Final Exam: Demystifying Generative AI
Final Exam: Demystifying Generative AI will test your knowledge and application of the topics presented throughout the Demystifying Generative AI track.
1 video |
32s
Assessment
Badge
COURSES INCLUDED
Generative AI on AWS: Getting Started
Amazon Web Services (AWS) provides both AI and generative AI services that can be used for developing and deploying business solutions. In this course, we will begin by introducing the foundational principles of generative artificial intelligence (GenAI). We will explore the benefits AWS offers for generative AI development and deployment. Next, we will delve into the intricacies of foundational models, focusing on their pivotal role in top AI startups and their relationship with generative models. Then, we will explore generative AI services available from AWS, distinguishing them from standard AI offerings, and gaining insight into the nuances of building generative AI systems on AWS. Finally, we will look at the robust infrastructure AWS provides to support generative AI development.
13 videos |
1h 10m
Assessment
Badge
Generative AI on AWS: Building GenAI Models with Amazon SageMaker
This comprehensive course introduces learners to the world of generative artificial intelligence (AI) models within machine learning (ML), focusing on Amazon SageMaker as a prime tool for design, training, optimization, deployment, and monitoring. In this course, we will begin with a deep dive into the fundamental concepts and types of generative models like generative adversarial networks (GANs) and variational autoencoders (VAEs). We will explore their pros, cons, and relevant architectures. Next, we will use hands-on tutorials and in-depth discussions to guide you through the steps of designing a GAN architecture, leveraging SageMaker's built-in algorithms, preprocessing data, and distributed training capabilities. We will then delve into optimization techniques, transfer learning, and quality evaluation methods, looking at ways apply these concepts in real-world scenarios. Lastly, we will introduce deployment strategies in SageMaker, highlighting how to serve models as endpoints for real-time inferences and how to efficiently monitor and troubleshoot their generative models.
14 videos |
1h 35m
Assessment
Badge
Generative AI on AWS: Building GenAI Models with Amazon Bedrock
Dive deep into the world of Amazon Bedrock and examine its applications in generative artificial intelligence (GenAI) development. Starting with the core concepts, this course takes you on a comprehensive journey through the various ways Amazon Bedrock can be applied and the inherent benefits of using it for generative AI development. You will explore the Bedrock console and playgrounds and learn how to design and develop different generative AI models. Then you will focus on evaluating a generative AI project. Finally, you will design a business application using Bedrock and investigate the platform's strengths and weaknesses. At the end of the course, you will be equipped with the skills to design innovative business applications and develop new generative AI models using Amazon Bedrock.
11 videos |
1h 5m
Assessment
Badge
Generative AI on AWS: Generating Code with Amazon CodeWhisperer
In the rapidly evolving world of software development, efficiency and productivity are paramount. This course provides an in-depth exploration of Amazon CodeWhisperer, one of the industry's most cutting-edge tools for automating the code generation process. You will begin by investigating the advantages of artificial intelligence (AI) code generation and its impact on productivity. Then you will explore Amazon CodeWhisperer, focusing on its role in automating code generation, its different techniques for code generation, specific use cases, and key features. Then you will set up CodeWhisperer for various platforms, including JetBrains and JupyterLab. Next, you will examine the code suggestions features of CodeWhisperer and learn how to configure security scans. Finally, you will discover how CodeWhisperer can optimize software development and you will identify best practices for generating and integrating code with CodeWhisperer.
13 videos |
1h 7m
Assessment
Badge
Generative AI on AWS: Generating Speech with Amazon Polly
Delve into the groundbreaking capabilities of Amazon Polly in revolutionizing text-to-speech applications across diverse sectors. Starting with the basics of Polly's text-to-speech technology, you will discover how to preprocess input texts to ensure clarity and effectiveness in speech output. You will learn how to install, design, and use Polly's rich set of voices and languages to create dynamic and engaging audio content for various purposes, from audiobooks to customer service chatbots. Then you will explore Polly's customization options, including adjusting speech rate, pitch, and emphasis to produce natural-sounding speech that fits your specific needs. Next, you will investigate security, speech synthesis, and how to implement Speech Synthesis Markup Language (SSML) tags to add pauses, adjust pronunciation, and control the volume of the speech output, enhancing the listening experience. Finally, you will examine best practices for managing and optimizing your Polly usage to keep costs down while maintaining high-quality speech output.
16 videos |
1h 25m
Assessment
Badge
Generative AI on AWS: Creating Intelligent Chatbots
Dive into the transformative world of Chatbots and their pivotal role in revolutionizing customer interactions. This course deciphers the intricacies of Amazon Lex, a premier tool for crafting conversational interfaces, and its seamless integration with Amazon Polly for lifelike speech. Participants will navigate through the creation of intent-driven, context-aware chatbots, delve deep into advanced capabilities like sentiment analysis and multi-turn conversations, and harness Amazon Polly for dynamic user responses. Moreover, attendees will learn to integrate external services to elevate chatbot functionality, ensuring the end products are not only interactive but also adhere to the highest standards of security, privacy, and compliance.
15 videos |
1h 24m
Assessment
Badge
Generative AI on AWS: Deploying & Managing GenAI Services on AWS
Embark on an enlightening journey into the realm of Generative artificial intelligence (AI) and its transformative impact across diverse industries, powered by AWS's robust suite of services. This course unravels the optimal AWS tools for deploying generative AI models, guiding participants through the nuances of configuration, setup, and deployment options. Engage with best practices for data preparation, model training, and optimization using premier AWS services like Amazon SageMaker. Further, participants will refine their expertise in implementing scalable architectures, leveraging AWS's advanced monitoring tools, ensuring rigorous security protocols, and mastering performance optimization strategies. All these culminate in crafting efficient, scalable, and secure generative AI applications on AWS.
12 videos |
1h 5m
Assessment
Badge
Final Exam: Generative AI on AWS
Final Exam: Generative AI and AWS will test your knowledge and application of the topics presented throughout the Generative AI and AWS track.
1 video |
32s
Assessment
Badge
COURSES INCLUDED
Introduction to Generative AI on Azure
In today's rapidly evolving technological landscape, generative artificial intelligence (AI) has gained significant attention for its ability to create intelligent solutions. This path focuses on leveraging the Azure cloud platform to explore and harness the power of generative AI. In this course, you'll explore how generative AI works and types of generative AI models. Then, you'll be introduced to Azure services for generative AI, including Azure OpenAI service, Azure Bot service, and Azure Machine Learning. Finally, you'll learn about privacy and policy considerations for generative AI, chatbot creation, personalized marketing content, new product development, and training and tuning generative AI models.
14 videos |
1h 24m
Assessment
Badge
Generative AI with Azure OpenAI
Artificial intelligence (AI) is being harnessed everywhere today for a myriad of different practical applications. Microsoft Azure's OpenAI service is a key component in the development of AI apps in Azure and has gained significant attention for its ability to create intelligent solutions. In this course, you'll learn about Azure OpenAI service, including models, practical uses, and AI content generation principles with OpenAI. Then, you'll explore integration with Azure OpenAI, text and question answering, OpenAI vs. other generative AI services, and OpenAI pricing. Finally, you'll dig into limitations of OpenAI and what the future holds for Azure OpenAI.
12 videos |
1h
Assessment
Badge
Deep Dive Into Generative AI with Azure OpenAI
The Azure Cloud platform's generative artificial intelligence (AI) solutions are robust and mature. Encompassing multiple services and supporting rich integration with other Azure services, it's relatively easy to get up and running with generative AI solutions using Azure. In this course, you'll dive deep into generative AI with Azure OpenAI, beginning with an introduction to Azure OpenAI architecture, an overview of OpenAI Studio, and a hands-on demonstration of how to customize models in Azure OpenAI. Then you'll learn how to build a custom app, fine-tune OpenAI models, and deploy models with Azure OpenAI. You'll explore text generation, translation, question answering, image generation, and troubleshooting. Finally, you'll discover Azure OpenAI service integrations, AI Search (formerly Cognitive Search), privacy and compliance issues, and quotas and collaboration with Azure OpenAI.
19 videos |
2h
Assessment
Badge
Generative AI & the Azure Bot AI Service
The chatbot is a popular example of how generative artificial intelligence (AI) is being used today, in all industries and environments. In this course, you will learn about the Azure Bot service and its features, including how generative AI can be leveraged to build intelligent and interactive chatbot applications. You will begin with an introduction to Azure Bot service, generative models and bots, and a high-level discussion of how to build a basic bot. Then you will explore ethical issues surrounding AI-driven bots, find out how to get started with bot creation in Copilot Studio, and learn how to train and deploy models for conversational language understanding (CLU) projects. Next, you will discover Azure Cognitive Services and scaling, and monitoring and troubleshooting bot performance. Finally, you will examine data security, usage auditing, and cost tracking.
14 videos |
1h 16m
Assessment
Badge
Final Exam: Generative AI on Azure
Final Exam: Generative AI and Azure will test your knowledge and application of the topics presented throughout the Generative AI and Azure track.
1 video |
32s
Assessment
Badge
COURSES INCLUDED
Generative AI on GCP: An Introduction
Generative artificial intelligence (AI) has taken the world by storm. Chatbots, photo creation, document writing, and other practical applications are everywhere, and they're gaining in popularity and sophistication. Google Cloud Platform (GCP) has a broad range of powerful generative AI tools that can be used to leverage the power of modern artificial intelligence. In this course, you'll be introduced to generative AI, beginning with GCP and its generative AI offerings. You will discover the advantages and disadvantages of generative AI and features of GCP machine learning (ML). Then you'll learn about the generative AI life cycle, image generation, natural language processing (NLP), and best practices for developing generative AI. Finally, you'll explore GCP privacy, security, and compliance considerations, monitoring and logging with GCP, and some real-world generative AI use cases.
15 videos |
1h 56m
Assessment
Badge
Generative AI on GCP: Empowering Machine Language Workflows with Vertex AI
Google Cloud Platform (GCP) has a broad range of powerful generative AI tools that can be used to leverage the power of modern artificial intelligence (AI). A main component of that toolbox is Google's Vertex AI platform, which can aid organizations in streamlining machine learning (ML) workflows and deliver better machine learning models. In this course, you'll be introduced to Vertex AI, beginning with an overview of its features, model deployment, and end-to-end workflow. Then you'll explore pros and cons of Vertex AI, how it can be used to accelerate development, and model selection, training, and evaluation considerations. Finally, you'll learn about Vertex AI integration, data preparation, feature engineering, model evaluation, and Vertex AI success stories.
12 videos |
1h 39m
Assessment
Badge
Generative AI on GCP: Harnessing Generative AI with Vertex AI
A main component of the Google Cloud Platform (GCP) machine learning offering is Google's Vertex AI Platform, which provides tools that can aid organizations in leveraging Vertex AI for generative artificial intelligence (GenAI) projects. This course investigates the unique support and capabilities offered by Vertex AI specifically for generative AI models, empowering learners to unlock their creative potential. In this course, you will dig into harnessing generative AI using Vertex AI, beginning with an overview of generative AI support in Vertex AI, Vertex AI's generative AI models, and the features and uses of Google's Generative AI Studio. Then you will discover the Vertex AI API, explore Vertex AI Model Garden, and create custom models in Vertex AI. Finally, you will learn about responsible AI with safety filters and find out how to use Vertex AI Search and Conversation. After completing this course, you will be able to confidently leverage Vertex AI to build generative AI models.
12 videos |
1h 13m
Assessment
Badge
Generative AI on GCP: Deep Dive Into Generative AI Studio
Generative artificial intelligence (AI) has taken the world by storm, and Google Cloud Platform (GCP) has a broad range of powerful generative AI tools that can be used to leverage the power of modern artificial intelligence. Google's Generative AI Studio is a cloud console tool for rapid prototyping and testing of generative AI models and leverages the power of Vertex AI, allowing developers to interact, tune, and deploy large-scale AI models. In this course, you will take a deep dive into Generative AI Studio, beginning with generative AI prompt design, model training, and tuning language models. Then you will explore model performance evaluation and generative AI deployment. Next, you will focus on case studies and practical examples to discover how organizations use GCP generative AI. Finally, you will learn how to convert speech to text and prototype language applications.
12 videos |
1h 37m
Assessment
Badge
Generative AI on GCP: Building Generative AI-powered Apps in GCP
Google Cloud Platform (GCP) has a wide range of powerful generative artificial intelligence (AI) services that can leverage the power of modern AI. Using these services, developers can build powerful applications with GCP, and with the proper use of various technologies, developers new to GCP can gain the knowledge and skills necessary to develop and deploy cutting-edge generative AI applications. In this course, you will create a generative AI-powered app in GCP, beginning with planning and building a generative AI model, GCP environment setup, and Python environment creation. Then you will learn how to build and train a generator and a discriminator with TensorFlow. Next, you will build and run a training loop, and dockerize the training script. Finally, you will deploy your finished model to an application programming interface (API) endpoint and test that model.
12 videos |
1h 16m
Assessment
Badge
Final Exam: Generative AI on GCP
Final Exam: Generative AI and GCP will test your knowledge and application of the topics presented throughout the Generative AI and GCP track.
1 video |
32s
Assessment
Badge
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