Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/panaverse/panaverse.github.io

Certified Web3 and Metaverse Developer Syllabus and Details by Panaverse
https://github.com/panaverse/panaverse.github.io

api csharp decentraland metaverse solidity solidity-dapps typescript unity3d web3

Last synced: 8 days ago
JSON representation

Certified Web3 and Metaverse Developer Syllabus and Details by Panaverse

Awesome Lists containing this project

README 

        

**Master the Future of Tech: Become a Cloud Native Applied Generative AI Engineer (GenEng and CNAI)**



Version: 10.0 (Implementation and adoption starting from July 1, 2024)



[Latest Google Document](https://docs.google.com/document/d/15usu1hkrrRLRjcq_3nCTT-0ljEcgiC44iSdvdqrCprk/edit?usp=sharing)



Today's pivotal technological trends are Cloud Native (CN) and Generative AI (GenAI). Cloud Native technology offers a scalable and dependable platform for application operation, while AI equips these applications with intelligent, human-like capabilities. Our aim is to train you to excel as a Cloud Native Applied Generative AI developer globally.



The Cloud Native Applied Generative AI Certification program equips you to create leading-edge Cloud Native AI solutions using a comprehensive cloud-native and AI platform.



This one-year program equips you with the skills to thrive in the age of Generative AI (GenAI) and cloud native computing (CN).



**Why This Program?**



* **Cutting-Edge Skills:** Develop in-demand skills to build intelligent, scalable cloud applications using Generative AI and Cloud Native technologies.

* **Industry-Ready:** Prepare for global certifications, startup and freelance opportunities after just six months.

* **Future-Proof Your Career:** Stay ahead of the curve in a rapidly evolving tech landscape.



**What You'll Learn:**



* **Develop AI Powered Microservices:** Master Python, build APIs using FastAPI, SQLModel, Postgres, Kafka, Kong, and leverage cutting-edge GenAI APIs like OpenAI, and Open Source AI LLMs.

* **Cloud Native Expertise:** Design and deploy cloud-native applications using Docker, DevContainers, TestContainers, Kubernetes, and Terraform.

* **Custom GPTs and Multi AI Agent Systems:** Learn to fine-tuning foundational AI models, and market them in GPT stores. Learn key principles of designing effective AI agents, and organising a team of AI agents to perform complex, multi-step tasks. Apply these concepts to automate common business processes.



**Flexible Learning:**



* **Hybrid Program:** Combine in-person and online classes for a comprehensive learning experience.

* **Earn While You Learn:** Start freelancing or contributing to projects after the second quarter.



**Program Structure (5 Quarters):**



* **Quarter 1: GenAI Essentials and Python Programming:** We begin the course by understanding GenAI Essentials. We will help people across roles and industries get essential AI skills to boost their productivity. Then we will master the fundamentals of Python, the go-to language for GenAI and Cloud Native API development.

    * **Certification:** 

        * [Google AI Essentials](https://www.coursera.org/learn/google-ai-essentials)

        * [Generative AI for Everyone](https://www.coursera.org/learn/generative-ai-for-everyone)

        * [Certified Professional Python Programmer (CPPP1)](https://pythoninstitute.org/pcpp1)

* **Quarter 2: AI Powered Cloud Native Microservices Development:** Build scalable AI Powered APIs using FastAPI, Postgres, Kafka, Kong, GenAI APIs like OpenAI Chat Completion APIs and Assistant APIs, and Open Source AI LLMs and deploy them using Docker containers.

    * **Certifications:**

        * [PostgreSQL 13 Associate Certification](https://www.enterprisedb.com/course/postgresql-13-associate-certification)

        * [Confluent Certified Developer for Apache Kafka (CCDAK)](https://www.confluent.io/certification/)

* **Quarter 3: Developing Custom GPTs and Multi AI Agent Systems:** Learn to create custom AI models and GPTs using OpenAI, Azure, and Google technologies and integrate them with your Microservices. Use open source libraries, like crewAI, to automate repeatable, multi-step tasks and automate business processes that are typically done by a group of people and deploy them in containers.

    * **Certifications:**

        * [Microsoft Certified: Azure AI Engineer Associate](https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-engineer/?practice-assessment-type=certification)

        * [Certified crewAI Engineer](https://www.crewai.com/)

* **Quarter 4: Developing and Deploying Cloud Native AI and Business Intelligence:** Master Kubernetes and Terraform to train Open Source Foundation LLMs using Fastai and PyTorch and deploy your AI models and applications in the cloud. Visualise data using Power BI.

    * **Certifications:**

        * [Certified Kubernetes Application Developer (CKAD)](https://www.cncf.io/training/certification/ckad/)

        * [HashiCorp Certified: Terraform Associate](https://www.hashicorp.com/certification/terraform-associate)

        * [Microsoft Certified: Power BI Data Analyst Associate](https://learn.microsoft.com/en-us/credentials/certifications/power-bi-data-analyst-associate/?practice-assessment-type=certification)

* **Quarter 5: Front-end Web GUI Development using Next.js and TypeScript:** Next.js is designed to handle complex front-end applications well, making it a good fit for AI applications that might grow in features and data usage over time. Next.js offers features like API routes and file-based routing, which can streamline development for AI applications that need to interact with backend APIs and manage different application views. While Next.js and TypeScript aren't the only options for building AI application frontends, their focus on performance, scalability, and developer experience makes them a compelling choice for many developers.



Generative AI is set to revolutionise our daily lives and work environments. According to McKinsey & Company, generative AI could contribute an annual economic value of $2.6 trillion to $4.4 trillion across various sectors by enhancing automation, bolstering decision-making, and providing personalised experiences. This revolution is pivotal for technology and job landscapes, making it essential knowledge in fast-evolving tech cycles. The rapid emergence of Gen AI-powered technologies and the evolving demand for skills necessitate extensive and timely professional training.



Cloud native is an approach in software development that enables application creation, deployment, and management in cloud environments. It involves constructing applications as a collection of small, interconnected services known as microservices, a shift from traditional monolithic structures. This modular approach enhances the agility of cloud-native applications, allowing them to operate more efficiently with fewer resources.



Technologies such as Kubernetes, Docker, serverless containers, APIs, SQL Databases, and Kafka support developers in swiftly constructing cloud-native applications. These tools offer a standardised platform for application development and management across various cloud services like Azure, Google Cloud, and AWS.



**Advanced Specializations**



Students will have the option of selecting one of the following specialisations after the completion of fifth quarter:



1. **Healthcare and Medical GenAI Specialization**

2. **Web3, Blockchain, and GenAI Integration Specialization**

3. **Metaverse, 3D, and GenAI Integration Specialization**

4. **GenAI for Accounting, Finance, and Banking Specialization**

5. **GenAI for Engineers Specialization**

6. **GenAI for Sales and Marketing Specialization**

8. **GenAI for Cyber Security**

9. **GenAI IoT**