Generative AI for Cloud Solutions
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Generative AI for Cloud Solutions
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What you'll learn
Understand the fundamentals of generative AI, large language models, and their integration with cloud platforms.
Explore advanced techniques such as fine-tuning, prompt engineering, and responsible AI practices.
Gain insights into the development and deployment of AI applications using frameworks like LLMOps and Assistants APIs.
Skills you'll gain
Tools you'll learn
Details to know
February 2026
10 assignments
See how employees at top companies are mastering in-demand skills
There are 10 modules in this course
This course explores how Generative AI is transforming modern cloud solutions by combining large language models with scalable cloud architectures. Learners gain a strategic understanding of how AI-driven systems are designed, deployed, and governed in real-world cloud environments.
Through a structured journey from NLP foundations to advanced LLM-based application development, the course helps learners build practical skills in fine-tuning models, retrieval-augmented generation, and prompt engineering. You will learn how to design, deploy, and scale AI-powered cloud applications while addressing operational and performance challenges. What sets this course apart is its balance of conceptual depth and hands-on architectural thinking. It connects core AI concepts with real-world cloud deployment patterns, Dev frameworks, and LLMOps practices. This course is ideal for cloud engineers, software developers, architects, and technology professionals looking to integrate Generative AI into cloud solutions. A basic understanding of cloud computing and software development concepts is recommended.
In this section, we explore conversational AI and generative AI, focusing on LLMs, open source vs closed source models, and cloud computing for scalable AI implementation.
What's included
2 videos9 readings1 assignment
2 videos•Total 2 minutes
- Course Overview•1 minute
- Cloud Computing Meets Generative AI Bridging Infinite Impossibilities - Overview Video•1 minute
9 readings•Total 130 minutes
- Introduction•20 minutes
- Chatbots and Agents•20 minutes
- Model Parameters•10 minutes
- Deep Dive Open Source vs Closed Source Proprietary Models•10 minutes
- Trending Models, Tasks, and Business Applications•10 minutes
- Image•10 minutes
- Audio•20 minutes
- Cloud Computing for Scalability, Cost Optimization, and Security•10 minutes
- From Vision to Value Navigating the Journey to Production•20 minutes
1 assignment•Total 10 minutes
- Bridging Cloud and AI•10 minutes
In this section, we explore NLP evolution and the role of transformers in AI communication and model development.
What's included
1 video5 readings1 assignment
1 video•Total 1 minute
- NLP Evolution and Transformers Exploring NLPs and LLMs - Overview Video•1 minute
5 readings•Total 55 minutes
- Introduction•10 minutes
- NLP and the Strengths of Generative AI in LLMs•10 minutes
- How Do Transformers Work?•10 minutes
- Conversation Prompts and Completions Under the Covers•20 minutes
- LLMs Landscape, Progression, and Expansion•5 minutes
1 assignment•Total 10 minutes
- NLP and Transformer Fundamentals•10 minutes
In this section, we cover domain-specific LLM fine-tuning, PEFT, and evaluation methods to improve accuracy and reliability.
What's included
1 video6 readings1 assignment
1 video•Total 1 minute
- Fine-Tuning Building Domain-Specific LLM Applications - Overview Video•1 minute
6 readings•Total 120 minutes
- Introduction•10 minutes
- Fine-tuning Applications•30 minutes
- Prompt Tuning Process•20 minutes
- LoRA•20 minutes
- How to Evaluate Fine-Tuned Model Performance•20 minutes
- GLUE and SuperGLUE•20 minutes
1 assignment•Total 10 minutes
- Fine-Tuning and Evaluation in LLM Applications•10 minutes
In this section, we explore retrieval-augmented generation (RAG) to enhance LLM accuracy, focusing on vector databases, chunking strategies, and real-world applications like chatbots and recommendation systems.
What's included
1 video7 readings1 assignment
1 video•Total 1 minute
- RAGs to Riches Elevating AI with External Data - Overview Video•1 minute
7 readings•Total 120 minutes
- Introduction•30 minutes
- Approximate Nearest Neighbors (ANNs)•20 minutes
- Similarity Measures•20 minutes
- How It Works•10 minutes
- Vector DB Limitations•10 minutes
- Common Vector DB Applications•10 minutes
- Business Applications of RAG•20 minutes
1 assignment•Total 10 minutes
- Enhancing AI with External Data•10 minutes
In this section, we explore prompt engineering techniques, emphasizing RAG integration, LLM interaction design, and ethical considerations for effective AI applications.
What's included
1 video4 readings1 assignment
1 video•Total 1 minute
- Effective Prompt Engineering Techniques Unlocking Wisdom Through AI - Overview Video•1 minute
4 readings•Total 70 minutes
- Introduction•10 minutes
- Tokens and Cost Considerations•20 minutes
- Assistant•30 minutes
- Ethical Guidelines for Prompt Engineering•10 minutes
1 assignment•Total 10 minutes
- Mastering Effective AI Interaction Strategies•10 minutes
In this section, we explore generative AI app development frameworks like Semantic Kernel and LangChain, autonomous agents, and LLMOps for operationalizing LLM-based applications.
What's included
1 video8 readings1 assignment
1 video•Total 1 minute
- Developing and Operationalizing LLM-based Apps Exploring Dev Frameworks and LLMOps - Overview Video•1 minute
8 readings•Total 140 minutes
- Introduction•20 minutes
- Fundamental Components•20 minutes
- LangChain•10 minutes
- Autonomous Agents•20 minutes
- AutoGPT•20 minutes
- Discover and Tune•10 minutes
- Comparing MLOps and LLMOps•20 minutes
- Putting It All Together•20 minutes
1 assignment•Total 10 minutes
- Operationalizing Large Language Models in the Cloud•10 minutes
In this section, we explore scaling ChatGPT in cloud environments, analyzing TPM, RPM, and PTU limits, and designing enterprise-ready architectures for efficient and reliable generative AI solutions.
What's included
1 video5 readings1 assignment
1 video•Total 1 minute
- Deploying ChatGPT in the Cloud Architecture Design and Scaling Strategies - Overview Video•1 minute
5 readings•Total 80 minutes
- Introduction•20 minutes
- PTUs•20 minutes
- Retries With Exponential Backoff The Scaling Special Sauce•10 minutes
- Monitoring, Logging, and HTTP Return Codes•10 minutes
- Costs Training and Support•20 minutes
1 assignment•Total 10 minutes
- Deploying AI Services in the Cloud•10 minutes
In this section, we examine security and privacy challenges in generative AI, focusing on risk mitigation, access controls, and secure deployment strategies for LLMs.
What's included
1 video8 readings1 assignment
1 video•Total 1 minute
- Security and Privacy Considerations for Gen AI Building Safe and Secure LLMs - Overview Video•1 minute
8 readings•Total 75 minutes
- Introduction•10 minutes
- Emerging Security Threats A Look at Attack Vectors and Future Challenges•5 minutes
- Jailbreaks and Prompt Injections•10 minutes
- Training Data Poisoning•5 minutes
- Insecure Output Handling•10 minutes
- Azure OpenAI Service API Keys•5 minutes
- What Is Privacy•20 minutes
- Auditing•10 minutes
1 assignment•Total 10 minutes
- Security and Privacy in Generative AI Systems•10 minutes
In this section, we explore responsible AI (RAI) principles, address LLM challenges, and evaluate Deepfake risks to ensure ethical, transparent, and safe AI development.
What's included
1 video8 readings1 assignment
1 video•Total 1 minute
- Responsible Development of AI Solutions Building with Integrity and Care - Overview Video•1 minute
8 readings•Total 95 minutes
- Introduction•10 minutes
- Key Principles of RAI•10 minutes
- Addressing LLM Challenges with RAI Principles•10 minutes
- Rising Deepfake Concern•10 minutes
- How to Spot a Deepfake•5 minutes
- Building Applications Using a Responsible AI-First Approach•10 minutes
- Building Augmenting Loop•10 minutes
- AI, the Cloud, and the Law Understanding Compliance and Regulations•30 minutes
1 assignment•Total 10 minutes
- Ethical and Responsible AI Development•10 minutes
In this section, we explore future AI trends, including multimodal interactions and ChatGPT's evolving trajectory.
What's included
1 video5 readings1 assignment
1 video•Total 1 minute
- The Future of Generative AI Trends and Emerging Use Cases - Overview Video•1 minute
5 readings•Total 95 minutes
- Introduction•30 minutes
- Video Prompts for Video Understanding•30 minutes
- Video Generation Models A Far-Fetched Dream•5 minutes
- Industry-specific Generative AI Apps•10 minutes
- The Rise of Small Language Models (SLMs)•20 minutes
1 assignment•Total 10 minutes
- Exploring the Future of Generative AI•10 minutes
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