Introduction
Uncover the necessities of crafting Generative AI functions by means of Microsoft’s Generative AI 18-lesson course for learners. Every phase contains a succinct video introduction, detailed written classes obtainable within the README, and Python and TypeScript Code Samples suitable with Azure OpenAI and OpenAI API. Moreover, entry supplementary assets to additional improve your data on this dynamic area.
Every lesson covers its matter, so begin wherever you prefer to. Classes are labeled both “Study” classes explaining a Generative AI idea or “Construct” classes explaining an idea and code examples in Python and TypeScript when attainable. Every lesson additionally features a “Maintain Studying” part with further studying instruments. Additional, on this weblog you’re going to get to know 18 Microsoft free programs on Gen AI
Stipulations
- Entry to the Azure OpenAI Service or OpenAI API – Solely required to finish coding classes
- Primary data of Python or Typescript is useful – For absolute learners try these Python and TypeScript programs.
- A Github Account to fork this whole repo to your individual GitHub account
They’ve created a Course Setup lesson that will help you with organising your developement surroundings.
Establishing for the Microsoft Free Programs
Fork this Repo
Fork this whole repo to your individual GitHub account to have the ability to change any code and full the challenges. You too can star (🌟) this repo to search out it and associated repos simpler.
Create a Codespace
To keep away from any dependency points when operating the code, we advocate operating this course in a GitHub codespace.
This may be created by choosing the Code possibility in your forked model of this repo and choosing the Codespaces possibility.
Storing Your API Keys
Retaining your API keys protected and safe is vital when constructing any kind of utility. We encourage you to not retailer any API keys instantly within the code you’re working with as committing these particulars to a public repository might end in undesirable prices and points.
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-33.png)
How you can Run domestically in your pc
To run the code domestically in your pc, you would want to have some model of Python put in.
To then use the repository, it is advisable to clone it:
git clone https://github.com/microsoft/generative-ai-for-beginners
cd generative-ai-for-beginners
Now you could have all the pieces checked out and might begin studying and work with the code.
Microsoft Free Programs for Gen AI Studying
Listed here are the Microsoft Free Programs on Gen AI you should know:
Course 1: Introduction to Generative AI and LLMs
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-27.png)
This lesson will cowl:
- Introduction to the enterprise situation: our startup thought and mission.
- Generative AI and the way we landed on the present know-how panorama.
- Internal working of a giant language mannequin.
- Most important capabilities and sensible use circumstances of Massive Language Fashions.
Studying Objectives
After finishing this lesson, you’ll perceive:
- What generative AI is and the way Massive Language Fashions work.
- How one can leverage giant language fashions for various use circumstances, with a deal with training eventualities.
Course 2: Exploring and evaluating completely different LLMs
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-30.png)
This lesson will cowl:
- Several types of LLMs within the present panorama.
- Testing, iterating, and evaluating completely different fashions on your use case in Azure.
- How you can deploy an LLM.
Studying Objectives
After finishing this lesson, it is possible for you to to:
- Choose the correct mannequin on your use case.
- Perceive methods to check, iterate, and enhance efficiency of your mannequin.
- Understand how companies deploy fashions.
Course 3: Utilizing Generative AI Responsibly
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-36.png)
This lesson will cowl:
- Why you must prioritize Accountable AI when constructing Generative AI functions.
- Core rules of Accountable AI and the way they relate to Generative AI.
- How you can put these Accountable AI rules into apply by means of technique and tooling.
Studying Objectives
After finishing this lesson you’ll know:
- The significance of Accountable AI when constructing Generative AI functions.
- When to suppose and apply the core rules of Accountable AI when constructing Generative AI functions.
- What instruments and methods can be found to you to place the idea of Accountable AI into apply.
Course 4: Understanding Immediate Engineering Fundamentals
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-39.png)
On this lesson, we be taught what Immediate Engineering is, why it issues, and the way we will craft more practical prompts for a given mannequin and utility goal. We’ll perceive core ideas and finest practices for immediate engineering – and study an interactive Jupyter Notebooks “sandbox” surroundings the place we will see these ideas utilized to actual examples.
By the top of this lesson we will:
- Clarify what immediate engineering is and why it issues.
- Describe the parts of a immediate and the way they’re used.
- Study finest practices and strategies for immediate engineering.
- Apply realized strategies to actual examples, utilizing an OpenAI endpoint.
Course 5: Creating Superior Prompts
On this chapter, we are going to cowl the next matters:
- Lengthen your data of immediate engineering by making use of completely different strategies to your prompts.
- Configuring your prompts to range the output.
Studying Objectives
After finishing this lesson, you’ll have the ability to:
- Apply immediate engineering strategies that enhance the result of your prompts.
- Carry out prompting that’s both assorted or deterministic.
Course 6: Constructing Textual content Era Functions
On this chapter, you’ll:
- Study concerning the openai library and it’s core ideas.
- Construct a textual content technology app utilizing openai.
- Perceive methods to use ideas like immediate, temperature, and tokens to construct a textual content technology app.
Studying Objectives
On the finish of this lesson, you’ll have the ability to:
- Clarify what a textual content technology app is.
- Construct a textual content technology app utilizing openai.
- Configure your app to make use of roughly tokens and in addition change the temperature, for a assorted output.
Course 7: Constructing Chat Functions
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-26.png)
This lesson covers:
- Strategies for effectively constructing and integrating chat functions.
- How you can apply customization and fine-tuning to functions.
- Methods and issues to successfully monitor chat functions.
Studying Objectives
By the top of this lesson, you’ll have the ability to:
- Describe issues for constructing and integrating chat functions into current methods.
- Customise chat functions for particular use-cases.
- Determine key metrics and issues to watch and preserve the standard of AI-powered chat functions successfully.
- Guarantee chat functions leverage AI responsibly.
Course 8: Constructing Search Apps Vector Databases
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-28.png)
On this lesson, we are going to cowl:
- Semantic vs Key phrase search.
- What are Textual content Embeddings.
- Making a Textual content Embeddings Index.
- Looking out a Textual content Embeddings Index.
Studying Objectives
After finishing this lesson, it is possible for you to to:
- Inform the distinction between semantic and key phrase search.
- Clarify what Textual content Embeddings are.
- Create an utility utilizing Embeddings to seek for knowledge.
Course 9: Constructing Picture Era Functions
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-42.png)
On this lesson, we are going to cowl:
- Picture technology and why it’s helpful.
- DALL-E and Midjourney, what they’re, and the way they work.
- How you’d construct a picture technology app.
Studying Objectives
After finishing this lesson, it is possible for you to to:
- Construct a picture technology utility.
- Outline boundaries on your utility with meta prompts.
- Work with DALL-E and Midjourney.
Course 10: Constructing Low Code AI Functions
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-29.png)
This lesson covers:
- Introduction to Generative AI in Energy Platform
- Introduction to Copilot and methods to use it
- Utilizing Generative AI to construct apps and flows in Energy Platform
- Understanding the AI Fashions in Energy Platform with AI Builder
Studying Objectives
By the top of this lesson, it is possible for you to to:
- Perceive how Copilot works in Energy Platform.
- Construct a Pupil Task Tracker App for our training startup.
- Construct an Bill Processing Move that makes use of AI to extract data from invoices.
- Apply finest practices when utilizing the Create Textual content with GPT AI Mannequin.
Course 11: Integrating Exterior Functions with Operate Calling
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-32.png)
This lesson will cowl:
- Clarify what’s perform calling and its use circumstances.
- Making a perform name utilizing Azure OpenAI.
- How you can combine a perform name into an utility.
Studying Objectives
After finishing this lesson it is possible for you to to:
- Clarify the aim of utilizing perform calling.
- Setup Operate Name utilizing the Azure Open AI Service.
- Design efficient perform calls on your utility’s use case.
Course 12: Designing UX for AI Functions
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-31.png)
The lesson will cowl the next areas:
- Introduction to Person Expertise and Understanding Person Wants
- Designing AI Functions for Belief and Transparency
- Designing AI Functions for Collaboration and Suggestions
Studying Objectives
After taking this lesson, you’ll have the ability to:
- Perceive methods to construct AI functions that meet the person wants.
- Design AI functions that promote belief and collaboration.
Course 13: Securing Your Generative AI Functions
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-40.png)
This lesson will cowl:
- Safety inside the context of AI methods.
- Frequent dangers and threats to AI methods.
- Strategies and issues for securing AI methods.
Studying Objectives
After finishing this lesson, you should have an understanding of:
- The threats and dangers to AI methods.
- Frequent strategies and practices for securing AI methods.
- How implementing safety testing can forestall surprising outcomes and erosion of person belief.
Course 14: The Generative AI Utility Lifecycle
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-37.png)
On this chapter, you’ll:
- Perceive the Paradigm Shift from MLOps to LLMOps
- The LLM Lifecycle
- Lifecycle Tooling
- Lifecycle Metrification and Analysis
Course 15: Retrieval Augmented Era (RAG) and Vector Databases
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-38.png)
On this lesson we are going to cowl the next:
- An introduction to RAG, what it’s and why it’s utilized in AI (synthetic intelligence).
- Understanding what vector databases are and creating one for our utility.
- A sensible instance on methods to combine RAG into an utility.
Studying Objectives
After finishing this lesson, it is possible for you to to:
- Clarify the importance of RAG in knowledge retrieval and processing.
- Setup RAG utility and floor your knowledge to an LLM
- Efficient integration of RAG and Vector Databases in LLM Functions.
Course 16: Open Supply Fashions and Hugging Face
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-34.png)
Studying Objectives
- Achieve an understanding of open supply Fashions
- Understanding the advantages of working with open supply Fashions
- Exploring the open fashions obtainable on Hugging Face and the Azure AI Studio
Course 17: AI Brokers
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-35.png)
AI Brokers symbolize an thrilling growth in Generative AI, enabling Massive Language Fashions (LLMs) to evolve from assistants into brokers able to taking actions. AI Agent frameworks allow builders to create functions that give LLMs entry to instruments and state administration. These frameworks additionally improve visibility, permitting customers and builders to watch the actions deliberate by LLMs, thereby bettering expertise administration.
The lesson will cowl the next areas:
- Understanding what an AI Agent is – What precisely is an AI Agent?
- Exploring 4 completely different AI Agent Frameworks – What makes them distinctive?
- Making use of these AI Brokers to completely different use circumstances – When ought to we use AI Brokers?
Studying Objectives
After taking this lesson, you’ll have the ability to:
- Clarify what AI Brokers are and the way they can be utilized.
- Have an understanding of the variations between among the widespread AI Agent Frameworks, and the way they differ.
- Perceive how AI Brokers perform with a view to construct functions with them.
Course 18: Superb-Tuning LLMs
![Microsoft Free Courses](https://cdn.analyticsvidhya.com/wp-content/uploads/2024/04/image-41.png)
This lesson introduces the idea of fine-tuning for pre-trained language fashions, explores the advantages and challenges of this method, and supplies steerage on when and methods to use effective tuning to enhance the efficiency of your generative AI fashions.
Studying Objectives
- What is ok tuning for language fashions?
- When, and why, is ok tuning helpful?
- How can I fine-tune a pre-trained mannequin?
- What are the restrictions of fine-tuning?
After finishing this lesson, try our Generative AI Studying assortment to proceed leveling up your Generative AI data! Congratsulations!! You have got accomplished the ultimate lesson from the v2 collection for this course! Don’t cease studying and constructing. Take a look at the Assets web page for an inventory of further options for simply this matter.
Conclusion
The given Microsoft Free Programs on Generative AI marks a big stride in the direction of democratizing entry to cutting-edge know-how training. These programs promise to empower learners with the foundational data and sensible abilities wanted to delve into the realm of AI-driven creativity. By offering these Microsoft free programs, Microsoft demonstrates its dedication to fostering innovation and equipping people worldwide with the instruments to harness the potential of Generative AI for numerous functions.
Aside from Microsoft Free Programs, you’ll be able to unlock your potential with the GenAI Pinnacle Program! Elevate your AI experience by means of revolutionary studying and growth. Expertise personalised 1:1 mentorship with industry-leading Generative AI specialists, dive deep into a complicated curriculum that includes over 200 hours of immersive studying, and grasp 26+ cutting-edge GenAI instruments and libraries. Don’t simply be taught AI, pioneer its future with GenAI Pinnacle!